A Next Generation Repository for Sharing Sensitive Network and Security Data

DTIC Science & Technology

2018-01-01

submission, and 5 yearly IRB reviews d. Provided legal support for MOA data provider and host agreements and amendments e. Feedback and bug reporting...intrusion detection methods and systems , b) event- reconstruction and evidence-based insights into global trends (e.g., DDoS attacks and malware...propagation), and c) situational awareness (e.g., outage detection). We have leveraged IMPACT’s policy and legal framework to minimize any risks associated

Mental Imagery and Post-Traumatic Stress Disorder: A Neuroimaging and Experimental Psychopathology Approach to Intrusive Memories of Trauma

PubMed Central

Clark, Ian A.; Mackay, Clare E.

2015-01-01

This hypothesis and theory paper presents a pragmatic framework to help bridge the clinical presentation and neuroscience of intrusive memories following psychological trauma. Intrusive memories are a hallmark symptom of post-traumatic stress disorder (PTSD). However, key questions, including those involving etiology, remain. In particular, we know little about the brain mechanisms involved in why only some moments of the trauma return as intrusive memories while others do not. We first present an overview of the patient experience of intrusive memories and the neuroimaging studies that have investigated intrusive memories in PTSD patients. Next, one mechanism of how to model intrusive memories in the laboratory, the trauma film paradigm, is examined. In particular, we focus on studies combining the trauma film paradigm with neuroimaging. Stemming from the clinical presentation and our current understanding of the processes involved in intrusive memories, we propose a framework in which an intrusive memory comprises five component parts; autobiographical (trauma) memory, involuntary recall, negative emotions, attention hijacking, and mental imagery. Each component part is considered in turn, both behaviorally and from a brain imaging perspective. A mapping of these five components onto our understanding of the brain is described. Unanswered questions that exist in our understanding of intrusive memories are considered using the proposed framework. Overall, we suggest that mental imagery is key to bridging the experience, memory, and intrusive recollection of the traumatic event. Further, we suggest that by considering the brain mechanisms involved in the component parts of an intrusive memory, in particular mental imagery, we may be able to aid the development of a firmer bridge between patients’ experiences of intrusive memories and the clinical neuroscience behind them. PMID:26257660

Intrusion-aware alert validation algorithm for cooperative distributed intrusion detection schemes of wireless sensor networks.

PubMed

Shaikh, Riaz Ahmed; Jameel, Hassan; d'Auriol, Brian J; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

PubMed Central

Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm. PMID:22454568

A Survey on Anomaly Based Host Intrusion Detection System

NASA Astrophysics Data System (ADS)

Jose, Shijoe; Malathi, D.; Reddy, Bharath; Jayaseeli, Dorathi

2018-04-01

An intrusion detection system (IDS) is hardware, software or a combination of two, for monitoring network or system activities to detect malicious signs. In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. The primary function of system is detecting intrusion and gives alerts when user tries to intrusion on timely manner. In these techniques when IDS find out intrusion it will send alert massage to the system administrator. Anomaly detection is an important problem that has been researched within diverse research areas and application domains. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. From the existing anomaly detection techniques, each technique has relative strengths and weaknesses. The current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This survey provides a study of existing anomaly detection techniques, and how the techniques used in one area can be applied in another application domain.

Neural Detection of Malicious Network Activities Using a New Direct Parsing and Feature Extraction Technique

DTIC Science & Technology

2015-09-01

intrusion detection systems , neural networks 15. NUMBER OF PAGES 75 16. PRICE CODE 17. SECURITY CLASSIFICATION OF... detection system (IDS) software, which learns to detect and classify network attacks and intrusions through prior training data. With the added criteria of...BACKGROUND The growing threat of malicious network activities and intrusion attempts makes intrusion detection systems (IDS) a

From measurements to metrics: PCA-based indicators of cyber anomaly

NASA Astrophysics Data System (ADS)

Ahmed, Farid; Johnson, Tommy; Tsui, Sonia

2012-06-01

We present a framework of the application of Principal Component Analysis (PCA) to automatically obtain meaningful metrics from intrusion detection measurements. In particular, we report the progress made in applying PCA to analyze the behavioral measurements of malware and provide some preliminary results in selecting dominant attributes from an arbitrary number of malware attributes. The results will be useful in formulating an optimal detection threshold in the principal component space, which can both validate and augment existing malware classifiers.

A Feasibility Study on the Application of the ScriptGenE Framework as an Anomaly Detection System in Industrial Control Systems

DTIC Science & Technology

2015-09-17

network intrusion detection systems NIST National Institute of Standards and Technology p-tree protocol tree PI protocol informatics PLC programmable logic...electrical, water, oil , natural gas, manufacturing, and pharmaceutical industries, to name a few. The differences between SCADA and DCS systems are often... Oil Company, also known as Saudi Aramco, suffered huge data loss that resulted in the disruption of daily operations for nearly two weeks [BTR13]. As it

Intrusion Detection in Control Systems using Sequence Characteristics

NASA Astrophysics Data System (ADS)

Kiuchi, Mai; Onoda, Takashi

Intrusion detection is considered effective in control systems. Sequences of the control application behavior observed in the communication, such as the order of the control device to be controlled, are important in control systems. However, most intrusion detection systems do not effectively reflect sequences in the application layer into the detection rules. In our previous work, we considered utilizing sequences for intrusion detection in control systems, and demonstrated the usefulness of sequences for intrusion detection. However, manually writing the detection rules for a large system can be difficult, so using machine learning methods becomes feasible. Also, in the case of control systems, there have been very few observed cyber attacks, so we have very little knowledge of the attack data that should be used to train the intrusion detection system. In this paper, we use an approach that combines CRF (Conditional Random Field) considering the sequence of the system, thus able to reflect the characteristics of control system sequences into the intrusion detection system, and also does not need the knowledge of attack data to construct the detection rules.

Application of a Hidden Bayes Naive Multiclass Classifier in Network Intrusion Detection

ERIC Educational Resources Information Center

Koc, Levent

2013-01-01

With increasing Internet connectivity and traffic volume, recent intrusion incidents have reemphasized the importance of network intrusion detection systems for combating increasingly sophisticated network attacks. Techniques such as pattern recognition and the data mining of network events are often used by intrusion detection systems to classify…

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

PubMed

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

Intrusion detection: systems and models

NASA Technical Reports Server (NTRS)

Sherif, J. S.; Dearmond, T. G.

2002-01-01

This paper puts forward a review of state of the art and state of the applicability of intrusion detection systems, and models. The paper also presents a classfication of literature pertaining to intrusion detection.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid

PubMed Central

Li, Yuancheng; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can’t satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy. PMID:29485990

The architecture of a network level intrusion detection system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heady, R.; Luger, G.; Maccabe, A.

1990-08-15

This paper presents the preliminary architecture of a network level intrusion detection system. The proposed system will monitor base level information in network packets (source, destination, packet size, and time), learning the normal patterns and announcing anomalies as they occur. The goal of this research is to determine the applicability of current intrusion detection technology to the detection of network level intrusions. In particular, the authors are investigating the possibility of using this technology to detect and react to worm programs.

Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks

NASA Astrophysics Data System (ADS)

Zhang, Huibin; Wang, Yuqiao; Chen, Haoran; Zhao, Yongli; Zhang, Jie

2017-12-01

In software defined optical networks (SDON), the centralized control plane may encounter numerous intrusion threatens which compromise the security level of provisioned services. In this paper, the issue of control plane security is studied and two machine-learning-based control plane intrusion detection techniques are proposed for SDON with properly selected features such as bandwidth, route length, etc. We validate the feasibility and efficiency of the proposed techniques by simulations. Results show an accuracy of 83% for intrusion detection can be achieved with the proposed machine-learning-based control plane intrusion detection techniques.

Porting Extremely Lightweight Intrusion Detection (ELIDe) to Android

DTIC Science & Technology

2015-10-01

ARL-TN-0681 ● OCT 2015 US Army Research Laboratory Porting Extremely Lightweight Intrusion Detection (ELIDe) to Android by...Lightweight Intrusion Detection (ELIDe) to Android by Ken F Yu and Garret S Payer Computational and Information Sciences Directorate, ARL...

Unsupervised algorithms for intrusion detection and identification in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2009-05-01

In previous work by the author, parameters across network protocol layers were selected as features in supervised algorithms that detect and identify certain intrusion attacks on wireless ad hoc sensor networks (WSNs) carrying multisensor data. The algorithms improved the residual performance of the intrusion prevention measures provided by any dynamic key-management schemes and trust models implemented among network nodes. The approach of this paper does not train algorithms on the signature of known attack traffic, but, instead, the approach is based on unsupervised anomaly detection techniques that learn the signature of normal network traffic. Unsupervised learning does not require the data to be labeled or to be purely of one type, i.e., normal or attack traffic. The approach can be augmented to add any security attributes and quantified trust levels, established during data exchanges among nodes, to the set of cross-layer features from the WSN protocols. A two-stage framework is introduced for the security algorithms to overcome the problems of input size and resource constraints. The first stage is an unsupervised clustering algorithm which reduces the payload of network data packets to a tractable size. The second stage is a traditional anomaly detection algorithm based on a variation of support vector machines (SVMs), whose efficiency is improved by the availability of data in the packet payload. In the first stage, selected algorithms are adapted to WSN platforms to meet system requirements for simple parallel distributed computation, distributed storage and data robustness. A set of mobile software agents, acting like an ant colony in securing the WSN, are distributed at the nodes to implement the algorithms. The agents move among the layers involved in the network response to the intrusions at each active node and trustworthy neighborhood, collecting parametric values and executing assigned decision tasks. This minimizes the need to move large amounts of audit-log data through resource-limited nodes and locates routines closer to that data. Performance of the unsupervised algorithms is evaluated against the network intrusions of black hole, flooding, Sybil and other denial-of-service attacks in simulations of published scenarios. Results for scenarios with intentionally malfunctioning sensors show the robustness of the two-stage approach to intrusion anomalies.

A prototype implementation of a network-level intrusion detection system. Technical report number CS91-11

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heady, R.; Luger, G.F.; Maccabe, A.B.

1991-05-15

This paper presents the implementation of a prototype network level intrusion detection system. The prototype system monitors base level information in network packets (source, destination, packet size, time, and network protocol), learning the normal patterns and announcing anomalies as they occur. The goal of this research is to determine the applicability of current intrusion detection technology to the detection of network level intrusions. In particular, the authors are investigating the possibility of using this technology to detect and react to worm programs.

Identification and Control of Pollution from Salt Water Intrusion.

ERIC Educational Resources Information Center

Environmental Protection Agency, Washington, DC. Office of Water Programs.

This document contains informational guidelines for identifying and evaluating the nature and extent of pollution from salt water intrusion. The intent of these guidelines is to provide a basic framework for assessing salt water intrusion problems and their relationship to the total hydrologic system, and to provide assistance in developing…

Machine Learning in Intrusion Detection

DTIC Science & Technology

2005-07-01

machine learning tasks. Anomaly detection provides the core technology for a broad spectrum of security-centric applications. In this dissertation, we examine various aspects of anomaly based intrusion detection in computer security. First, we present a new approach to learn program behavior for intrusion detection. Text categorization techniques are adopted to convert each process to a vector and calculate the similarity between two program activities. Then the k-nearest neighbor classifier is employed to classify program behavior as normal or intrusive. We demonstrate

Real-time distributed fiber optic sensor for security systems: Performance, event classification and nuisance mitigation

NASA Astrophysics Data System (ADS)

Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

2012-09-01

The success of any perimeter intrusion detection system depends on three important performance parameters: the probability of detection (POD), the nuisance alarm rate (NAR), and the false alarm rate (FAR). The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings (LCs) based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder (MZ) interferometer.

Intrusion Detection in Database Systems

NASA Astrophysics Data System (ADS)

Javidi, Mohammad M.; Sohrabi, Mina; Rafsanjani, Marjan Kuchaki

Data represent today a valuable asset for organizations and companies and must be protected. Ensuring the security and privacy of data assets is a crucial and very difficult problem in our modern networked world. Despite the necessity of protecting information stored in database systems (DBS), existing security models are insufficient to prevent misuse, especially insider abuse by legitimate users. One mechanism to safeguard the information in these databases is to use an intrusion detection system (IDS). The purpose of Intrusion detection in database systems is to detect transactions that access data without permission. In this paper several database Intrusion detection approaches are evaluated.

A New Intrusion Detection Method Based on Antibody Concentration

NASA Astrophysics Data System (ADS)

Zeng, Jie; Li, Tao; Li, Guiyang; Li, Haibo

Antibody is one kind of protein that fights against the harmful antigen in human immune system. In modern medical examination, the health status of a human body can be diagnosed by detecting the intrusion intensity of a specific antigen and the concentration indicator of corresponding antibody from human body’s serum. In this paper, inspired by the principle of antigen-antibody reactions, we present a New Intrusion Detection Method Based on Antibody Concentration (NIDMBAC) to reduce false alarm rate without affecting detection rate. In our proposed method, the basic definitions of self, nonself, antigen and detector in the intrusion detection domain are given. Then, according to the antigen intrusion intensity, the change of antibody number is recorded from the process of clone proliferation for detectors based on the antigen classified recognition. Finally, building upon the above works, a probabilistic calculation method for the intrusion alarm production, which is based on the correlation between the antigen intrusion intensity and the antibody concen-tration, is proposed. Our theoretical analysis and experimental results show that our proposed method has a better performance than traditional methods.

Fingerprinting Software Defined Networks and Controllers

DTIC Science & Technology

2015-03-01

24 2.5.3 Intrusion Prevention System with SDN . . . . . . . . . . . . . . . 25 2.5.4 Modular Security Services...Control Message Protocol IDS Intrusion Detection System IPS Intrusion Prevention System ISP Internet Service Provider LLDP Link Layer Discovery Protocol...layer functions (e.g., web proxies, firewalls, intrusion detection/prevention, load balancers, etc.). The increase in switch capabilities combined

Conjunctive Management of Multi-Aquifer System for Saltwater Intrusion Mitigation

NASA Astrophysics Data System (ADS)

Tsai, F. T. C.; Pham, H. V.

2015-12-01

Due to excessive groundwater withdrawals, many water wells in Baton Rouge, Louisiana experience undesirable chloride concentration because of saltwater intrusion. The study goal is to develop a conjunctive management framework that takes advantage of the Baton Rouge multi-aquifer system to mitigate saltwater intrusion. The conjunctive management framework utilizes several hydraulic control techniques to mitigate saltwater encroachment. These hydraulic control approaches include pumping well relocation, freshwater injection, saltwater scavenging, and their combinations. Specific objectives of the study are: (1) constructing scientific geologic architectures of the "800-foot" sand, the "1,000-foot" sand, the "1,200-foot" sand, the "1,500-foot" sand, the "1,700-foot" sand, and the "2,000-foot" sand, (2) developing scientific saltwater intrusion models for these sands. (3) using connector wells to draw native groundwater from one sand and inject to another sand to create hydraulic barriers to halt saltwater intrusion, (4) using scavenger wells or well couples to impede saltwater intrusion progress and reduce chloride concentration in pumping wells, and (5) reducing cones of depression by relocating and dispersing pumping wells to different sands. The study utilizes optimization techniques and newest LSU high performance computing (HPC) facilities to derive solutions. The conjunctive management framework serves as a scientific tool to assist policy makers to solve the urgent saltwater encroachment issue in the Baton Rouge area. The research results will help water companies as well as industries in East Baton Rouge Parish and neighboring parishes by reducing their saltwater intrusion threats, which in turn would sustain Capital Area economic development.

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT.

PubMed

Lopez-Martin, Manuel; Carro, Belen; Sanchez-Esguevillas, Antonio; Lloret, Jaime

2017-08-26

The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host's network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery.

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT

PubMed Central

Carro, Belen; Sanchez-Esguevillas, Antonio

2017-01-01

The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery. PMID:28846608

A novel interacting multiple model based network intrusion detection scheme

NASA Astrophysics Data System (ADS)

Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

2006-04-01

In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.

Distributed intrusion detection system based on grid security model

NASA Astrophysics Data System (ADS)

Su, Jie; Liu, Yahui

2008-03-01

Grid computing has developed rapidly with the development of network technology and it can solve the problem of large-scale complex computing by sharing large-scale computing resource. In grid environment, we can realize a distributed and load balance intrusion detection system. This paper first discusses the security mechanism in grid computing and the function of PKI/CA in the grid security system, then gives the application of grid computing character in the distributed intrusion detection system (IDS) based on Artificial Immune System. Finally, it gives a distributed intrusion detection system based on grid security system that can reduce the processing delay and assure the detection rates.

The study and implementation of the wireless network data security model

NASA Astrophysics Data System (ADS)

Lin, Haifeng

2013-03-01

In recent years, the rapid development of Internet technology and the advent of information age, people are increasing the strong demand for the information products and the market for information technology. Particularly, the network security requirements have become more sophisticated. This paper analyzes the wireless network in the data security vulnerabilities. And a list of wireless networks in the framework is the serious defects with the related problems. It has proposed the virtual private network technology and wireless network security defense structure; and it also given the wireless networks and related network intrusion detection model for the detection strategies.

Detection and recognition of mechanical, digging and vehicle signals in the optical fiber pre-warning system

NASA Astrophysics Data System (ADS)

Tian, Qing; Yang, Dan; Zhang, Yuan; Qu, Hongquan

2018-04-01

This paper presents detection and recognition method to locate and identify harmful intrusions in the optical fiber pre-warning system (OFPS). Inspired by visual attention architecture (VAA), the process flow is divided into two parts, i.e., data-driven process and task-driven process. At first, data-driven process takes all the measurements collected by the system as input signals, which is handled by detection method to locate the harmful intrusion in both spatial domain and time domain. Then, these detected intrusion signals are taken over by task-driven process. Specifically, we get pitch period (PP) and duty cycle (DC) of the intrusion signals to identify the mechanical and manual digging (MD) intrusions respectively. For the passing vehicle (PV) intrusions, their strong low frequency component can be used as good feature. In generally, since the harmful intrusion signals only account for a small part of whole measurements, the data-driven process reduces the amount of input data for subsequent task-driven process considerably. Furthermore, the task-driven process determines the harmful intrusions orderly according to their severity, which makes a priority mechanism for the system as well as targeted processing for different harmful intrusion. At last, real experiments are performed to validate the effectiveness of this method.

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

PubMed Central

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

PubMed

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

An automatically tuning intrusion detection system.

PubMed

Yu, Zhenwei; Tsai, Jeffrey J P; Weigert, Thomas

2007-04-01

An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

Realistic computer network simulation for network intrusion detection dataset generation

NASA Astrophysics Data System (ADS)

Payer, Garrett

2015-05-01

The KDD-99 Cup dataset is dead. While it can continue to be used as a toy example, the age of this dataset makes it all but useless for intrusion detection research and data mining. Many of the attacks used within the dataset are obsolete and do not reflect the features important for intrusion detection in today's networks. Creating a new dataset encompassing a large cross section of the attacks found on the Internet today could be useful, but would eventually fall to the same problem as the KDD-99 Cup; its usefulness would diminish after a period of time. To continue research into intrusion detection, the generation of new datasets needs to be as dynamic and as quick as the attacker. Simply examining existing network traffic and using domain experts such as intrusion analysts to label traffic is inefficient, expensive, and not scalable. The only viable methodology is simulation using technologies including virtualization, attack-toolsets such as Metasploit and Armitage, and sophisticated emulation of threat and user behavior. Simulating actual user behavior and network intrusion events dynamically not only allows researchers to vary scenarios quickly, but enables online testing of intrusion detection mechanisms by interacting with data as it is generated. As new threat behaviors are identified, they can be added to the simulation to make quicker determinations as to the effectiveness of existing and ongoing network intrusion technology, methodology and models.

Intrusion Detection: Generics and State-of-the-Art (la Detection de l’intrusion: Modeles generiques et etat de l’art)

DTIC Science & Technology

2002-01-01

by the user for a number of possible pre-defined intrusions. One of these pre-defined intrusions is the command “get /etc/ passwd ”. If this command is...Application-level firewalls: which check communication at the application level. An example is the string get /etc/ passwd in the ftp protocol

Implementing and testing a fiber-optic polarization-based intrusion detection system

NASA Astrophysics Data System (ADS)

Hajj, Rasha El; MacDonald, Gregory; Verma, Pramode; Huck, Robert

2015-09-01

We describe a layer-1-based intrusion detection system for fiber-optic-based networks. Layer-1-based intrusion detection represents a significant elevation in security as it prohibits an adversary from obtaining information in the first place (no cryptanalysis is possible). We describe the experimental setup of the intrusion detection system, which is based on monitoring the behavior of certain attributes of light both in unperturbed and perturbed optical fiber links. The system was tested with optical fiber links of various lengths and types, under different environmental conditions, and under changes in fiber geometry similar to what is experienced during tapping activity. Comparison of the results for perturbed and unperturbed links has shown that the state of polarization is more sensitive to intrusion activity than the degree of polarization or power of the received light. The testing was conducted in a simulated telecommunication network environment that included both underground and aerial links. The links were monitored for intrusion activity. Attempts to tap the link were easily detected with no apparent degradation in the visual quality of the real-time surveillance video.

Research on recognition of the geologic framework of porphyry copper deposits on ERTS-1 imagery. [New Guinea, Alaska, and Colorado

NASA Technical Reports Server (NTRS)

Wilson, J. C. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Many new linear and circular features were found. These features prompted novel tectonic classification and analysis especially in the Ray and Ely areas. Tectonic analyses of the Ok Tedi, Tanacross, and Silvertone areas follow conventional interpretations. Circular features are mapped in many cases and are interpreted as exposed or covered intrusive centers. The small circular features reported in the Ok Tedi test area are valid and useful correlations with tertiary intrusion and volcanism in this remote part of New Guinea. Several major faults of regional dimensions, such as the Denali fault in Alaska and the Colorado mineral belt structures in Colorado are detected in the imagery. Many more faults and regional structures are found in the imagery than exist on present maps.

Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection

NASA Astrophysics Data System (ADS)

Elfers, Carsten; Horstmann, Mirko; Sohr, Karsten; Herzog, Otthein

Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine learning techniques have been proposed. However, one critical issue is that the amount of reference data that contains serious intrusions is very sparse. In this paper we present an inference process with linear chain conditional random fields that aims to solve this problem by using domain knowledge about the alerts of different intrusion sensors represented in an ontology.

A system for distributed intrusion detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snapp, S.R.; Brentano, J.; Dias, G.V.

1991-01-01

The study of providing security in computer networks is a rapidly growing area of interest because the network is the medium over which most attacks or intrusions on computer systems are launched. One approach to solving this problem is the intrusion-detection concept, whose basic premise is that not only abandoning the existing and huge infrastructure of possibly-insecure computer and network systems is impossible, but also replacing them by totally-secure systems may not be feasible or cost effective. Previous work on intrusion-detection systems were performed on stand-alone hosts and on a broadcast local area network (LAN) environment. The focus of ourmore » present research is to extend our network intrusion-detection concept from the LAN environment to arbitarily wider areas with the network topology being arbitrary as well. The generalized distributed environment is heterogeneous, i.e., the network nodes can be hosts or servers from different vendors, or some of them could be LAN managers, like our previous work, a network security monitor (NSM), as well. The proposed architecture for this distributed intrusion-detection system consists of the following components: a host manager in each host; a LAN manager for monitoring each LAN in the system; and a central manager which is placed at a single secure location and which receives reports from various host and LAN managers to process these reports, correlate them, and detect intrusions. 11 refs., 2 figs.« less

Protecting against cyber threats in networked information systems

NASA Astrophysics Data System (ADS)

Ertoz, Levent; Lazarevic, Aleksandar; Eilertson, Eric; Tan, Pang-Ning; Dokas, Paul; Kumar, Vipin; Srivastava, Jaideep

2003-07-01

This paper provides an overview of our efforts in detecting cyber attacks in networked information systems. Traditional signature based techniques for detecting cyber attacks can only detect previously known intrusions and are useless against novel attacks and emerging threats. Our current research at the University of Minnesota is focused on developing data mining techniques to automatically detect attacks against computer networks and systems. This research is being conducted as a part of MINDS (Minnesota Intrusion Detection System) project at the University of Minnesota. Experimental results on live network traffic at the University of Minnesota show that the new techniques show great promise in detecting novel intrusions. In particular, during the past few months our techniques have been successful in automatically identifying several novel intrusions that could not be detected using state-of-the-art tools such as SNORT.

Intelligent agent-based intrusion detection system using enhanced multiclass SVM.

PubMed

Ganapathy, S; Yogesh, P; Kannan, A

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

PubMed Central

Ganapathy, S.; Yogesh, P.; Kannan, A.

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

Evidential reasoning research on intrusion detection

NASA Astrophysics Data System (ADS)

Wang, Xianpei; Xu, Hua; Zheng, Sheng; Cheng, Anyu

2003-09-01

In this paper, we mainly aim at D-S theory of evidence and the network intrusion detection these two fields. It discusses the method how to apply this probable reasoning as an AI technology to the Intrusion Detection System (IDS). This paper establishes the application model, describes the new mechanism of reasoning and decision-making and analyses how to implement the model based on the synscan activities detection on the network. The results suggest that if only rational probability values were assigned at the beginning, the engine can, according to the rules of evidence combination and hierarchical reasoning, compute the values of belief and finally inform the administrators of the qualities of the traced activities -- intrusions, normal activities or abnormal activities.

Analysis of a SCADA System Anomaly Detection Model Based on Information Entropy

DTIC Science & Technology

2014-03-27

20 Intrusion Detection...alarms ( Rem ). ............................................................................................................. 86 Figure 25. TP% for...literature concerning the focus areas of this research. The focus areas include SCADA vulnerabilities, information theory, and intrusion detection

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

DTIC Science & Technology

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

State of the Practice of Intrusion Detection Technologies

DTIC Science & Technology

2000-01-01

security incident response teams ) - the role of IDS in threat management, such as defining alarm severity, monitoring, alerting, and policy-based...attacks in an effort to sneak under the radar of security specialists and intrusion detection software, a U.S. Navy network security team said today...to get the smoking gun," said Stephen Northcutt, head of the Shadow intrusion detection team at the Naval Surface Warfare Center. "To know what’s

Unsupervised Anomaly Detection Based on Clustering and Multiple One-Class SVM

NASA Astrophysics Data System (ADS)

Song, Jungsuk; Takakura, Hiroki; Okabe, Yasuo; Kwon, Yongjin

Intrusion detection system (IDS) has played an important role as a device to defend our networks from cyber attacks. However, since it is unable to detect unknown attacks, i.e., 0-day attacks, the ultimate challenge in intrusion detection field is how we can exactly identify such an attack by an automated manner. Over the past few years, several studies on solving these problems have been made on anomaly detection using unsupervised learning techniques such as clustering, one-class support vector machine (SVM), etc. Although they enable one to construct intrusion detection models at low cost and effort, and have capability to detect unforeseen attacks, they still have mainly two problems in intrusion detection: a low detection rate and a high false positive rate. In this paper, we propose a new anomaly detection method based on clustering and multiple one-class SVM in order to improve the detection rate while maintaining a low false positive rate. We evaluated our method using KDD Cup 1999 data set. Evaluation results show that our approach outperforms the existing algorithms reported in the literature; especially in detection of unknown attacks.

Using Machine Learning in Adversarial Environments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warren Leon Davis

Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approachesmore » only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.« less

HMM Sequential Hypothesis Tests for Intrusion Detection in MANETs Extended Abstract

DTIC Science & Technology

2003-01-01

securing the routing protocols of mobile ad hoc wireless net- works has been done in prevention. Intrusion detection systems play a complimentary...TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 10 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified...hops of A would be unable to communicate with B and vice versa [1]. 1.2 The role of intrusion detection in security In order to provide reliable

Railway clearance intrusion detection method with binocular stereo vision

NASA Astrophysics Data System (ADS)

Zhou, Xingfang; Guo, Baoqing; Wei, Wei

2018-03-01

In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou's method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera's image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

Research on artificial neural network intrusion detection photochemistry based on the improved wavelet analysis and transformation

NASA Astrophysics Data System (ADS)

Li, Hong; Ding, Xue

2017-03-01

This paper combines wavelet analysis and wavelet transform theory with artificial neural network, through the pretreatment on point feature attributes before in intrusion detection, to make them suitable for improvement of wavelet neural network. The whole intrusion classification model gets the better adaptability, self-learning ability, greatly enhances the wavelet neural network for solving the problem of field detection invasion, reduces storage space, contributes to improve the performance of the constructed neural network, and reduces the training time. Finally the results of the KDDCup99 data set simulation experiment shows that, this method reduces the complexity of constructing wavelet neural network, but also ensures the accuracy of the intrusion classification.

State-of-the-art technologies for intrusion and obstacle detection for railroad operations

DOT National Transportation Integrated Search

2007-07-01

This report provides an update on the state-of-the-art technologies with intrusion and obstacle detection capabilities for rail rights of way (ROW) and crossings. A workshop entitled Intruder and Obstacle Detection Systems (IODS) for Railroads Requir...

Intrusive [r] and Optimal Epenthetic Consonants

ERIC Educational Resources Information Center

Uffmann, Christian

2007-01-01

This paper argues against the view of intrusive [r] as a synchronically arbitrary insertion process. Instead, it is seen as a phonologically natural process, which can be modelled within the framework of Optimality Theory (OT). Insertion of [r] in phonologically restricted environments is a consequence of a more general theory of consonant…

The relationship between loss of parents in the holocaust, intrusive memories, and distress among child survivors.

PubMed

Letzter-Pouw, Sonia; Werner, Perla

2012-04-01

The prevalence of intrusive memories of the Holocaust and their relationship to distress was examined among 272 child survivors in Israel. Using attachment theory as a conceptual framework, the authors also examined the effects of type of experience and loss of parents in the Holocaust, psychological resources, other life events, and sociodemographic characteristics on distress and symptomatic behavior. Eighty five percent of the participants reported suffering from intrusive memories. Structural equation modeling showed that survivors who lost one or both parents in the Holocaust suffered more distress because of more intrusive memories. These findings suggest that intrusive memories may be part of unfinished mourning processes related to the loss of parents in the Holocaust. © 2012 American Orthopsychiatric Association.

Anomaly-based intrusion detection for SCADA systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, D.; Usynin, A.; Hines, J. W.

2006-07-01

Most critical infrastructure such as chemical processing plants, electrical generation and distribution networks, and gas distribution is monitored and controlled by Supervisory Control and Data Acquisition Systems (SCADA. These systems have been the focus of increased security and there are concerns that they could be the target of international terrorists. With the constantly growing number of internet related computer attacks, there is evidence that our critical infrastructure may also be vulnerable. Researchers estimate that malicious online actions may cause $75 billion at 2007. One of the interesting countermeasures for enhancing information system security is called intrusion detection. This paper willmore » briefly discuss the history of research in intrusion detection techniques and introduce the two basic detection approaches: signature detection and anomaly detection. Finally, it presents the application of techniques developed for monitoring critical process systems, such as nuclear power plants, to anomaly intrusion detection. The method uses an auto-associative kernel regression (AAKR) model coupled with the statistical probability ratio test (SPRT) and applied to a simulated SCADA system. The results show that these methods can be generally used to detect a variety of common attacks. (authors)« less

Visualization techniques for computer network defense

NASA Astrophysics Data System (ADS)

Beaver, Justin M.; Steed, Chad A.; Patton, Robert M.; Cui, Xiaohui; Schultz, Matthew

2011-06-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operator to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.

Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Şen, Sevil; Clark, John A.; Tapiador, Juan E.

Mobile ad hoc networks (MANETs) are a highly promising new form of networking. However they are more vulnerable to attacks than wired networks. In addition, conventional intrusion detection systems (IDS) are ineffective and inefficient for highly dynamic and resource-constrained environments. Achieving an effective operational MANET requires tradeoffs to be made between functional and non-functional criteria. In this paper we show how Genetic Programming (GP) together with a Multi-Objective Evolutionary Algorithm (MOEA) can be used to synthesise intrusion detection programs that make optimal tradeoffs between security criteria and the power they consume.

Scheduling Randomly-Deployed Heterogeneous Video Sensor Nodes for Reduced Intrusion Detection Time

NASA Astrophysics Data System (ADS)

Pham, Congduc

This paper proposes to use video sensor nodes to provide an efficient intrusion detection system. We use a scheduling mechanism that takes into account the criticality of the surveillance application and present a performance study of various cover set construction strategies that take into account cameras with heterogeneous angle of view and those with very small angle of view. We show by simulation how a dynamic criticality management scheme can provide fast event detection for mission-critical surveillance applications by increasing the network lifetime and providing low stealth time of intrusions.

Network intrusion detection by the coevolutionary immune algorithm of artificial immune systems with clonal selection

NASA Astrophysics Data System (ADS)

Salamatova, T.; Zhukov, V.

2017-02-01

The paper presents the application of the artificial immune systems apparatus as a heuristic method of network intrusion detection for algorithmic provision of intrusion detection systems. The coevolutionary immune algorithm of artificial immune systems with clonal selection was elaborated. In testing different datasets the empirical results of evaluation of the algorithm effectiveness were achieved. To identify the degree of efficiency the algorithm was compared with analogs. The fundamental rules based of solutions generated by this algorithm are described in the article.

Research on intrusion detection based on Kohonen network and support vector machine

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

Characterization of Saharan dust ageing over the western Mediterranean Basin during a multi-intrusion event in June 2013 in the framework of the ADRIMED/ChArMEx campaign

NASA Astrophysics Data System (ADS)

Barragan, Ruben; Sicard, Michaël; Totems, Julien; François Léon, Jean; Baptiste Renard, Jean; Dulac, François; Mallet, Marc; Pelon, Jacques; Alados-Arboledas, Lucas; Amodeo, Aldo; José Granados-Muñoz, María; Boselli, Antonella; Bravo-Aranda, Juan Antonio; Muñoz-Porcar, Constantino; Chazette, Patrick; Comerón, Adolfo; D'Amico, Giuseppe; Wang, Xuan; Mona, Lucia; Pappalardo, Gelsomina

2015-04-01

In the framework of the ChArMEx (Chemistry-Aerosol Mediterranean Experiment, http://charmex.lsce.ipsl.fr/) initiative, a field campaign took place in the western Mediterranean Basin between 10 June and 5 July 2013 within the ADRIMED (Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) project. The scientific objectives of the campaign were the characterization of the different aerosol types found over the Mediterranean Sea and the calculation of their direct radiative forcing (column closure and regional scale). Two super-sites (Ersa, Corsica Island, France, and Lampedusa Island, Italy) were equipped with a complete set of instruments to measure in-situ aerosol physical, chemical and optical properties, as well as aerosol mixing state and vertical distribution and radiative fluxes. Four secondary sites were operated in Granada (Spain), Menorca Island (Spain), Rome (Italy) and Lecce (Italy). All sites were equipped with AERONET sunphotometers. The ground observations were supported by airborne measurements including 2 SAFIRE aircraft (ATR-42 equipped with in situ measurements (10 June - 5 July) and Falcon-20 (17 June - 5 July) with the LNG aerosol lidar) and sounding and drifting balloons launched by CNES from Menorca Island and carrying the LOAC particle counter/sizer (16 June - 4 July). Satellite products from MODIS, MSG/SEVIRI and CALIOP provided additional observations. In several occasions corresponding to aerosol loads of different types, the aircraft flew near EARLINET/ACTRIS (European Aerosol Research Lidar Network / Aerosols, Clouds, and Trace gases Research InfraStructure Network, http://www.actris.net/) lidar stations. This work is focused on a moderate multi-intrusion Saharan dust event occurred over the western Mediterranean Basin (WMB) during the period 14 - 27 June. The dust plumes were detected by the EARLINET stations of Granada, Barcelona, Naples, Potenza, Lecce and Serra la Nave (Sicily) and by the ChArMEx lidar stations of Menorca, Ersa and Lampedusa. The dust origin is chronologically identified from northern Morocco, center Algeria and center Tunisia. The multi-intrusion aspect of the event results in aerosol optical depth peaks higher in the eastern part of the WMB (maximum of 0.45 at 440 nm detected in Lecce) than in the western part of the WMB where the event starts (maximum of 0.29 at 440 nm detected in Granada). The spatio-temporal evolution of the plumes during their transport and the differences due to the different dust origins are investigated with multi-wavelength ground-based lidars, sun-photometers, the airborne lidar and balloon-borne aerosol counters. Acknowledgments: EARLINET lidar measurements are supported by the 7th Framework Programme under the project ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network; grant agreement no. 262254). The field campaign was performed in the framework of work package 4 on aerosol-radiation-climate interactions of the coordinated programme MISTRALS/ChArMEx) and was also supported by ANR.

InfoSec-MobCop - Framework for Theft Detection and Data Security on Mobile Computing Devices

NASA Astrophysics Data System (ADS)

Gupta, Anand; Gupta, Deepank; Gupta, Nidhi

People steal mobile devices with the intention of making money either by selling the mobile or by taking the sensitive information stored inside it. Mobile thefts are rising even with existing deterrents in place. This is because; they are ineffective, as they generate unnecessary alerts and might require expensive hardware equipments. In this paper a novel framework termed as InfoSec-MobCop is proposed which secures a mobile user’s data and discovers theft by detecting any anomaly in the user behavior. The anomaly of the user is computed by extracting and monitoring user specific details (typing pattern and usage history). The result of any intrusion attempt by a masquerader is intimated to the service provider through an SMS. Effectiveness of the used approach is discussed using FAR and FRR graphs. The experimental system uses both real users and simulated studies to quantify the effectiveness of the InfoSec-MobCop (Information Security Mobile Cop).

78 FR 12337 - Published Privacy Impact Assessments on the Web

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-22

... system for intrusion detection, analysis, intrusion prevention, and information sharing capabilities that... equivalent protection to participating Federal civilian agencies pending deployment of EINSTEIN intrusion...-008 Homeland Security Information Network R3 User Accounts (HSIN). Component: Operations Coordination...

A Protocol Layer Trust-Based Intrusion Detection Scheme for Wireless Sensor Networks

PubMed Central

Wang, Jian; Jiang, Shuai; Fapojuwo, Abraham O.

2017-01-01

This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different protocol layers will inevitably have impacts on the parameters of the corresponding protocol layers. For simplicity, the paper mainly considers three aspects of trustworthiness, namely physical layer trust, media access control layer trust and network layer trust. The per-layer trust metrics are then combined to determine the overall trust metric of a sensor node. The performance of the proposed intrusion detection mechanism is then analyzed using the t-distribution to derive analytical results of false positive and false negative probabilities. Numerical analytical results, validated by simulation results, are presented in different attack scenarios. It is shown that the proposed protocol layer trust-based intrusion detection scheme outperforms a state-of-the-art scheme in terms of detection probability and false probability, demonstrating its usefulness for detecting cross-layer attacks. PMID:28555023

A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks

PubMed Central

Ma, Tao; Wang, Fen; Cheng, Jianjun; Yu, Yang; Chen, Xiaoyun

2016-01-01

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks. PMID:27754380

A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks.

PubMed

Ma, Tao; Wang, Fen; Cheng, Jianjun; Yu, Yang; Chen, Xiaoyun

2016-10-13

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks.

A Protocol Layer Trust-Based Intrusion Detection Scheme for Wireless Sensor Networks.

PubMed

Wang, Jian; Jiang, Shuai; Fapojuwo, Abraham O

2017-05-27

This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different protocol layers will inevitably have impacts on the parameters of the corresponding protocol layers. For simplicity, the paper mainly considers three aspects of trustworthiness, namely physical layer trust, media access control layer trust and network layer trust. The per-layer trust metrics are then combined to determine the overall trust metric of a sensor node. The performance of the proposed intrusion detection mechanism is then analyzed using the t-distribution to derive analytical results of false positive and false negative probabilities. Numerical analytical results, validated by simulation results, are presented in different attack scenarios. It is shown that the proposed protocol layer trust-based intrusion detection scheme outperforms a state-of-the-art scheme in terms of detection probability and false probability, demonstrating its usefulness for detecting cross-layer attacks.

Industrial Control System Process-Oriented Intrusion Detection (iPoid) Algorithm

DTIC Science & Technology

2016-08-01

inspection rules using an intrusion-detection system (IDS) sensor, a simulated Programmable Logic Controller (PLC), and a Modbus client operating...operating system PLC Programmable Logic Controller SCADA supervisory control and data acquisition SIGHUP signal hangup SPAN Switched Port Analyzer

Design of an Evolutionary Approach for Intrusion Detection

PubMed Central

2013-01-01

A novel evolutionary approach is proposed for effective intrusion detection based on benchmark datasets. The proposed approach can generate a pool of noninferior individual solutions and ensemble solutions thereof. The generated ensembles can be used to detect the intrusions accurately. For intrusion detection problem, the proposed approach could consider conflicting objectives simultaneously like detection rate of each attack class, error rate, accuracy, diversity, and so forth. The proposed approach can generate a pool of noninferior solutions and ensembles thereof having optimized trade-offs values of multiple conflicting objectives. In this paper, a three-phase, approach is proposed to generate solutions to a simple chromosome design in the first phase. In the first phase, a Pareto front of noninferior individual solutions is approximated. In the second phase of the proposed approach, the entire solution set is further refined to determine effective ensemble solutions considering solution interaction. In this phase, another improved Pareto front of ensemble solutions over that of individual solutions is approximated. The ensemble solutions in improved Pareto front reported improved detection results based on benchmark datasets for intrusion detection. In the third phase, a combination method like majority voting method is used to fuse the predictions of individual solutions for determining prediction of ensemble solution. Benchmark datasets, namely, KDD cup 1999 and ISCX 2012 dataset, are used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover individual solutions and ensemble solutions thereof with a good support and a detection rate from benchmark datasets (in comparison with well-known ensemble methods like bagging and boosting). In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting objectives, and a dataset can be represented in the form of labelled instances in terms of its features. PMID:24376390

Intrusion Detection System Visualization of Network Alerts

DTIC Science & Technology

2010-07-01

Intrusion Detection System Visualization of Network Alerts Dolores M. Zage and Wayne M. Zage Ball State University Final Report July 2010...contracts. Staff Wayne Zage, Director of the S2ERC and Professor, Department of Computer Science, Ball State University Dolores Zage, Research

Network Anomaly Detection Based on Wavelet Analysis

NASA Astrophysics Data System (ADS)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

Detection of network attacks based on adaptive resonance theory

NASA Astrophysics Data System (ADS)

Bukhanov, D. G.; Polyakov, V. M.

2018-05-01

The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.

Non-intrusive methods of characterizing vehicles on the highway.

DOT National Transportation Integrated Search

2003-06-01

Over the past year we have worked on the development of a real-time laser-based non-intrusive field-deployable detection system for delineation of moving vehicles. The primary goal of the project is to develop a roadway detection system that can be u...

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features.

PubMed

Amudha, P; Karthik, S; Sivakumari, S

2015-01-01

Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

PubMed Central

Amudha, P.; Karthik, S.; Sivakumari, S.

2015-01-01

Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625

Intrusion detection using rough set classification.

PubMed

Zhang, Lian-hua; Zhang, Guan-hua; Zhang, Jie; Bai, Ying-cai

2004-09-01

Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of "IF-THEN" rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

A Comparative Study of Unsupervised Anomaly Detection Techniques Using Honeypot Data

NASA Astrophysics Data System (ADS)

Song, Jungsuk; Takakura, Hiroki; Okabe, Yasuo; Inoue, Daisuke; Eto, Masashi; Nakao, Koji

Intrusion Detection Systems (IDS) have been received considerable attention among the network security researchers as one of the most promising countermeasures to defend our crucial computer systems or networks against attackers on the Internet. Over the past few years, many machine learning techniques have been applied to IDSs so as to improve their performance and to construct them with low cost and effort. Especially, unsupervised anomaly detection techniques have a significant advantage in their capability to identify unforeseen attacks, i.e., 0-day attacks, and to build intrusion detection models without any labeled (i.e., pre-classified) training data in an automated manner. In this paper, we conduct a set of experiments to evaluate and analyze performance of the major unsupervised anomaly detection techniques using real traffic data which are obtained at our honeypots deployed inside and outside of the campus network of Kyoto University, and using various evaluation criteria, i.e., performance evaluation by similarity measurements and the size of training data, overall performance, detection ability for unknown attacks, and time complexity. Our experimental results give some practical and useful guidelines to IDS researchers and operators, so that they can acquire insight to apply these techniques to the area of intrusion detection, and devise more effective intrusion detection models.

An Adaptive Database Intrusion Detection System

ERIC Educational Resources Information Center

Barrios, Rita M.

2011-01-01

Intrusion detection is difficult to accomplish when attempting to employ current methodologies when considering the database and the authorized entity. It is a common understanding that current methodologies focus on the network architecture rather than the database, which is not an adequate solution when considering the insider threat. Recent…

Day, night and all-weather security surveillance automation synergy from combining two powerful technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morellas, Vassilios; Johnson, Andrew; Johnston, Chris

2006-07-01

Thermal imaging is rightfully a real-world technology proven to bring confidence to daytime, night-time and all weather security surveillance. Automatic image processing intrusion detection algorithms are also a real world technology proven to bring confidence to system surveillance security solutions. Together, day, night and all weather video imagery sensors and automated intrusion detection software systems create the real power to protect early against crime, providing real-time global homeland protection, rather than simply being able to monitor and record activities for post event analysis. These solutions, whether providing automatic security system surveillance at airports (to automatically detect unauthorized aircraft takeoff andmore » landing activities) or at high risk private, public or government facilities (to automatically detect unauthorized people or vehicle intrusion activities) are on the move to provide end users the power to protect people, capital equipment and intellectual property against acts of vandalism and terrorism. As with any technology, infrared sensors and automatic image intrusion detection systems for global homeland security protection have clear technological strengths and limitations compared to other more common day and night vision technologies or more traditional manual man-in-the-loop intrusion detection security systems. This paper addresses these strength and limitation capabilities. False Alarm (FAR) and False Positive Rate (FPR) is an example of some of the key customer system acceptability metrics and Noise Equivalent Temperature Difference (NETD) and Minimum Resolvable Temperature are examples of some of the sensor level performance acceptability metrics. (authors)« less

Alerts Visualization and Clustering in Network-based Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Dr. Li; Gasior, Wade C; Dasireddy, Swetha

2010-04-01

Today's Intrusion detection systems when deployed on a busy network overload the network with huge number of alerts. This behavior of producing too much raw information makes it less effective. We propose a system which takes both raw data and Snort alerts to visualize and analyze possible intrusions in a network. Then we present with two models for the visualization of clustered alerts. Our first model gives the network administrator with the logical topology of the network and detailed information of each node that involves its associated alerts and connections. In the second model, flocking model, presents the network administratormore » with the visual representation of IDS data in which each alert is represented in different color and the alerts with maximum similarity move together. This gives network administrator with the idea of detecting various of intrusions through visualizing the alert patterns.« less

Towards a Cyber Defense Framework for SCADA Systems Based on Power Consumption Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez Jimenez, Jarilyn M; Chen, Qian; Nichols, Jeff A.

Supervisory control and data acquisition (SCADA) is an industrial automation system that remotely monitor, and control critical infrastructures. SCADA systems are major targets for espionage and sabotage attackers. According to the 2015 Dell security annual threat report, the number of cyber-attacks against SCADA systems has doubled in the past year. Cyber-attacks (i.e., buffer overflow, rootkits and code injection) could cause serious financial losses and physical infrastructure damages. Moreover, some specific cyber-attacks against SCADA systems could become a threat to human life. Current commercial off-the-shelf security solutions are insufficient in protecting SCADA systems against sophisticated cyber-attacks. In 2014 a report bymore » Mandiant stated that only 69% of organizations learned about their breaches from third entities, meaning that these companies lack of their own detection system. Furthermore, these breaches are not detected in real-time or fast enough to prevent further damages. The average time between compromise and detection (for those intrusions that were detected) was 205 days. To address this challenge, we propose an Intrusion Detection System (IDS) that detects SCADA-specific cyber-attacks by analyzing the power consumption of a SCADA device. Specifically, to validate the proposed approach, we chose to monitor in real-time the power usage of a a Programmable Logic Controller (PLC). To this end, we configured the hardware of the tetsbed by installing the required sensors to monitor and collect its power consumption. After that two SCADA-specific cyber-attacks were simulated and TracerDAQ Pro was used to collect the power consumption of the PLC under normal and anomalous scenarios. Results showed that is possible to distinguish between the regular power usage of the PLC and when the PLC was under specific cyber-attacks.« less

76 FR 38089 - Defense Federal Acquisition Regulation Supplement; Safeguarding Unclassified DoD Information...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-29

... encryption of data for storage and transmission, network protection and intrusion detection, and cyber... review of its unclassified network for evidence of intrusion to include, but is not limited to... DoD information within industry, nor does it address cyber intrusion reporting for that information...

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

Intrusion Detection for Defense at the MAC and Routing Layers of Wireless Networks

DTIC Science & Technology

2007-01-01

Space DoS Denial of Service DSR Dynamic Source Routing IDS Intrusion Detection System LAR Location-Aided Routing MAC Media Access Control MACA Multiple...different mobility parameters. 10 They simulate interaction between three MAC protocols ( MACA , 802.11 and CSMA) and three routing protocols (AODV, DSR

On Modeling of Adversary Behavior and Defense for Survivability of Military MANET Applications

DTIC Science & Technology

2015-01-01

anomaly detection technique. b) A system-level majority-voting based intrusion detection system with m being the number of verifiers used to perform...pp. 1254 - 1263. [5] R. Mitchell, and I.R. Chen, “Adaptive Intrusion Detection for Unmanned Aircraft Systems based on Behavior Rule Specification...and adaptively trigger the best attack strategies while avoiding detection and eviction. The second step is to model defense behavior of defenders

Confabulation Based Real-time Anomaly Detection for Wide-area Surveillance Using Heterogeneous High Performance Computing Architecture

DTIC Science & Technology

2015-06-01

system accuracy. The AnRAD system was also generalized for the additional application of network intrusion detection . A self-structuring technique...to Host- based Intrusion Detection Systems using Contiguous and Discontiguous System Call Patterns,” IEEE Transactions on Computer, 63(4), pp. 807...square kilometer areas. The anomaly recognition and detection (AnRAD) system was built as a cogent confabulation network . It represented road

Virtual-Lattice Based Intrusion Detection Algorithm over Actuator-Assisted Underwater Wireless Sensor Networks

PubMed Central

Yan, Jing; Li, Xiaolei; Luo, Xiaoyuan; Guan, Xinping

2017-01-01

Due to the lack of a physical line of defense, intrusion detection becomes one of the key issues in applications of underwater wireless sensor networks (UWSNs), especially when the confidentiality has prime importance. However, the resource-constrained property of UWSNs such as sparse deployment and energy constraint makes intrusion detection a challenging issue. This paper considers a virtual-lattice-based approach to the intrusion detection problem in UWSNs. Different from most existing works, the UWSNs consist of two kinds of nodes, i.e., sensor nodes (SNs), which cannot move autonomously, and actuator nodes (ANs), which can move autonomously according to the performance requirement. With the cooperation of SNs and ANs, the intruder detection probability is defined. Then, a virtual lattice-based monitor (VLM) algorithm is proposed to detect the intruder. In order to reduce the redundancy of communication links and improve detection probability, an optimal and coordinative lattice-based monitor patrolling (OCLMP) algorithm is further provided for UWSNs, wherein an equal price search strategy is given for ANs to find the shortest patrolling path. Under VLM and OCLMP algorithms, the detection probabilities are calculated, while the topology connectivity can be guaranteed. Finally, simulation results are presented to show that the proposed method in this paper can improve the detection accuracy and save the energy consumption compared with the conventional methods. PMID:28531127

Detection and response to unauthorized access to a communication device

DOEpatents

Smith, Rhett; Gordon, Colin

2015-09-08

A communication gateway consistent with the present disclosure may detect unauthorized physical or electronic access and implement security actions in response thereto. A communication gateway may provide a communication path to an intelligent electronic device (IED) using an IED communications port configured to communicate with the IED. The communication gateway may include a physical intrusion detection port and a network port. The communication gateway may further include control logic configured to evaluate physical intrusion detection signal. The control logic may be configured to determine that the physical intrusion detection signal is indicative of an attempt to obtain unauthorized access to one of the communication gateway, the IED, and a device in communication with the gateway; and take a security action based upon the determination that the indication is indicative of the attempt to gain unauthorized access.

Visualization Techniques for Computer Network Defense

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beaver, Justin M; Steed, Chad A; Patton, Robert M

2011-01-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operatormore » to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.« less

A Security Monitoring Framework For Virtualization Based HEP Infrastructures

NASA Astrophysics Data System (ADS)

Gomez Ramirez, A.; Martinez Pedreira, M.; Grigoras, C.; Betev, L.; Lara, C.; Kebschull, U.; ALICE Collaboration

2017-10-01

High Energy Physics (HEP) distributed computing infrastructures require automatic tools to monitor, analyze and react to potential security incidents. These tools should collect and inspect data such as resource consumption, logs and sequence of system calls for detecting anomalies that indicate the presence of a malicious agent. They should also be able to perform automated reactions to attacks without administrator intervention. We describe a novel framework that accomplishes these requirements, with a proof of concept implementation for the ALICE experiment at CERN. We show how we achieve a fully virtualized environment that improves the security by isolating services and Jobs without a significant performance impact. We also describe a collected dataset for Machine Learning based Intrusion Prevention and Detection Systems on Grid computing. This dataset is composed of resource consumption measurements (such as CPU, RAM and network traffic), logfiles from operating system services, and system call data collected from production Jobs running in an ALICE Grid test site and a big set of malware samples. This malware set was collected from security research sites. Based on this dataset, we will proceed to develop Machine Learning algorithms able to detect malicious Jobs.

An Optimal Method for Detecting Internal and External Intrusion in MANET

NASA Astrophysics Data System (ADS)

Rafsanjani, Marjan Kuchaki; Aliahmadipour, Laya; Javidi, Mohammad M.

Mobile Ad hoc Network (MANET) is formed by a set of mobile hosts which communicate among themselves through radio waves. The hosts establish infrastructure and cooperate to forward data in a multi-hop fashion without a central administration. Due to their communication type and resources constraint, MANETs are vulnerable to diverse types of attacks and intrusions. In this paper, we proposed a method for prevention internal intruder and detection external intruder by using game theory in mobile ad hoc network. One optimal solution for reducing the resource consumption of detection external intruder is to elect a leader for each cluster to provide intrusion service to other nodes in the its cluster, we call this mode moderate mode. Moderate mode is only suitable when the probability of attack is low. Once the probability of attack is high, victim nodes should launch their own IDS to detect and thwart intrusions and we call robust mode. In this paper leader should not be malicious or selfish node and must detect external intrusion in its cluster with minimum cost. Our proposed method has three steps: the first step building trust relationship between nodes and estimation trust value for each node to prevent internal intrusion. In the second step we propose an optimal method for leader election by using trust value; and in the third step, finding the threshold value for notifying the victim node to launch its IDS once the probability of attack exceeds that value. In first and third step we apply Bayesian game theory. Our method due to using game theory, trust value and honest leader can effectively improve the network security, performance and reduce resource consumption.

Reactive and multiphase modelling for the identification of monitoring parameters to detect CO2 intrusion into freshwater aquifers

NASA Astrophysics Data System (ADS)

Fahrner, S.; Schaefer, D.; Wiegers, C.; Köber, R.; Dahmke, A.

2011-12-01

A monitoring at geological CO2 storage sites has to meet environmental, regulative, financial and public demands and thus has to enable the detection of CO2 leakages. Current monitoring concepts for the detection of CO2 intrusion into freshwater aquifers located above saline storage formations in course of leakage events lack the identification of monitoring parameters. Their response to CO2 intrusion still has to be enlightened. Scenario simulations of CO2 intrusion in virtual synthetic aquifers are performed using the simulators PhreeqC and TOUGH2 to reveal relevant CO2-water-mineral interactions and multiphase behaviour on potential monitoring parameters. The focus is set on pH, total dissolved inorganic carbon (TIC) and the hydroelectric conductivity (EC). The study aims at identifying at which conditions the parameters react rapidly, durable and in a measurable degree. The depth of the aquifer, the mineralogy, the intrusion rates, the sorption specification and capacities, and groundwater flow velocities are varied in the course of the scenario modelling. All three parameters have been found suited in most scenarios. However, in case of a lack of calcite combined with low saturation of the water with respect to CO2 and shallow conditions, changes are close to the measurement resolution. Predicted changes in EC result from the interplay between carbonic acid production and its dissociation, and pH buffering by mineral dissolution. The formation of a discrete gas phase in cases of full saturation of the groundwater in confined aquifers illustrates the potential bipartite resistivity response: An increased hydroelectric conductivity at locations with dissolved CO2, and a high resistivity where the gas phase dominates the pore volume occupation. Increased hydrostatic pressure with depth and enhanced groundwater flow velocities enforce gas dissolution and diminish the formation of a discrete gas phase. Based on the results, a monitoring strategy is proposed which combines electromagnetic surface and in-situ geochemical measurements: The changes in formation resistivity / hydroelectric conductivity could be used as "first-level" parameter to identify potential intrusion locations. Subsequent targeted drilling and probe measurements of pH and TIC could be used to reject or confirm an intrusion event. Further sampling and analysis can be performed at this stage for the impact assessment if required. Next to considering regulative, environmental and public aspects, the approach helps to reduce financial strains by significantly lowering the number of required monitoring wells. This study is funded by the German Federal Ministry of Education and Research (BMBF), EnBW Energie Baden-Württemberg AG, E.ON Energie AG, E.ON Gas Storage AG, RWE Dea AG, Vattenfall Europe Technology Research GmbH, Wintershall Holding AG and Stadtwerke Kiel AG as part of the CO2-MoPa joint project in the framework of the Special Programme GEOTECHNOLOGIEN. Further funding occurred via CLEAN, which is part of the geoscientific research and development programme GEOTECHNOLOGIEN and is funded by the German Federal Ministry for Education and Research (BMBF).

Unsupervised active learning based on hierarchical graph-theoretic clustering.

PubMed

Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

2009-10-01

Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

PubMed Central

Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

2013-01-01

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu–Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors. PMID:23529146

A distributed signature detection method for detecting intrusions in sensor systems.

PubMed

Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

2013-03-25

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu-Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors.

Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection.

PubMed

Al-Jarrah, Omar Y; Alhussein, Omar; Yoo, Paul D; Muhaidat, Sami; Taha, Kamal; Kim, Kwangjo

2016-08-01

Botnets, which consist of remotely controlled compromised machines called bots, provide a distributed platform for several threats against cyber world entities and enterprises. Intrusion detection system (IDS) provides an efficient countermeasure against botnets. It continually monitors and analyzes network traffic for potential vulnerabilities and possible existence of active attacks. A payload-inspection-based IDS (PI-IDS) identifies active intrusion attempts by inspecting transmission control protocol and user datagram protocol packet's payload and comparing it with previously seen attacks signatures. However, the PI-IDS abilities to detect intrusions might be incapacitated by packet encryption. Traffic-based IDS (T-IDS) alleviates the shortcomings of PI-IDS, as it does not inspect packet payload; however, it analyzes packet header to identify intrusions. As the network's traffic grows rapidly, not only the detection-rate is critical, but also the efficiency and the scalability of IDS become more significant. In this paper, we propose a state-of-the-art T-IDS built on a novel randomized data partitioned learning model (RDPLM), relying on a compact network feature set and feature selection techniques, simplified subspacing and a multiple randomized meta-learning technique. The proposed model has achieved 99.984% accuracy and 21.38 s training time on a well-known benchmark botnet dataset. Experiment results demonstrate that the proposed methodology outperforms other well-known machine-learning models used in the same detection task, namely, sequential minimal optimization, deep neural network, C4.5, reduced error pruning tree, and randomTree.

Detection of Dry Intrusion on Water Vapor Images Over Central Europe - June 2010 TO September 2011

NASA Astrophysics Data System (ADS)

Novotny, J.; Dejmal, K.; Hudec, F.; Kolar, P.

2016-06-01

The knowledge of evaluation of the intensity of cyclogenesis which could be connected with the weather having a significant impact on Earth's surface is quite useful. If, as one of the basic assumptions, the existence of connection between dry intrusions, dry bands, tropopause height and warm dark areas distribution on water vapor images (WV images) is considered, it is possible to set up a method of detecting dry intrusions on searching and tracking areas with higher brightness temperature compared with the surrounding environment. This paper covers the period between June 2010 and September 2011 over Central Europe. The ISIS method (Instrument de Suivi dans I'Imagerie satellitaire), originally developed for detection of cold cloud tops, was used as an initial ideological point. Subsequently, this method was modified by Michel and Bouttier for usage on WV images. Some of the applied criteria and parameters were chosen with reference to the results published by Michel and Bouttier as well as by Novotny. The procedure can be divided into two steps: detection of warm areas and their tracking. Cases of detection of areas not evidently connected with dry intrusions can be solved by filtering off based on the connection between detected warm areas to the cyclonic side of jet streams and significant lowering of the tropopause.

Neural Network Based Intrusion Detection System for Critical Infrastructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Todd Vollmer; Ondrej Linda; Milos Manic

2009-07-01

Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recordedmore » from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.« less

Tackling the x-ray cargo inspection challenge using machine learning

NASA Astrophysics Data System (ADS)

Jaccard, Nicolas; Rogers, Thomas W.; Morton, Edward J.; Griffin, Lewis D.

2016-05-01

The current infrastructure for non-intrusive inspection of cargo containers cannot accommodate exploding com-merce volumes and increasingly stringent regulations. There is a pressing need to develop methods to automate parts of the inspection workflow, enabling expert operators to focus on a manageable number of high-risk images. To tackle this challenge, we developed a modular framework for automated X-ray cargo image inspection. Employing state-of-the-art machine learning approaches, including deep learning, we demonstrate high performance for empty container verification and specific threat detection. This work constitutes a significant step towards the partial automation of X-ray cargo image inspection.

Nuclear and radiological Security: Introduction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, James Christopher

Nuclear security includes the prevention and detection of, and response to, theft, sabotage, unauthorized access, illegal transfer, or other malicious acts involving nuclear or other radioactive substances or their associated facilities. The presentation begins by discussing the concept and its importance, then moves on to consider threats--insider threat, sabotage, diversion of materials--with considerable emphasis on the former. The intrusion at Pelindaba, South Africa, is described as a case study. The distinction between nuclear security and security of radiological and portable sources is clarified, and the international legal framework is touched upon. The paper concludes by discussing the responsibilities of themore » various entities involved in nuclear security.« less

Vapor Intrusion Estimation Tool for Unsaturated Zone Contaminant Sources. User’s Guide

DTIC Science & Technology

2016-08-30

324449 Page Intentionally Left Blank iii Executive Summary Soil vapor extraction (SVE) is a prevalent remediation approach for volatile contaminants...strength and location, vadose zone transport, and a model for estimating movement of soil -gas vapor contamination into buildings. The tool may be...framework for estimating the impact of a vadose zone contaminant source on soil gas concentrations and vapor intrusion into a building

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.

2001-09-01

This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerablemore » preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.« less

Formal Methods for Information Protection Technology. Task 2: Mathematical Foundations, Architecture and Principles of Implementation of Multi-Agent Learning Components for Attack Detection in Computer Networks. Part 2

DTIC Science & Technology

2003-11-01

Lafayette, IN 47907. [Lane et al-97b] T. Lane and C . E. Brodley. Sequence matching and learning in anomaly detection for computer security. Proceedings of...Mining, pp 259-263. 1998. [Lane et al-98b] T. Lane and C . E. Brodley. Temporal sequence learning and data reduction for anomaly detection ...W. Lee, C . Park, and S. Stolfo. Towards Automatic Intrusion Detection using NFR. 1st USENIX Workshop on Intrusion Detection and Network Monitoring

In-situ trainable intrusion detection system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob

A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such thatmore » the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.« less

An artificial bioindicator system for network intrusion detection.

PubMed

Blum, Christian; Lozano, José A; Davidson, Pedro Pinacho

An artificial bioindicator system is developed in order to solve a network intrusion detection problem. The system, inspired by an ecological approach to biological immune systems, evolves a population of agents that learn to survive in their environment. An adaptation process allows the transformation of the agent population into a bioindicator that is capable of reacting to system anomalies. Two characteristics stand out in our proposal. On the one hand, it is able to discover new, previously unseen attacks, and on the other hand, contrary to most of the existing systems for network intrusion detection, it does not need any previous training. We experimentally compare our proposal with three state-of-the-art algorithms and show that it outperforms the competing approaches on widely used benchmark data.

A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

PubMed Central

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing. PMID:22919273

A survey and proposed framework on the soft biometrics technique for human identification in intelligent video surveillance system.

PubMed

Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

2012-01-01

Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.

A Database of Computer Attacks for the Evaluation of Intrusion Detection Systems

DTIC Science & Technology

1999-06-01

administrator whenever a system binary file (such as the ps, login , or ls program) is modified. Normal users have no legitimate reason to alter these files...development of EMERALD [46], which combines statistical anomaly detection from NIDES with signature verification. Specification-based intrusion detection...the creation of a single host that can act as many hosts. Daemons that provide network services—including telnetd, ftpd, and login — display banners

Attacks and Countermeasures in Communications and Power Networks

DTIC Science & Technology

2014-01-01

the victim. This strategy is often used to confuse the intrusion detection system about the adversary’s location. If the adversary compromises a pair...1.2 Detection of Information Flows Detection of information flows between a pair of nodes has been studied in the context of network intrusion ...Theo- rem 3.3.4 were derived purely based on the condition for undetectability. Hence, the same optimality statements hold for the noisy measurement

Smart container UWB sensor system for situational awareness of intrusion alarms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romero, Carlos E.; Haugen, Peter C.; Zumstein, James M.

An in-container monitoring sensor system is based on an UWB radar intrusion detector positioned in a container and having a range gate set to the farthest wall of the container from the detector. Multipath reflections within the container make every point on or in the container appear to be at the range gate, allowing intrusion detection anywhere in the container. The system also includes other sensors to provide false alarm discrimination, and may include other sensors to monitor other parameters, e.g. radiation. The sensor system also includes a control subsystem for controlling system operation. Communications and information extraction capability maymore » also be included. A method of detecting intrusion into a container uses UWB radar, and may also include false alarm discrimination. A secure container has an UWB based monitoring system« less

Repeated magmatic intrusions at El Hierro Island following the 2011-2012 submarine eruption

NASA Astrophysics Data System (ADS)

Benito-Saz, Maria A.; Parks, Michelle M.; Sigmundsson, Freysteinn; Hooper, Andrew; García-Cañada, Laura

2017-09-01

After more than 200 years of quiescence, in July 2011 an intense seismic swarm was detected beneath the center of El Hierro Island (Canary Islands), culminating on 10 October 2011 in a submarine eruption, 2 km off the southern coast. Although the eruption officially ended on 5 March 2012, magmatic activity continued in the area. From June 2012 to March 2014, six earthquake swarms, indicative of magmatic intrusions, were detected underneath the island. We have studied these post-eruption intrusive events using GPS and InSAR techniques to characterize the ground surface deformation produced by each of these intrusions, and to determine the optimal source parameters (geometry, location, depth, volume change). Source inversions provide insight into the depth of the intrusions ( 11-16 km) and the volume change associated with each of them (between 0.02 and 0.13 km3). During this period, > 20 cm of uplift was detected in the central-western part of the island, corresponding to approximately 0.32-0.38 km3 of magma intruded beneath the volcano. We suggest that these intrusions result from deep magma migrating from the mantle, trapped at the mantle/lower crust discontinuity in the form of sill-like bodies. This study, using joint inversion of GPS and InSAR data in a post-eruption period, provides important insight into the characteristics of the magmatic plumbing system of El Hierro, an oceanic intraplate volcanic island.

49 CFR Appendix A to Part 209 - Statement of Agency Policy Concerning Enforcement of the Federal Railroad Safety Laws

Code of Federal Regulations, 2013 CFR

2013-10-01

... exercise of jurisdiction. In this context, the presence of intrusion detection devices to alert one or both... about sufficient intrusion detection and related safety measures designed to avoid a collision between...). By “general railroad system of transportation,” FRA refers to the network of standard gage track over...

49 CFR Appendix A to Part 209 - Statement of Agency Policy Concerning Enforcement of the Federal Railroad Safety Laws

Code of Federal Regulations, 2014 CFR

2014-10-01

... exercise of jurisdiction. In this context, the presence of intrusion detection devices to alert one or both... about sufficient intrusion detection and related safety measures designed to avoid a collision between...). By “general railroad system of transportation,” FRA refers to the network of standard gage track over...

49 CFR Appendix A to Part 209 - Statement of Agency Policy Concerning Enforcement of the Federal Railroad Safety Laws

Code of Federal Regulations, 2012 CFR

2012-10-01

... exercise of jurisdiction. In this context, the presence of intrusion detection devices to alert one or both... about sufficient intrusion detection and related safety measures designed to avoid a collision between...). By “general railroad system of transportation,” FRA refers to the network of standard gage track over...

VMSoar: a cognitive agent for network security

NASA Astrophysics Data System (ADS)

Benjamin, David P.; Shankar-Iyer, Ranjita; Perumal, Archana

2005-03-01

VMSoar is a cognitive network security agent designed for both network configuration and long-term security management. It performs automatic vulnerability assessments by exploring a configuration"s weaknesses and also performs network intrusion detection. VMSoar is built on the Soar cognitive architecture, and benefits from the general cognitive abilities of Soar, including learning from experience, the ability to solve a wide range of complex problems, and use of natural language to interact with humans. The approach used by VMSoar is very different from that taken by other vulnerability assessment or intrusion detection systems. VMSoar performs vulnerability assessments by using VMWare to create a virtual copy of the target machine then attacking the simulated machine with a wide assortment of exploits. VMSoar uses this same ability to perform intrusion detection. When trying to understand a sequence of network packets, VMSoar uses VMWare to make a virtual copy of the local portion of the network and then attempts to generate the observed packets on the simulated network by performing various exploits. This approach is initially slow, but VMSoar"s learning ability significantly speeds up both vulnerability assessment and intrusion detection. This paper describes the design and implementation of VMSoar, and initial experiments with Windows NT and XP.

Using Unix system auditing for detecting network intrusions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christensen, M.J.

1993-03-01

Intrusion Detection Systems (IDSs) are designed to detect actions of individuals who use computer resources without authorization as well as legitimate users who exceed their privileges. This paper describes a novel approach to IDS research, namely a decision aiding approach to intrusion detection. The introduction of a decision tree represents the logical steps necessary to distinguish and identify different types of attacks. This tool, the Intrusion Decision Aiding Tool (IDAT), utilizes IDS-based attack models and standard Unix audit data. Since attacks have certain characteristics and are based on already developed signature attack models, experienced and knowledgeable Unix system administrators knowmore » what to look for in system audit logs to determine if a system has been attacked. Others, however, are usually less able to recognize common signatures of unauthorized access. Users can traverse the tree using available audit data displayed by IDAT and general knowledge they possess to reach a conclusion regarding suspicious activity. IDAT is an easy-to-use window based application that gathers, analyzes, and displays pertinent system data according to Unix attack characteristics. IDAT offers a more practical approach and allows the user to make an informed decision regarding suspicious activity.« less

An exact computational method for performance analysis of sequential test algorithms for detecting network intrusions

NASA Astrophysics Data System (ADS)

Chen, Xinjia; Lacy, Fred; Carriere, Patrick

2015-05-01

Sequential test algorithms are playing increasingly important roles for quick detecting network intrusions such as portscanners. In view of the fact that such algorithms are usually analyzed based on intuitive approximation or asymptotic analysis, we develop an exact computational method for the performance analysis of such algorithms. Our method can be used to calculate the probability of false alarm and average detection time up to arbitrarily pre-specified accuracy.

Integrity Verification for SCADA Devices Using Bloom Filters and Deep Packet Inspection

DTIC Science & Technology

2014-03-27

prevent intrusions in smart grids [PK12]. Parthasarathy proposed an anomaly detection based IDS that takes into account system state. In his implementation...Security, 25(7):498–506, 10 2006. [LMV12] O. Linda, M. Manic, and T. Vollmer. Improving cyber-security of smart grid systems via anomaly detection and...6 2012. 114 [PK12] S. Parthasarathy and D. Kundur. Bloom filter based intrusion detection for smart grid SCADA. In Electrical & Computer Engineering

Modeling and Analyzing Intrusion Attempts to a Computer Network Operating in a Defense in Depth Posture

DTIC Science & Technology

2004-09-01

protection. Firewalls, Intrusion Detection Systems (IDS’s), Anti-Virus (AV) software , and routers are such tools used. In recent years, computer security...associated with operating systems, application software , and computing hardware. When IDS’s are utilized on a host computer or network, there are two...primary approaches to detecting and / or preventing attacks. Traditional IDS’s, like most AV software , rely on known “signatures” to detect attacks

Pulsed thermography detection of water and hydraulic oil intrusion in the honeycomb sandwich structure composite

NASA Astrophysics Data System (ADS)

Zhao, Shi-bin; Zhang, Cun-lin; Wu, Nai-ming

2011-08-01

Water and hydraulic oil intrusion inside honeycomb sandwich Structure Composite during service has been linked to in-flight failure in some aircraft. There is an ongoing effort to develop nondestructive testing methods to detect the presence of water and hydraulic oil within the sandwich panels. Pulsed thermography(PT) represents an attractive approach in that it is sensitive to the change of thermal properties. Using a flash lamp PT, testing can be applied directly to the surface of the panel. The viability of PT is demonstrated through laboratory imaging of both water and hydraulic oil within sandwich panels. The detection of water and hydraulic oil intrusion using a one-sided flash lamp PT is presented. It is shown that simple detection, as well as spatial localization of water and hydraulic oil within sandwich panels, and assign the quantity of water and hydraulic oil is possible.

State-Based Network Intrusion Detection Systems for SCADA Protocols: A Proof of Concept

NASA Astrophysics Data System (ADS)

Carcano, Andrea; Fovino, Igor Nai; Masera, Marcelo; Trombetta, Alberto

We present a novel Intrusion Detection System able to detect complex attacks to SCADA systems. By complex attack, we mean a set of commands (carried in Modbus packets) that, while licit when considered in isolation on a single-packet basis, interfere with the correct behavior of the system. The proposed IDS detects such attacks thanks to an internal representation of the controlled SCADA system and a corresponding rule language, powerful enough to express the system's critical states. Furthermore, we detail the implementation and provide experimental comparative results.

A Protocol Specification-Based Intrusion Detection System for VoIP and Its Evaluation

NASA Astrophysics Data System (ADS)

Phit, Thyda; Abe, Kôki

We propose an architecture of Intrusion Detection System (IDS) for VoIP using a protocol specification-based detection method to monitor the network traffics and alert administrator for further analysis of and response to suspicious activities. The protocol behaviors and their interactions are described by state machines. Traffic that behaves differently from the standard specifications are considered to be suspicious. The IDS has been implemented and simulated using OPNET Modeler, and verified to detect attacks. It was found that our system can detect typical attacks within a reasonable amount of delay time.

Identifying seawater intrusion in coastal areas by means of 1D and quasi-2D joint inversion of TDEM and VES data

NASA Astrophysics Data System (ADS)

Martínez-Moreno, F. J.; Monteiro-Santos, F. A.; Bernardo, I.; Farzamian, M.; Nascimento, C.; Fernandes, J.; Casal, B.; Ribeiro, J. A.

2017-09-01

Seawater intrusion is an increasingly widespread problem in coastal aquifers caused by climate changes -sea-level rise, extreme phenomena like flooding and droughts- and groundwater depletion near to the coastline. To evaluate and mitigate the environmental risks of this phenomenon it is necessary to characterize the coastal aquifer and the salt intrusion. Geophysical methods are the most appropriate tool to address these researches. Among all geophysical techniques, electrical methods are able to detect seawater intrusions due to the high resistivity contrast between saltwater, freshwater and geological layers. The combination of two or more geophysical methods is recommended and they are more efficient when both data are inverted jointly because the final model encompasses the physical properties measured for each methods. In this investigation, joint inversion of vertical electric and time domain soundings has been performed to examine seawater intrusion in an area within the Ferragudo-Albufeira aquifer system (Algarve, South of Portugal). For this purpose two profiles combining electrical resistivity tomography (ERT) and time domain electromagnetic (TDEM) methods were measured and the results were compared with the information obtained from exploration drilling. Three different inversions have been carried out: single inversion of the ERT and TDEM data, 1D joint inversion and quasi-2D joint inversion. Single inversion results identify seawater intrusion, although the sedimentary layers detected in exploration drilling were not well differentiated. The models obtained with 1D joint inversion improve the previous inversion due to better detection of sedimentary layer and the seawater intrusion appear to be better defined. Finally, the quasi-2D joint inversion reveals a more realistic shape of the seawater intrusion and it is able to distinguish more sedimentary layers recognised in the exploration drilling. This study demonstrates that the quasi-2D joint inversion improves the previous inversions methods making it a powerful tool applicable to different research areas.

Ultra-long high-sensitivity Φ-OTDR for high spatial resolution intrusion detection of pipelines.

PubMed

Peng, Fei; Wu, Han; Jia, Xin-Hong; Rao, Yun-Jiang; Wang, Zi-Nan; Peng, Zheng-Pu

2014-06-02

An ultra-long phase-sensitive optical time domain reflectometry (Φ-OTDR) that can achieve high-sensitivity intrusion detection over 131.5km fiber with high spatial resolution of 8m is presented, which is the longest Φ-OTDR reported to date, to the best of our knowledge. It is found that the combination of distributed Raman amplification with heterodyne detection can extend the sensing distance and enhances the sensitivity substantially, leading to the realization of ultra-long Φ-OTDR with high sensitivity and spatial resolution. Furthermore, the feasibility of applying such an ultra-long Φ-OTDR to pipeline security monitoring is demonstrated and the features of intrusion signal can be extracted with improved SNR by using the wavelet detrending/denoising method proposed.

Use of behavioral biometrics in intrusion detection and online gaming

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2006-04-01

Behavior based intrusion detection is a frequently used approach for insuring network security. We expend behavior based intrusion detection approach to a new domain of game networks. Specifically, our research shows that a unique behavioral biometric can be generated based on the strategy used by an individual to play a game. We wrote software capable of automatically extracting behavioral profiles for each player in a game of Poker. Once a behavioral signature is generated for a player, it is continuously compared against player's current actions. Any significant deviations in behavior are reported to the game server administrator as potential security breaches. Our algorithm addresses a well-known problem of user verification and can be re-applied to the fields beyond game networks, such as operating systems and non-game networks security.

A Learning System for Discriminating Variants of Malicious Network Traffic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beaver, Justin M; Symons, Christopher T; Gillen, Rob

Modern computer network defense systems rely primarily on signature-based intrusion detection tools, which generate alerts when patterns that are pre-determined to be malicious are encountered in network data streams. Signatures are created reactively, and only after in-depth manual analysis of a network intrusion. There is little ability for signature-based detectors to identify intrusions that are new or even variants of an existing attack, and little ability to adapt the detectors to the patterns unique to a network environment. Due to these limitations, the need exists for network intrusion detection techniques that can more comprehensively address both known unknown networkbased attacksmore » and can be optimized for the target environment. This work describes a system that leverages machine learning to provide a network intrusion detection capability that analyzes behaviors in channels of communication between individual computers. Using examples of malicious and non-malicious traffic in the target environment, the system can be trained to discriminate between traffic types. The machine learning provides insight that would be difficult for a human to explicitly code as a signature because it evaluates many interdependent metrics simultaneously. With this approach, zero day detection is possible by focusing on similarity to known traffic types rather than mining for specific bit patterns or conditions. This also reduces the burden on organizations to account for all possible attack variant combinations through signatures. The approach is presented along with results from a third-party evaluation of its performance.« less

Perimeter intrusion detection and assessment system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eaton, M.J.; Jacobs, J.; McGovern, D.E.

1977-01-01

The key elements of the system considered at a materials storage site are intrusion sensors, alarm assessment, and system control and display. Three papers discussing each of these topics are compiled. They are abstracted individually. (JSR)

A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Sainani, Varsha

The increasing number of network security related incidents have made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). IDSs are expected to analyze a large volume of data while not placing a significantly added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel data mining assisted multiagent-based intrusion detection system (DMAS-IDS) is proposed, particularly with the support of multiclass supervised classification. These agents can detect and take predefined actions against malicious activities, and data mining techniques can help detect them. Our proposed DMAS-IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDS with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on multiagent platform along with a supervised classification technique.

Low Cost Efficient Deliverying Video Surveillance Service to Moving Guard for Smart Home.

PubMed

Gualotuña, Tatiana; Macías, Elsa; Suárez, Álvaro; C, Efraín R Fonseca; Rivadeneira, Andrés

2018-03-01

Low-cost video surveillance systems are attractive for Smart Home applications (especially in emerging economies). Those systems use the flexibility of the Internet of Things to operate the video camera only when an intrusion is detected. We are the only ones that focus on the design of protocols based on intelligent agents to communicate the video of an intrusion in real time to the guards by wireless or mobile networks. The goal is to communicate, in real time, the video to the guards who can be moving towards the smart home. However, this communication suffers from sporadic disruptions that difficults the control and drastically reduces user satisfaction and operativity of the system. In a novel way, we have designed a generic software architecture based on design patterns that can be adapted to any hardware in a simple way. The implanted hardware is of very low economic cost; the software frameworks are free. In the experimental tests we have shown that it is possible to communicate to the moving guard, intrusion notifications (by e-mail and by instant messaging), and the first video frames in less than 20 s. In addition, we automatically recovered the frames of video lost in the disruptions in a transparent way to the user, we supported vertical handover processes and we could save energy of the smartphone's battery. However, the most important thing was that the high satisfaction of the people who have used the system.

Low Cost Efficient Deliverying Video Surveillance Service to Moving Guard for Smart Home

PubMed Central

Gualotuña, Tatiana; Fonseca C., Efraín R.; Rivadeneira, Andrés

2018-01-01

Low-cost video surveillance systems are attractive for Smart Home applications (especially in emerging economies). Those systems use the flexibility of the Internet of Things to operate the video camera only when an intrusion is detected. We are the only ones that focus on the design of protocols based on intelligent agents to communicate the video of an intrusion in real time to the guards by wireless or mobile networks. The goal is to communicate, in real time, the video to the guards who can be moving towards the smart home. However, this communication suffers from sporadic disruptions that difficults the control and drastically reduces user satisfaction and operativity of the system. In a novel way, we have designed a generic software architecture based on design patterns that can be adapted to any hardware in a simple way. The implanted hardware is of very low economic cost; the software frameworks are free. In the experimental tests we have shown that it is possible to communicate to the moving guard, intrusion notifications (by e-mail and by instant messaging), and the first video frames in less than 20 s. In addition, we automatically recovered the frames of video lost in the disruptions in a transparent way to the user, we supported vertical handover processes and we could save energy of the smartphone's battery. However, the most important thing was that the high satisfaction of the people who have used the system. PMID:29494551

Independent component analysis (ICA) and self-organizing map (SOM) approach to multidetection system for network intruders

NASA Astrophysics Data System (ADS)

Abdi, Abdi M.; Szu, Harold H.

2003-04-01

With the growing rate of interconnection among computer systems, network security is becoming a real challenge. Intrusion Detection System (IDS) is designed to protect the availability, confidentiality and integrity of critical network information systems. Today"s approach to network intrusion detection involves the use of rule-based expert systems to identify an indication of known attack or anomalies. However, these techniques are less successful in identifying today"s attacks. Hackers are perpetually inventing new and previously unanticipated techniques to compromise information infrastructure. This paper proposes a dynamic way of detecting network intruders on time serious data. The proposed approach consists of a two-step process. Firstly, obtaining an efficient multi-user detection method, employing the recently introduced complexity minimization approach as a generalization of a standard ICA. Secondly, we identified unsupervised learning neural network architecture based on Kohonen"s Self-Organizing Map for potential functional clustering. These two steps working together adaptively will provide a pseudo-real time novelty detection attribute to supplement the current intrusion detection statistical methodology.

Performance Assessment of Network Intrusion-Alert Prediction

DTIC Science & Technology

2012-09-01

the threats. In this thesis, we use Snort to generate the intrusion detection alerts. 2. SNORT Snort is an open source network intrusion...standard for IPS. (Snort, 2012) We choose Snort because it is an open source product that is free to download and can be deployed cross-platform...Learning & prediction in relational time series: A survey. 21st Behavior Representation in Modeling & Simulation ( BRIMS ) Conference 2012, 93–100. Tan

Cybersecurity Intrusion Detection and Monitoring for Field Area Network: Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pietrowicz, Stanley

This report summarizes the key technical accomplishments, industry impact and performance of the I2-CEDS grant entitled “Cybersecurity Intrusion Detection and Monitoring for Field Area Network”. Led by Applied Communication Sciences (ACS/Vencore Labs) in conjunction with its utility partner Sacramento Municipal Utility District (SMUD), the project accelerated research on a first-of-its-kind cybersecurity monitoring solution for Advanced Meter Infrastructure and Distribution Automation field networks. It advanced the technology to a validated, full-scale solution that detects anomalies, intrusion events and improves utility situational awareness and visibility. The solution was successfully transitioned and commercialized for production use as SecureSmart™ Continuous Monitoring. Discoveries made withmore » SecureSmart™ Continuous Monitoring led to tangible and demonstrable improvements in the security posture of the US national electric infrastructure.« less

Scanning seismic intrusion detection method and apparatus. [monitoring unwanted subterranean entry and departure

NASA Technical Reports Server (NTRS)

Lee, R. D. (Inventor)

1983-01-01

An intrusion monitoring system includes an array of seismic sensors, such as geophones, arranged along a perimeter to be monitored for unauthorized intrusion as by surface movement or tunneling. Two wires lead from each sensor to a central monitoring station. The central monitoring station has three modes of operation. In a first mode of operation, the output of all of the seismic sensors is summed into a receiver for amplification and detection. When the amplitude of the summed signals exceeds a certain predetermined threshold value an alarm is sounded. In a second mode of operation, the individual output signals from the sensors are multiplexed into the receiver for sequentially interrogating each of the sensors.

Demonstration of Advanced EMI Models for Live-Site UXO Discrimination at Waikoloa, Hawaii

DTIC Science & Technology

2015-12-01

magnetic source models PNN Probabilistic Neural Network SERDP Strategic Environmental Research and Development Program SLO San Luis Obispo...SNR Signal to noise ratio SVM Support vector machine TD Time Domain TEMTADS Time Domain Electromagnetic Towed Array Detection System TOI... intrusive procedure, which was used by Parsons at WMA, failed to document accurately all intrusive results, or failed to detect and clear all UXO like

Embedded security system for multi-modal surveillance in a railway carriage

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Audigier, Romaric; Ambellouis, Sébastien; Capman, François; Benhadda, Hamid; Joudrier, Stéphanie; Sodoyer, David; Lamarque, Thierry

2015-10-01

Public transport security is one of the main priorities of the public authorities when fighting against crime and terrorism. In this context, there is a great demand for autonomous systems able to detect abnormal events such as violent acts aboard passenger cars and intrusions when the train is parked at the depot. To this end, we present an innovative approach which aims at providing efficient automatic event detection by fusing video and audio analytics and reducing the false alarm rate compared to classical stand-alone video detection. The multi-modal system is composed of two microphones and one camera and integrates onboard video and audio analytics and fusion capabilities. On the one hand, for detecting intrusion, the system relies on the fusion of "unusual" audio events detection with intrusion detections from video processing. The audio analysis consists in modeling the normal ambience and detecting deviation from the trained models during testing. This unsupervised approach is based on clustering of automatically extracted segments of acoustic features and statistical Gaussian Mixture Model (GMM) modeling of each cluster. The intrusion detection is based on the three-dimensional (3D) detection and tracking of individuals in the videos. On the other hand, for violent events detection, the system fuses unsupervised and supervised audio algorithms with video event detection. The supervised audio technique detects specific events such as shouts. A GMM is used to catch the formant structure of a shout signal. Video analytics use an original approach for detecting aggressive motion by focusing on erratic motion patterns specific to violent events. As data with violent events is not easily available, a normality model with structured motions from non-violent videos is learned for one-class classification. A fusion algorithm based on Dempster-Shafer's theory analyses the asynchronous detection outputs and computes the degree of belief of each probable event.

On-line detection of Escherichia coli intrusion in a pilot-scale drinking water distribution system.

PubMed

Ikonen, Jenni; Pitkänen, Tarja; Kosse, Pascal; Ciszek, Robert; Kolehmainen, Mikko; Miettinen, Ilkka T

2017-08-01

Improvements in microbial drinking water quality monitoring are needed for the better control of drinking water distribution systems and for public health protection. Conventional water quality monitoring programmes are not always able to detect a microbial contamination of drinking water. In the drinking water production chain, in addition to the vulnerability of source waters, the distribution networks are prone to contamination. In this study, a pilot-scale drinking-water distribution network with an on-line monitoring system was utilized for detecting bacterial intrusion. During the experimental Escherichia coli intrusions, the contaminant was measured by applying a set of on-line sensors for electric conductivity (EC), pH, temperature (T), turbidity, UV-absorbance at 254 nm (UVAS SC) and with a device for particle counting. Monitored parameters were compared with the measured E. coli counts using the integral calculations of the detected peaks. EC measurement gave the strongest signal compared with the measured baseline during the E. coli intrusion. Integral calculations showed that the peaks in the EC, pH, T, turbidity and UVAS SC data were detected corresponding to the time predicted. However, the pH and temperature peaks detected were barely above the measured baseline and could easily be mixed with the background noise. The results indicate that on-line monitoring can be utilized for the rapid detection of microbial contaminants in the drinking water distribution system although the peak interpretation has to be performed carefully to avoid being mixed up with normal variations in the measurement data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unmanned Tactical Autonomous Control and Collaboration Situation Awareness

DTIC Science & Technology

2017-06-01

methodology framework using interdependence analysis (IA) tables for informing design requirements based on SA requirements. Future research should seek...requirements of UTACC. The authors then apply SA principles to Coactive Design in order to inform robotic design. The result is a methodology framework using...28  2.  Non -intrusive Methods ................................................................29  3.  Post-Mission Reviews

In-ground optical fibre Bragg grating pressure switch for security applications

NASA Astrophysics Data System (ADS)

Allwood, Gary; Wild, Graham; Hinckley, Steven

2012-02-01

In this study, a fibre Bragg grating (FBG) was embedded beneath three common flooring materials acting as a pressure switch for in-ground intrusion detection. This is achieved using an intensiometric detection system, where a laser diode and FBG were optically mismatched so that there was a static dc offset from the transmitted and reflected optical power signals. As pressure was applied, in the form of a footstep, a strain induced wavelength shift occurred that could then be detected by converting the wavelength shift into an intensity change. The change in intensity caused a significant change in the DC offset which behaved as on optical switch. This switch could easily be configured to trigger an alarm if required. The intention is to use the FBG sensor as an in-ground intrusion detection pressure switch to detect an intruder walking within range of the sensor. This type of intrusion detection system can be applied to both external (in soil, etc) and internal (within the foundations or flooring of the home) security systems. The results show that a person's footstep can clearly be detected through solid wood flooring, laminate flooring, and ceramic floor tiles.

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

A two-stage flow-based intrusion detection model for next-generation networks.

PubMed

Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.

A two-stage flow-based intrusion detection model for next-generation networks

PubMed Central

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results. PMID:29329294

Attacks and intrusion detection in wireless sensor networks of industrial SCADA systems

NASA Astrophysics Data System (ADS)

Kamaev, V. A.; Finogeev, A. G.; Finogeev, A. A.; Parygin, D. S.

2017-01-01

The effectiveness of automated process control systems (APCS) and supervisory control and data acquisition systems (SCADA) information security depends on the applied protection technologies of transport environment data transmission components. This article investigates the problems of detecting attacks in wireless sensor networks (WSN) of SCADA systems. As a result of analytical studies, the authors developed the detailed classification of external attacks and intrusion detection in sensor networks and brought a detailed description of attacking impacts on components of SCADA systems in accordance with the selected directions of attacks.

Hybrid feature selection for supporting lightweight intrusion detection systems

NASA Astrophysics Data System (ADS)

Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

2017-08-01

Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

Predicting and Detecting Emerging Cyberattack Patterns Using StreamWorks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, George; Choudhury, Sutanay; Feo, John T.

2014-06-30

The number and sophistication of cyberattacks on industries and governments have dramatically grown in recent years. To counter this movement, new advanced tools and techniques are needed to detect cyberattacks in their early stages such that defensive actions may be taken to avert or mitigate potential damage. From a cybersecurity analysis perspective, detecting cyberattacks may be cast as a problem of identifying patterns in computer network traffic. Logically and intuitively, these patterns may take on the form of a directed graph that conveys how an attack or intrusion propagates through the computers of a network. Such cyberattack graphs could providemore » cybersecurity analysts with powerful conceptual representations that are natural to express and analyze. We have been researching and developing graph-centric approaches and algorithms for dynamic cyberattack detection. The advanced dynamic graph algorithms we are developing will be packaged into a streaming network analysis framework known as StreamWorks. With StreamWorks, a scientist or analyst may detect and identify precursor events and patterns as they emerge in complex networks. This analysis framework is intended to be used in a dynamic environment where network data is streamed in and is appended to a large-scale dynamic graph. Specific graphical query patterns are decomposed and collected into a graph query library. The individual decomposed subpatterns in the library are continuously and efficiently matched against the dynamic graph as it evolves to identify and detect early, partial subgraph patterns. The scalable emerging subgraph pattern algorithms will match on both structural and semantic network properties.« less

A Metrics-Based Approach to Intrusion Detection System Evaluation for Distributed Real-Time Systems

DTIC Science & Technology

2002-04-01

Based Approach to Intrusion Detection System Evaluation for Distributed Real - Time Systems Authors: G. A. Fink, B. L. Chappell, T. G. Turner, and...Distributed, Security. 1 Introduction Processing and cost requirements are driving future naval combat platforms to use distributed, real - time systems of...distributed, real - time systems . As these systems grow more complex, the timing requirements do not diminish; indeed, they may become more constrained

Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

DTIC Science & Technology

2016-06-01

research is being done to incorporate the field of machine learning into intrusion detection. Machine learning is a branch of artificial intelligence (AI...adversarial drift." Proceedings of the 2013 ACM workshop on Artificial intelligence and security. ACM. (2013) Kantarcioglu, M., Xi, B., and Clifton, C. "A...34 Proceedings of the 4th ACM workshop on Security and artificial intelligence . ACM. (2011) Dua, S., and Du, X. Data Mining and Machine Learning in

Perimeter intrusion detection and assessment system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eaton, M.J.; Jacobs, J.; McGovern, D.E.

1977-11-01

To obtain an effective perimeter intrusion detection system requires careful sensor selection, procurement, and installation. The selection process involves a thorough understanding of the unique site features and how these features affect the performance of each type of sensor. It is necessary to develop procurement specifications to establish acceptable sensor performance limits. Careful explanation and inspection of critical installation dimensions is required during on-site construction. The implementation of these activities at a particular site is discussed.

A Targeted Attack For Enhancing Resiliency of Intelligent Intrusion Detection Modules in Energy Cyber Physical Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Youssef, Tarek; El Hariri, Mohammad; Habib, Hani

Abstract— Secure high-speed communication is required to ensure proper operation of complex power grid systems and prevent malicious tampering activities. In this paper, artificial neural networks with temporal dependency are introduced for false data identification and mitigation for broadcasted IEC 61850 SMV messages. The fast responses of such intelligent modules in intrusion detection make them suitable for time- critical applications, such as protection. However, care must be taken in selecting the appropriate intelligence model and decision criteria. As such, this paper presents a customizable malware script to sniff and manipulate SMV messages and demonstrates the ability of the malware tomore » trigger false positives in the neural network’s response. The malware developed is intended to be as a vaccine to harden the intrusion detection system against data manipulation attacks by enhancing the neural network’s ability to learn and adapt to these attacks.« less

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Hariri, Mohamad; Faddel, Samy; Mohammed, Osama

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted tomore » verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.« less

Trouble Brewing: Using Observations of Invariant Behavior to Detect Malicious Agency in Distributed Control Systems

NASA Astrophysics Data System (ADS)

McEvoy, Thomas Richard; Wolthusen, Stephen D.

Recent research on intrusion detection in supervisory data acquisition and control (SCADA) and DCS systems has focused on anomaly detection at protocol level based on the well-defined nature of traffic on such networks. Here, we consider attacks which compromise sensors or actuators (including physical manipulation), where intrusion may not be readily apparent as data and computational states can be controlled to give an appearance of normality, and sensor and control systems have limited accuracy. To counter these, we propose to consider indirect relations between sensor readings to detect such attacks through concurrent observations as determined by control laws and constraints.

Multilevel regression analyses to investigate the relationship between two variables over time: examining the longitudinal association between intrusion and avoidance.

PubMed

Suvak, Michael K; Walling, Sherry M; Iverson, Katherine M; Taft, Casey T; Resick, Patricia A

2009-12-01

Multilevel modeling is a powerful and flexible framework for analyzing nested data structures (e.g., repeated measures or longitudinal designs). The authors illustrate a series of multilevel regression procedures that can be used to elucidate the nature of the relationship between two variables across time. The goal is to help trauma researchers become more aware of the utility of multilevel modeling as a tool for increasing the field's understanding of posttraumatic adaptation. These procedures are demonstrated by examining the relationship between two posttraumatic symptoms, intrusion and avoidance, across five assessment points in a sample of rape and robbery survivors (n = 286). Results revealed that changes in intrusion were highly correlated with changes in avoidance over the 18-month posttrauma period.

Characterization of Extremely Lightweight Intrusion Detection (ELIDe) Power Utilization with Varying Throughput and Payload Sizes

DTIC Science & Technology

2015-09-01

Extremely Lightweight Intrusion Detection (ELIDe) algorithm on an Android -based mobile device. Our results show that the hashing and inner product...approximately 2.5 megabits per second (assuming a normal distribution of packet sizes) with no significant packet loss. 15. SUBJECT TERMS ELIDe, Android , pcap...system (OS). To run ELIDe, the current version was ported for use on Android .4 2.1 Mobile Device After ELIDe was ported to the Android mobile

A prototype forensic toolkit for industrial-control-systems incident response

NASA Astrophysics Data System (ADS)

Carr, Nickolas B.; Rowe, Neil C.

2015-05-01

Industrial control systems (ICSs) are an important part of critical infrastructure in cyberspace. They are especially vulnerable to cyber-attacks because of their legacy hardware and software and the difficulty of changing it. We first survey the history of intrusions into ICSs, the more serious of which involved a continuing adversary presence on an ICS network. We discuss some common vulnerabilities and the categories of possible attacks, noting the frequent use of software written a long time ago. We propose a framework for designing ICS incident response under the constraints that no new software must be required and that interventions cannot impede the continuous processing that is the norm for such systems. We then discuss a prototype toolkit we built using the Windows Management Instrumentation Command-Line tool for host-based analysis and the Bro intrusion-detection software for network-based analysis. Particularly useful techniques we used were learning the historical range of parameters of numeric quantities so as to recognize anomalies, learning the usual addresses of connections to a node, observing Internet addresses (usually rare), observing anomalous network protocols such as unencrypted data transfers, observing unusual scheduled tasks, and comparing key files through registry entries and hash values to find malicious modifications. We tested our methods on actual data from ICSs including publicly-available data, voluntarily-submitted data, and researcher-provided "advanced persistent threat" data. We found instances of interesting behavior in our experiments. Intrusions were generally easy to see because of the repetitive nature of most processing on ICSs, but operators need to be motivated to look.

A Non-Intrusive Alert System for Maritime Anomalies: Literature Review and the Development and Assessment of Interface Design Concepts (Systeme d’Alerte non Intrusive en cas d’Anomalies Maritimes: Examen de la Documentation et Elaboration/Evaluation de Concepts d’Interface)

DTIC Science & Technology

2009-03-01

compris les anomalies (augmentation soudaine de vitesse, déroutement des navires, etc.). Il est donc nécessaire de disposer d’un système capable...ONTOLOGY ................................................................ 6 FIGURE 2: IRC FRAMEWORK (ADAPTED FROM MCCRICKARD ET AL ., 2003A, P. 321...19 FIGURE 3: HAZARD NETWORK (HAUTAMAKI ET AL ., 2006, P. 7

A model for anomaly classification in intrusion detection systems

NASA Astrophysics Data System (ADS)

Ferreira, V. O.; Galhardi, V. V.; Gonçalves, L. B. L.; Silva, R. C.; Cansian, A. M.

2015-09-01

Intrusion Detection Systems (IDS) are traditionally divided into two types according to the detection methods they employ, namely (i) misuse detection and (ii) anomaly detection. Anomaly detection has been widely used and its main advantage is the ability to detect new attacks. However, the analysis of anomalies generated can become expensive, since they often have no clear information about the malicious events they represent. In this context, this paper presents a model for automated classification of alerts generated by an anomaly based IDS. The main goal is either the classification of the detected anomalies in well-defined taxonomies of attacks or to identify whether it is a false positive misclassified by the IDS. Some common attacks to computer networks were considered and we achieved important results that can equip security analysts with best resources for their analyses.

Real Time Intrusion Detection (la detection des intrusions en temps reel)

DTIC Science & Technology

2003-06-01

prometteuses actuelles et nouvelles, susceptibles d’être utilisées pour des applications temps réel, et laisse prévoir ainsi les technologies et les...components, to survivability, as a risk management problem requiring the involvement of the whole organization to support the survival of the organization’s...this topic. In all fairness , until recently “reaction” has not been part of IDS’s functionality. Above all and as stated previously, traditional RT

Statistical process control based chart for information systems security

NASA Astrophysics Data System (ADS)

Khan, Mansoor S.; Cui, Lirong

2015-07-01

Intrusion detection systems have a highly significant role in securing computer networks and information systems. To assure the reliability and quality of computer networks and information systems, it is highly desirable to develop techniques that detect intrusions into information systems. We put forward the concept of statistical process control (SPC) in computer networks and information systems intrusions. In this article we propose exponentially weighted moving average (EWMA) type quality monitoring scheme. Our proposed scheme has only one parameter which differentiates it from the past versions. We construct the control limits for the proposed scheme and investigate their effectiveness. We provide an industrial example for the sake of clarity for practitioner. We give comparison of the proposed scheme with EWMA schemes and p chart; finally we provide some recommendations for the future work.

A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems.

PubMed

Raman, M R Gauthama; Somu, Nivethitha; Kirthivasan, Kannan; Sriram, V S Shankar

2017-08-01

Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems

PubMed Central

Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy. PMID:26161437

Intelligent detection and identification in fiber-optical perimeter intrusion monitoring system based on the FBG sensor network

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Li, Hanyu; Xie, Xin

2015-12-01

A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal's profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems.

PubMed

Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.

A research using hybrid RBF/Elman neural networks for intrusion detection system secure model

NASA Astrophysics Data System (ADS)

Tong, Xiaojun; Wang, Zhu; Yu, Haining

2009-10-01

A hybrid RBF/Elman neural network model that can be employed for both anomaly detection and misuse detection is presented in this paper. The IDSs using the hybrid neural network can detect temporally dispersed and collaborative attacks effectively because of its memory of past events. The RBF network is employed as a real-time pattern classification and the Elman network is employed to restore the memory of past events. The IDSs using the hybrid neural network are evaluated against the intrusion detection evaluation data sponsored by U.S. Defense Advanced Research Projects Agency (DARPA). Experimental results are presented in ROC curves. Experiments show that the IDSs using this hybrid neural network improve the detection rate and decrease the false positive rate effectively.

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments

PubMed Central

Avalappampatty Sivasamy, Aneetha; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

PubMed

Sivasamy, Aneetha Avalappampatty; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

Idaho National Laboratory Supervisory Control and Data Acquisition Intrusion Detection System (SCADA IDS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jared Verba; Michael Milvich

2008-05-01

Current Intrusion Detection System (IDS) technology is not suited to be widely deployed inside a Supervisory, Control and Data Acquisition (SCADA) environment. Anomaly- and signature-based IDS technologies have developed methods to cover information technology-based networks activity and protocols effectively. However, these IDS technologies do not include the fine protocol granularity required to ensure network security inside an environment with weak protocols lacking authentication and encryption. By implementing a more specific and more intelligent packet inspection mechanism, tailored traffic flow analysis, and unique packet tampering detection, IDS technology developed specifically for SCADA environments can be deployed with confidence in detecting maliciousmore » activity.« less

Appliance of Independent Component Analysis to System Intrusion Analysis

NASA Astrophysics Data System (ADS)

Ishii, Yoshikazu; Takagi, Tarou; Nakai, Kouji

In order to analyze the output of the intrusion detection system and the firewall, we evaluated the applicability of ICA(independent component analysis). We developed a simulator for evaluation of intrusion analysis method. The simulator consists of the network model of an information system, the service model and the vulnerability model of each server, and the action model performed on client and intruder. We applied the ICA for analyzing the audit trail of simulated information system. We report the evaluation result of the ICA on intrusion analysis. In the simulated case, ICA separated two attacks correctly, and related an attack and the abnormalities of the normal application produced under the influence of the attach.

Visual behavior characterization for intrusion and misuse detection

NASA Astrophysics Data System (ADS)

Erbacher, Robert F.; Frincke, Deborah

2001-05-01

As computer and network intrusions become more and more of a concern, the need for better capabilities, to assist in the detection and analysis of intrusions also increase. System administrators typically rely on log files to analyze usage and detect misuse. However, as a consequence of the amount of data collected by each machine, multiplied by the tens or hundreds of machines under the system administrator's auspices, the entirety of the data available is neither collected nor analyzed. This is compounded by the need to analyze network traffic data as well. We propose a methodology for analyzing network and computer log information visually based on the analysis of the behavior of the users. Each user's behavior is the key to determining their intent and overriding activity, whether they attempt to hide their actions or not. Proficient hackers will attempt to hide their ultimate activities, which hinders the reliability of log file analysis. Visually analyzing the users''s behavior however, is much more adaptable and difficult to counteract.

Forced intrusion of water and aqueous solutions in microporous materials: from fundamental thermodynamics to energy storage devices.

PubMed

Fraux, Guillaume; Coudert, François-Xavier; Boutin, Anne; Fuchs, Alain H

2017-12-07

We review the high pressure forced intrusion studies of water in hydrophobic microporous materials such as zeolites and MOFs, a field of research that has emerged some 15 years ago and is now very active. Many of these studies are aimed at investigating the possibility of using these systems as energy storage devices. A series of all-silica zeolites (zeosil) frameworks were found suitable for reversible energy storage because of their stability with respect to hydrolysis after several water intrusion-extrusion cycles. Several microporous hydrophobic zeolite imidazolate frameworks (ZIFs) also happen to be quite stable and resistant towards hydrolysis and thus seem very promising for energy storage applications. Replacing pure water by electrolyte aqueous solutions enables to increase the stored energy by a factor close to 3, on account of the high pressure shift of the intrusion transition. In addition to the fact that aqueous solutions and microporous silica materials are environmental friendly, these systems are thus becoming increasingly interesting for the design of new energy storage devices. This review also addresses the theoretical approaches and molecular simulations performed in order to better understand the experimental behavior of nano-confined water. Molecular simulation studies showed that water condensation takes place through a genuine first-order phase transition, provided that the interconnected pores structure is 3-dimensional and sufficiently open. In an extreme confinement situations such as in ferrierite zeosil, condensation seem to take place through a continuous supercritical crossing from a diluted to a dense fluid, on account of the fact that the first-order transition line is shifted to higher pressure, and the confined water critical point is correlatively shifted to lower temperature. These molecular simulation studies suggest that the most important features of the intrusion/extrusion process can be understood in terms of equilibrium thermodynamics considerations.

Neural methods based on modified reputation rules for detection and identification of intrusion attacks in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2010-04-01

Determining methods to secure the process of data fusion against attacks by compromised nodes in wireless sensor networks (WSNs) and to quantify the uncertainty that may exist in the aggregation results is a critical issue in mitigating the effects of intrusion attacks. Published research has introduced the concept of the trustworthiness (reputation) of a single sensor node. Reputation is evaluated using an information-theoretic concept, the Kullback- Leibler (KL) distance. Reputation is added to the set of security features. In data aggregation, an opinion, a metric of the degree of belief, is generated to represent the uncertainty in the aggregation result. As aggregate information is disseminated along routes to the sink node(s), its corresponding opinion is propagated and regulated by Josang's belief model. By applying subjective logic on the opinion to manage trust propagation, the uncertainty inherent in aggregation results can be quantified for use in decision making. The concepts of reputation and opinion are modified to allow their application to a class of dynamic WSNs. Using reputation as a factor in determining interim aggregate information is equivalent to implementation of a reputation-based security filter at each processing stage of data fusion, thereby improving the intrusion detection and identification results based on unsupervised techniques. In particular, the reputation-based version of the probabilistic neural network (PNN) learns the signature of normal network traffic with the random probability weights normally used in the PNN replaced by the trust-based quantified reputations of sensor data or subsequent aggregation results generated by the sequential implementation of a version of Josang's belief model. A two-stage, intrusion detection and identification algorithm is implemented to overcome the problems of large sensor data loads and resource restrictions in WSNs. Performance of the twostage algorithm is assessed in simulations of WSN scenarios with multiple sensors at edge nodes for known intrusion attacks. Simulation results show improved robustness of the two-stage design based on reputation-based NNs to intrusion anomalies from compromised nodes and external intrusion attacks.

Acoustic emission intrusion detector

DOEpatents

Carver, Donald W.; Whittaker, Jerry W.

1980-01-01

An intrusion detector is provided for detecting a forcible entry into a secured structure while minimizing false alarms. The detector uses a piezoelectric crystal transducer to sense acoustic emissions. The transducer output is amplified by a selectable gain amplifier to control the sensitivity. The rectified output of the amplifier is applied to a Schmitt trigger circuit having a preselected threshold level to provide amplitude discrimination. Timing circuitry is provided which is activated by successive pulses from the Schmitt trigger which lie within a selected time frame for frequency discrimination. Detected signals having proper amplitude and frequency trigger an alarm within the first complete cycle time of a detected acoustical disturbance signal.

Saltwater intrusion in the surficial aquifer system of the Big Cypress Basin, southwest Florida, and a proposed plan for improved salinity monitoring

USGS Publications Warehouse

Prinos, Scott T.

2013-01-01

The installation of drainage canals, poorly cased wells, and water-supply withdrawals have led to saltwater intrusion in the primary water-use aquifers in southwest Florida. Increasing population and water use have exacerbated this problem. Installation of water-control structures, well-plugging projects, and regulation of water use have slowed saltwater intrusion, but the chloride concentration of samples from some of the monitoring wells in this area indicates that saltwater intrusion continues to occur. In addition, rising sea level could increase the rate and extent of saltwater intrusion. The existing saltwater intrusion monitoring network was examined and found to lack the necessary organization, spatial distribution, and design to properly evaluate saltwater intrusion. The most recent hydrogeologic framework of southwest Florida indicates that some wells may be open to multiple aquifers or have an incorrect aquifer designation. Some of the sampling methods being used could result in poor-quality data. Some older wells are badly corroded, obstructed, or damaged and may not yield useable samples. Saltwater in some of the canals is in close proximity to coastal well fields. In some instances, saltwater occasionally occurs upstream from coastal salinity control structures. These factors lead to an incomplete understanding of the extent and threat of saltwater intrusion in southwest Florida. A proposed plan to improve the saltwater intrusion monitoring network in the South Florida Water Management District’s Big Cypress Basin describes improvements in (1) network management, (2) quality assurance, (3) documentation, (4) training, and (5) data accessibility. The plan describes improvements to hydrostratigraphic and geospatial network coverage that can be accomplished using additional monitoring, surface geophysical surveys, and borehole geophysical logging. Sampling methods and improvements to monitoring well design are described in detail. Geochemical analyses that provide insights concerning the sources of saltwater in the aquifers are described. The requirement to abandon inactive wells is discussed.

Intrusive Method for Uncertainty Quantification in a Multiphase Flow Solver

NASA Astrophysics Data System (ADS)

Turnquist, Brian; Owkes, Mark

2016-11-01

Uncertainty quantification (UQ) is a necessary, interesting, and often neglected aspect of fluid flow simulations. To determine the significance of uncertain initial and boundary conditions, a multiphase flow solver is being created which extends a single phase, intrusive, polynomial chaos scheme into multiphase flows. Reliably estimating the impact of input uncertainty on design criteria can help identify and minimize unwanted variability in critical areas, and has the potential to help advance knowledge in atomizing jets, jet engines, pharmaceuticals, and food processing. Use of an intrusive polynomial chaos method has been shown to significantly reduce computational cost over non-intrusive collocation methods such as Monte-Carlo. This method requires transforming the model equations into a weak form through substitution of stochastic (random) variables. Ultimately, the model deploys a stochastic Navier Stokes equation, a stochastic conservative level set approach including reinitialization, as well as stochastic normals and curvature. By implementing these approaches together in one framework, basic problems may be investigated which shed light on model expansion, uncertainty theory, and fluid flow in general. NSF Grant Number 1511325.

multiUQ: An intrusive uncertainty quantification tool for gas-liquid multiphase flows

NASA Astrophysics Data System (ADS)

Turnquist, Brian; Owkes, Mark

2017-11-01

Uncertainty quantification (UQ) can improve our understanding of the sensitivity of gas-liquid multiphase flows to variability about inflow conditions and fluid properties, creating a valuable tool for engineers. While non-intrusive UQ methods (e.g., Monte Carlo) are simple and robust, the cost associated with these techniques can render them unrealistic. In contrast, intrusive UQ techniques modify the governing equations by replacing deterministic variables with stochastic variables, adding complexity, but making UQ cost effective. Our numerical framework, called multiUQ, introduces an intrusive UQ approach for gas-liquid flows, leveraging a polynomial chaos expansion of the stochastic variables: density, momentum, pressure, viscosity, and surface tension. The gas-liquid interface is captured using a conservative level set approach, including a modified reinitialization equation which is robust and quadrature free. A least-squares method is leveraged to compute the stochastic interface normal and curvature needed in the continuum surface force method for surface tension. The solver is tested by applying uncertainty to one or two variables and verifying results against the Monte Carlo approach. NSF Grant #1511325.

A simulation/optimization study to assess seawater intrusion management strategies for the Gaza Strip coastal aquifer (Palestine)

NASA Astrophysics Data System (ADS)

Dentoni, Marta; Deidda, Roberto; Paniconi, Claudio; Qahman, Khalid; Lecca, Giuditta

2015-03-01

Seawater intrusion is one of the major threats to freshwater resources in coastal areas, often exacerbated by groundwater overexploitation. Mitigation measures are needed to properly manage aquifers, and to restore groundwater quality. This study integrates three computational tools into a unified framework to investigate seawater intrusion in coastal areas and to assess strategies for managing groundwater resources under natural and human-induced stresses. The three components are a three-dimensional hydrogeological model for density-dependent variably saturated flow and miscible salt transport, an automatic calibration procedure that uses state variable outputs from the model to estimate selected model parameters, and an optimization module that couples a genetic algorithm with the simulation model. The computational system is used to rank alternative strategies for mitigation of seawater intrusion, taking into account conflicting objectives and problem constraints. It is applied to the Gaza Strip (Palestine) coastal aquifer to identify a feasible groundwater management strategy for the period 2011-2020. The optimized solution is able to: (1) keep overall future abstraction from municipal groundwater wells close to the user-defined maximum level, (2) increase the average groundwater heads, and (3) lower both the total mass of salt extracted and the extent of the areas affected by seawater intrusion.

Characterizing Articulation in Apraxic Speech Using Real-Time Magnetic Resonance Imaging.

PubMed

Hagedorn, Christina; Proctor, Michael; Goldstein, Louis; Wilson, Stephen M; Miller, Bruce; Gorno-Tempini, Maria Luisa; Narayanan, Shrikanth S

2017-04-14

Real-time magnetic resonance imaging (MRI) and accompanying analytical methods are shown to capture and quantify salient aspects of apraxic speech, substantiating and expanding upon evidence provided by clinical observation and acoustic and kinematic data. Analysis of apraxic speech errors within a dynamic systems framework is provided and the nature of pathomechanisms of apraxic speech discussed. One adult male speaker with apraxia of speech was imaged using real-time MRI while producing spontaneous speech, repeated naming tasks, and self-paced repetition of word pairs designed to elicit speech errors. Articulatory data were analyzed, and speech errors were detected using time series reflecting articulatory activity in regions of interest. Real-time MRI captured two types of apraxic gestural intrusion errors in a word pair repetition task. Gestural intrusion errors in nonrepetitive speech, multiple silent initiation gestures at the onset of speech, and covert (unphonated) articulation of entire monosyllabic words were also captured. Real-time MRI and accompanying analytical methods capture and quantify many features of apraxic speech that have been previously observed using other modalities while offering high spatial resolution. This patient's apraxia of speech affected the ability to select only the appropriate vocal tract gestures for a target utterance, suppressing others, and to coordinate them in time.

Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection

PubMed Central

Kaliappan, Jayakumar; Thiagarajan, Revathi; Sundararajan, Karpagam

2015-01-01

An intrusion detection system (IDS) helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. This paper is designed on the idea that each IDS is efficient in detecting a specific type of attack. In proposed Multiple IDS Unit (MIU), there are five IDS units, and each IDS follows a unique algorithm to detect attacks. The feature selection is done with the help of genetic algorithm. The selected features of the input traffic are passed on to the MIU for processing. The decision from each IDS is termed as local decision. The fusion unit inside the MIU processes all the local decisions with the help of majority voting rule and makes the final decision. The proposed system shows a very good improvement in detection rate and reduces the false alarm rate. PMID:26295058

Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection.

PubMed

Kaliappan, Jayakumar; Thiagarajan, Revathi; Sundararajan, Karpagam

2015-01-01

An intrusion detection system (IDS) helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. This paper is designed on the idea that each IDS is efficient in detecting a specific type of attack. In proposed Multiple IDS Unit (MIU), there are five IDS units, and each IDS follows a unique algorithm to detect attacks. The feature selection is done with the help of genetic algorithm. The selected features of the input traffic are passed on to the MIU for processing. The decision from each IDS is termed as local decision. The fusion unit inside the MIU processes all the local decisions with the help of majority voting rule and makes the final decision. The proposed system shows a very good improvement in detection rate and reduces the false alarm rate.

A Framework for Learning Analytics Using Commodity Wearable Devices

PubMed Central

Lu, Yu; Zhang, Sen; Zhang, Zhiqiang; Xiao, Wendong; Yu, Shengquan

2017-01-01

We advocate for and introduce LEARNSense, a framework for learning analytics using commodity wearable devices to capture learner’s physical actions and accordingly infer learner context (e.g., student activities and engagement status in class). Our work is motivated by the observations that: (a) the fine-grained individual-specific learner actions are crucial to understand learners and their context information; (b) sensor data available on the latest wearable devices (e.g., wrist-worn and eye wear devices) can effectively recognize learner actions and help to infer learner context information; (c) the commodity wearable devices that are widely available on the market can provide a hassle-free and non-intrusive solution. Following the above observations and under the proposed framework, we design and implement a sensor-based learner context collector running on the wearable devices. The latest data mining and sensor data processing techniques are employed to detect different types of learner actions and context information. Furthermore, we detail all of the above efforts by offering a novel and exemplary use case: it successfully provides the accurate detection of student actions and infers the student engagement states in class. The specifically designed learner context collector has been implemented on the commodity wrist-worn device. Based on the collected and inferred learner information, the novel intervention and incentivizing feedback are introduced into the system service. Finally, a comprehensive evaluation with the real-world experiments, surveys and interviews demonstrates the effectiveness and impact of the proposed framework and this use case. The F1 score for the student action classification tasks achieve 0.9, and the system can effectively differentiate the defined three learner states. Finally, the survey results show that the learners are satisfied with the use of our system (mean score of 3.7 with a standard deviation of 0.55). PMID:28613236

A Framework for Learning Analytics Using Commodity Wearable Devices.

PubMed

Lu, Yu; Zhang, Sen; Zhang, Zhiqiang; Xiao, Wendong; Yu, Shengquan

2017-06-14

We advocate for and introduce LEARNSense, a framework for learning analytics using commodity wearable devices to capture learner's physical actions and accordingly infer learner context (e.g., student activities and engagement status in class). Our work is motivated by the observations that: (a) the fine-grained individual-specific learner actions are crucial to understand learners and their context information; (b) sensor data available on the latest wearable devices (e.g., wrist-worn and eye wear devices) can effectively recognize learner actions and help to infer learner context information; (c) the commodity wearable devices that are widely available on the market can provide a hassle-free and non-intrusive solution. Following the above observations and under the proposed framework, we design and implement a sensor-based learner context collector running on the wearable devices. The latest data mining and sensor data processing techniques are employed to detect different types of learner actions and context information. Furthermore, we detail all of the above efforts by offering a novel and exemplary use case: it successfully provides the accurate detection of student actions and infers the student engagement states in class. The specifically designed learner context collector has been implemented on the commodity wrist-worn device. Based on the collected and inferred learner information, the novel intervention and incentivizing feedback are introduced into the system service. Finally, a comprehensive evaluation with the real-world experiments, surveys and interviews demonstrates the effectiveness and impact of the proposed framework and this use case. The F1 score for the student action classification tasks achieve 0.9, and the system can effectively differentiate the defined three learner states. Finally, the survey results show that the learners are satisfied with the use of our system (mean score of 3.7 with a standard deviation of 0.55).

Diagnosing and Reconstructing Real-World Hydroclimatic Dynamics from Time Sequenced Data: The Case of Saltwater Intrusion into Coastal Wetlands in Everglades National Park

NASA Astrophysics Data System (ADS)

Huffaker, R.; Munoz-Carpena, R.

2016-12-01

There are increasing calls to audit decision-support models used for environmental policy to ensure that they correspond with the reality facing policy makers. Modelers can establish correspondence by providing empirical evidence of real-world dynamic behavior that their models skillfully simulate. We present a pre-modeling diagnostic framework—based on nonlinear dynamic analysis—for detecting and reconstructing real-world environmental dynamics from observed time-sequenced data. Phenomenological (data-driven) modeling—based on machine learning regression techniques—extracts a set of ordinary differential equations governing empirically-diagnosed system dynamics from a single time series, or from multiple time series on causally-interacting variables. We apply the framework to investigate saltwater intrusion into coastal wetlands in Everglades National Park, Florida, USA. We test the following hypotheses posed in the literature linking regional hydrologic variables with global climatic teleconnections: (1) Sea level in Florida Bay drives well level and well salinity in the coastal Everglades; (2) Atlantic Multidecadal Oscillation (AMO) drives sea level, well level and well salinity; and (3) AMO and (El Niño Southern Oscillation) ENSO bi-causally interact. The thinking is that salt water intrusion links ocean-surface salinity with salinity of inland water sources, and sea level with inland water; that AMO and ENSO share a teleconnective relationship (perhaps through the atmosphere); and that AMO and ENSO both influence inland precipitation and thus well levels. Our results support these hypotheses, and we successfully construct a parsimonious phenomenological model that reproduces diagnosed nonlinear dynamics and system interactions. We propose that reconstructed data dynamics be used, along with other expert information, as a rigorous benchmark to guide specification and testing of hydrologic decision support models corresponding with real-world behavior.

Detecting the thermal aureole of a magmatic intrusion in immature to mature sediments: a case study in the East Greenland Basin (73°N)

NASA Astrophysics Data System (ADS)

Aubourg, Charles; Techer, Isabelle; Geoffroy, Laurent; Clauer, Norbert; Baudin, François

2014-01-01

The Cretaceous and Triassic argillaceous rocks from the passive margin of Greenland have been investigated in order to detect the thermal aureole of magmatic intrusions, ranging from metric dyke to kilometric syenite pluton. Rock-Eval data (Tmax generally <468 °C), vitrinite reflectance data (R0 < 0.9 per cent) and illite cristallinity data (ICI > 0.3), all indicate a maximum of 5 km burial for the argillaceous rocks whatever the distance to an intrusion. The K-Ar dating of the clays <2 μm fraction suggests that illites are mostly detrital, except near magmatic intrusions where younger ages are recorded. To get more information about the extent of the thermal aureole, rock magnetism data were determined. At distance away from the thermal aureole of the syenite intrusion, Triassic argillaceous rocks reveal a standard magnetic assemblage compatible with their burial (R0 ˜ 0.4 per cent). It is constituted essentially by neoformed stoichiometric magnetite (Fe3O4). In contrast, within the thermal aureole of the magmatic intrusions, the Cretaceous argillaceous rocks contain micron-sized pyrrhotite (Fe7S8), firmly identified through the recognition of Besnus transition at 35 K. The thermal demagnetization of natural remanence carried by this pyrrhotite shows a diagnostic `square shouldered' pattern, indicating a narrow grain size distribution of pyrrhotite. The extension of this diagnostic pyrrhotite maps a ˜10-km-thick aureole around the syenitic pluton. Away from this aureole, the magnetic assemblage is diagnostic of those found in argillaceous rocks where organic matter is mature.

An Intrusion Detection System for the Protection of Railway Assets Using Fiber Bragg Grating Sensors

PubMed Central

Catalano, Angelo; Bruno, Francesco Antonio; Pisco, Marco; Cutolo, Antonello; Cusano, Andrea

2014-01-01

We demonstrate the ability of Fiber Bragg Gratings (FBGs) sensors to protect large areas from unauthorized activities in railway scenarios such as stations or tunnels. We report on the technological strategy adopted to protect a specific depot, representative of a common scenario for security applications in the railway environment. One of the concerns in the protection of a railway area centers on the presence of rail-tracks, which cannot be obstructed with physical barriers. We propose an integrated optical fiber system composed of FBG strain sensors that can detect human intrusion for protection of the perimeter combined with FBG accelerometer sensors for protection of rail-track access. Several trials were carried out in indoor and outdoor environments. The results demonstrate that FBG strain sensors bonded under a ribbed rubber mat enable the detection of intruder break-in via the pressure induced on the mat, whereas the FBG accelerometers installed under the rails enable the detection of intruders walking close to the railroad tracks via the acoustic surface waves generated by footsteps. Based on a single enabling technology, this integrated system represents a valuable intrusion detection system for railway security and could be integrated with other sensing functionalities in the railway field using fiber optic technology. PMID:25268920

Seismic signature of active intrusions in mountain chains.

PubMed

Di Luccio, Francesca; Chiodini, Giovanni; Caliro, Stefano; Cardellini, Carlo; Convertito, Vincenzo; Pino, Nicola Alessandro; Tolomei, Cristiano; Ventura, Guido

2018-01-01

Intrusions are a ubiquitous component of mountain chains and testify to the emplacement of magma at depth. Understanding the emplacement and growth mechanisms of intrusions, such as diapiric or dike-like ascent, is critical to constrain the evolution and structure of the crust. Petrological and geological data allow us to reconstruct magma pathways and long-term magma differentiation and assembly processes. However, our ability to detect and reconstruct the short-term dynamics related to active intrusive episodes in mountain chains is embryonic, lacking recognized geophysical signals. We analyze an anomalously deep seismic sequence (maximum magnitude 5) characterized by low-frequency bursts of earthquakes that occurred in 2013 in the Apennine chain in Italy. We provide seismic evidences of fluid involvement in the earthquake nucleation process and identify a thermal anomaly in aquifers where CO 2 of magmatic origin dissolves. We show that the intrusion of dike-like bodies in mountain chains may trigger earthquakes with magnitudes that may be relevant to seismic hazard assessment. These findings provide a new perspective on the emplacement mechanisms of intrusive bodies and the interpretation of the seismicity in mountain chains.

Seismic signature of active intrusions in mountain chains

PubMed Central

Di Luccio, Francesca; Chiodini, Giovanni; Caliro, Stefano; Cardellini, Carlo; Convertito, Vincenzo; Pino, Nicola Alessandro; Tolomei, Cristiano; Ventura, Guido

2018-01-01

Intrusions are a ubiquitous component of mountain chains and testify to the emplacement of magma at depth. Understanding the emplacement and growth mechanisms of intrusions, such as diapiric or dike-like ascent, is critical to constrain the evolution and structure of the crust. Petrological and geological data allow us to reconstruct magma pathways and long-term magma differentiation and assembly processes. However, our ability to detect and reconstruct the short-term dynamics related to active intrusive episodes in mountain chains is embryonic, lacking recognized geophysical signals. We analyze an anomalously deep seismic sequence (maximum magnitude 5) characterized by low-frequency bursts of earthquakes that occurred in 2013 in the Apennine chain in Italy. We provide seismic evidences of fluid involvement in the earthquake nucleation process and identify a thermal anomaly in aquifers where CO2 of magmatic origin dissolves. We show that the intrusion of dike-like bodies in mountain chains may trigger earthquakes with magnitudes that may be relevant to seismic hazard assessment. These findings provide a new perspective on the emplacement mechanisms of intrusive bodies and the interpretation of the seismicity in mountain chains. PMID:29326978

Design of an Acoustic Target Intrusion Detection System Based on Small-Aperture Microphone Array.

PubMed

Zu, Xingshui; Guo, Feng; Huang, Jingchang; Zhao, Qin; Liu, Huawei; Li, Baoqing; Yuan, Xiaobing

2017-03-04

Automated surveillance of remote locations in a wireless sensor network is dominated by the detection algorithm because actual intrusions in such locations are a rare event. Therefore, a detection method with low power consumption is crucial for persistent surveillance to ensure longevity of the sensor networks. A simple and effective two-stage algorithm composed of energy detector (ED) and delay detector (DD) with all its operations in time-domain using small-aperture microphone array (SAMA) is proposed. The algorithm analyzes the quite different velocities between wind noise and sound waves to improve the detection capability of ED in the surveillance area. Experiments in four different fields with three types of vehicles show that the algorithm is robust to wind noise and the probability of detection and false alarm are 96.67% and 2.857%, respectively.

Evaluation and analysis of non-intrusive techniques for detecting illicit substances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Micklich, B.J.; Roche, C.T.; Fink, C.L.

1995-12-31

Argonne National Laboratory (ANL) and the Houston Advanced Research Center (HARC) have been tasked by the Counterdrug Technology Assessment Center of the Office of National Drug Control Policy to conduct evaluations and analyses of technologies for the non-intrusive inspection of containers for illicit substances. These technologies span the range of nuclear, X-ray, and chemical techniques used in nondestructive sample analysis. ANL has performed assessments of nuclear and X-ray inspection concepts and undertaken site visits with developers to understand the capabilities and the range of applicability of candidate systems. ANL and HARC have provided support to law enforcement agencies (LEAs), includingmore » participation in numerous field studies. Both labs have provided staff to assist in the Narcotics Detection Technology Assessment (NDTA) program for evaluating drug detection systems. Also, the two labs are performing studies of drug contamination of currency. HARC has directed technical evaluations of automated ballistics imaging and identification systems under consideration by law enforcement agencies. ANL and HARC have sponsored workshops and a symposium, and are participating in a Non-Intrusive Inspection Study being led by Dynamics Technology, Incorporated.« less

Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armstrong, Peter R.; Laughman, C R.; Leeb, S B.

Non-intrusive load monitoring (NILM) is accomplished by sampling voltage and current at high rates and reducing the resulting start transients or harmonic contents to concise ''signatures''. Changes in these signatures can be used to detect, and in many cases directly diagnose, equipment and component faults associated with roof-top cooling units. Use of the NILM for fault detection and diagnosis (FDD) is important because (1) it complements other FDD schemes that are based on thermo-fluid sensors and analyses and (2) it is minimally intrusive (one measuring point in the relatively protected confines of the control panel) and therefore inherently reliable. Thismore » paper describes changes in the power signatures of fans and compressors that were found, experimentally and theoretically, to be useful for fault detection.« less

Dike Intrusion Process of 2000 Miyakejima - Kozujima Event estimated from GPS measurements in Kozujima - Niijima Islands, central Japan

NASA Astrophysics Data System (ADS)

Murase, M.; Nakao, S.; Kato, T.; Tabei, T.; Kimata, F.; Fujii, N.

2003-12-01

Kozujima - Niijima Islands of Izu Volcano Islands are located about 180 km southeast of Tokyo, Japan. Although the last volcano eruptions in Kozujima and Niijima volcanoes are recorded more than 1000 year before, the ground deformation of 2-3 cm is detected at Kozujima - Niijima Islands by GPS measurements since 1996. On June 26, 2000, earthquake swarm and large ground deformation more than 20 cm are observed at Miyakejima volcano located 40 km east-southeastward of Kozu Island, and volcano eruption are continued since July 7. Remarkable earthquake swarm including five earthquakes more than M5 is stretching to Kozushima Island from Miyakejima Island. From the rapid ground deformation detected by continuous GPS measurements at Miyakejima Island on June 26, magma intrusion models of two or three dikes are discussed in the south and west part of Miyakejima volcano by Irwan et al.(2003) and Ueda et al.(2003). They also estimate dike intrusions are propagated from southern part of Miyakejima volcano to western part, and finally dike intrusion is stretching to 20 km distance toward Kozujima Island. From the ground deformation detected by GPS daily solution of Nation-wide dense GPS network (GEONET), some dike intrusion models are discussed. Ito et al.(2002) estimate the huge dike intrusion with length of about 20 km and volume of 1 km3 in the sea area between the Miyake Island and Kozu Island. (And) Nishimura et al.(2001) introduce not only dike but also aseismic creep source to explain the deformation in Shikinejima. Yamaoka et al.(2002) discuss the dike and spherical deflation source under the dike, because of no evidence supported large aseismic creep. They indicate a dike and spherical deflation source model is as good as dike and creep source model. In case of dike and creep, magma supply is only from the chamber under the Miyakejima volcano. In dike and spherical deflation source model, magma supply is from under Miyakejima volcano and under the dike. Furuya et al.(2003) discuss the gravity change of Miyakejima and they conclude that the magma supply from the chamber under Miyakejima volcano is too small to explain the dike intrusion. In order to discuss the local ground deformation, Nagoya University additionally operates the local GPS network of single frequency receivers at seven sites in Kozujima, Shikineshima and Niijima. Form the vertical deformation detected on local GPS network, northward tilting is observed in Kozujima. We used Genetic Algorithm (GA) for search the model parameter of dike intrusion and fault. GA is an attractive global search tool suitable for the irregular, multimodal fitness functions typically observed in nonlinear optimization problems. We discuss mechanism of Miyakejima - Kozujima event in detail using data of 20 GPS sites near field by GA. The results suggest that magma intrusion system of the dike between Miyakejima and Kozujima changes on August 18 when a large volcano eruption occurred. Until August 18 the activity of creep fault is high and after then deflation at the point source just under the dike is active.

Analogue modelling on the interaction between shallow magma intrusion and a strike-slip fault: Application on the Middle Triassic Monzoni Intrusive Complex (Dolomites, Italy)

NASA Astrophysics Data System (ADS)

Michail, Maria; Coltorti, Massimo; Gianolla, Piero; Riva, Alberto; Rosenau, Matthias; Bonadiman, Costanza; Galland, Olivier; Guldstrand, Frank; Thordén Haug, Øystein; Rudolf, Michael; Schmiedel, Tobias

2017-04-01

The southwestern part of the Dolomites in Northern Italy has undergone a short-lived Ladinian (Middle Triassic) tectono-magmatic event, forming a series of significant magmatic features. These intrusive bodies deformed and metamorphosed the Permo-Triassic carbonate sedimentary framework. In this study we focus on the tectono-magmatic evolution of the shallow shoshonitic Monzoni Intrusive Complex of this Ladinian event (ca 237 Ma), covering an area of 20 km^2. This NW-SE elongated intrusive structure (5 km length) shows an orogenic magmatic affinity which is in contrast to the tectonic regime at the time of intrusion. Strain analysis shows anorogenic transtensional displacement in accordance with the ENE-WSW extensional pattern in the central Dolomites during the Ladinian. Field interpretations led to a detailed description of the regional stratigraphic sequence and the structural features of the study area. However, the geodynamic context of this magmatism and the influence of the inherited strike-slip fault on the intrusion, are still in question. To better understand the specific natural prototype and the general mechanisms of magma emplacement in tectonically active areas, we performed analogue experiments defined by, but not limited to, first order field observations. We have conducted a systematic series of experiments in different tectonic regimes (static conditions, strike-slip, transtension). We varied the ratio of viscous to brittle stresses between magma and country rock, by injecting Newtonian fluids both of high and low viscosity (i.e. silicone oil/vegetable oil) into granular materials of varying cohesion (sand, silica flour, glass beads). The evolving surface and side view of the experiments were monitored by photogrammetric techniques for strain analyses and topographic evolution. In our case, the combination of the results from field and analogue experiments brings new insights regarding the tectonic regime, the geometry of the intrusive body, and the deformational pattern of the evolving system.

Adults' memories of childhood: true and false reports.

PubMed

Qin, Jianjian; Ogle, Christin M; Goodman, Gail S

2008-12-01

In 3 experiments, the authors examined factors that, according to the source-monitoring framework, might influence false memory formation and true/false memory discernment. In Experiment 1, combined effects of warning and visualization on false childhood memory formation were examined, as were individual differences in true and false childhood memories. Combining warnings and visualization led to the lowest false memory and highest true memory. Several individual difference factors (e.g., parental fearful attachment style) predicted false recall. In addition, true and false childhood memories differed (e.g., in amount of information). Experiment 2 examined relations between Deese/Roediger-McDermott task performance and false childhood memories. Deese/Roediger-McDermott performance (e.g., intrusion of unrelated words in free recall) was associated with false childhood memory, suggesting liberal response criteria in source decisions as a common underlying mechanism. Experiment 3 investigated adults' abilities to discern true and false childhood memory reports (e.g., by detecting differences in amount of information as identified in Experiment 1). Adults who were particularly successful in discerning such reports indicated reliance on event plausibility. Overall, the source-monitoring framework provided a viable explanatory framework. Implications for theory and clinical and forensic interviews are discussed. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Development of HIHM (Home Integrated Health Monitor) for ubiquitous home healthcare.

PubMed

Kim, Jung Soo; Kim, Beom Oh; Park, Kwang Suk

2007-01-01

Home Integrated Health Monitor (HIHM) was developed for ubiquitous home healthcare. From quantitative analysis, we have elicited modal of chair. The HIHM could detect Electrocardiogram (ECG) and Photoplethysmography (PPG) non-intrusively. Also, it could estimate blood pressure (BP) non-intrusively, measure blood glucose and ear temperature. Detected signals and information were transmitted to home gateway and home server through Zigbee communication technology. Home server carried them to Healthcare Center, and specialists such as medical doctors could monitor by Internet. There was also feedback system. This device has a potential to study about ubiquitous home healthcare.

Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism

NASA Astrophysics Data System (ADS)

Xu, Haiyan; Xie, Yingjuan; Li, Min; Zhang, Zhuo; Zhang, Xuewu

2017-11-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, an intrusion recognition based on the auditory selective attention mechanism is proposed. Firstly, considering the time-frequency of vibration, the spectrogram is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Based on these maps, the feature matrix is formed after normalization. The system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises. What's more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.

The water supply-water environment nexus in salt Intrusion area under the climate change

NASA Astrophysics Data System (ADS)

Liu, D.

2017-12-01

Water resources are critical problems in in salt Intrusion area for the increasing water supply and water quality deterioration. And the climate change exacerbates these problems. In order to balance the relationship between water supply and water environment requirements, the water supply-water environment nexus should be understood well. Based on the de Saint-Venant system of equations and the convection diffusion equation, which can be used to reflect the laws of water quality, the water supply- water environment nexus equation has be determined. And the nexus is dynamic with the climate change factors. The methods of determined the nexus have then been applied to a case study of the water supply-water environment nexus for the Pearl River Delta in China. The results indicate that the water supply-water environment nexus is trade off each other and are mainly affected by the fresh water flow from the upstream, salt water intrusion will reduce the resilience of the water supply system in this area. Our methods provides a useful framework to quantify the nexus according to the mechanisms of the water quantity and water quality, which will useful freshwater allocation and management in this saltwater intrusion area.

Cross-layer design for intrusion detection and data security in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2007-09-01

A wireless ad hoc sensor network is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. The nodes are severely resource-constrained, with limited processing, memory and power capacities and must operate cooperatively to fulfill a common mission in typically unattended modes. In a wireless sensor network (WSN), each sensor at a node can observe locally some underlying physical phenomenon and sends a quantized version of the observation to sink (destination) nodes via wireless links. Since the wireless medium can be easily eavesdropped, links can be compromised by intrusion attacks from nodes that may mount denial-of-service attacks or insert spurious information into routing packets, leading to routing loops, long timeouts, impersonation, and node exhaustion. A cross-layer design based on protocol-layer interactions is proposed for detection and identification of various intrusion attacks on WSN operation. A feature set is formed from selected cross-layer parameters of the WSN protocol to detect and identify security threats due to intrusion attacks. A separate protocol is not constructed from the cross-layer design; instead, security attributes and quantified trust levels at and among nodes established during data exchanges complement customary WSN metrics of energy usage, reliability, route availability, and end-to-end quality-of-service (QoS) provisioning. Statistical pattern recognition algorithms are applied that use observed feature-set patterns observed during network operations, viewed as security audit logs. These algorithms provide the "best" network global performance in the presence of various intrusion attacks. A set of mobile (software) agents distributed at the nodes implement the algorithms, by moving among the layers involved in the network response at each active node and trust neighborhood, collecting parametric information and executing assigned decision tasks. The communications overhead due to security mechanisms and the latency in network response are thus minimized by reducing the need to move large amounts of audit data through resource-limited nodes and by locating detection/identification programs closer to audit data. If network partitioning occurs due to uncoordinated node exhaustion, data compromise or other effects of the attacks, the mobile agents can continue to operate, thereby increasing fault tolerance in the network response to intrusions. Since the mobile agents behave like an ant colony in securing the WSN, published ant colony optimization (ACO) routines and other evolutionary algorithms are adapted to protect network security, using data at and through nodes to create audit records to detect and respond to denial-of-service attacks. Performance evaluations of algorithms are performed by simulation of a few intrusion attacks, such as black hole, flooding, Sybil and others, to validate the ability of the cross-layer algorithms to enable WSNs to survive the attacks. Results are compared for the different algorithms.

Surveillance for unattended gas compressor stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stastny, F.J.

1974-06-01

Surveillance devices in unattended compressor stations include those which detect trespassing by unauthorized personnel and those which protect the major operating equipment from damage and/or self-destruction. The latter monitor the critical operating parameters of major equipment and shut down the equipment when these parameters are exceeded; a table presents a function monitor and control list for such devices. Detection and apprehension of unauthorized personnel is a subject of increasing importance to guarantee station operability for reliable service and yet minimize staff personnel. An effective intrusion-detection system must (1) pinpoint the location and indicate the nature of the intrusion and (2)more » detect and respond rapidly to give security personnel a reasonable probability of apprehending or deterring the intruder before damage is done. The 2nd requirement is most difficult to satisfy when the facility is in a remote location, as is usually the case. Some of the parameters to consider in selecting an intrusion-detection system include concealment, legality, active vs. passive detector, back-up power, weather conditions, reliability, maintenance, discrimination, and compromising by intruders. Types of detectors include photo cell, infrared and radio frequency, audio,vibration, taut wire, circuit continuity, radar, and closed-circuit TV. The numerous types of devices and systems available provide sufficient diversity to enable a company to select a single device or a hybrid system which would incorporate several different devices for protecting unattended facilities.« less

Non-intrusive ultrasonic liquid-in-line detector for small diameter tubes. [Patent application

DOEpatents

Piper, T.C.

1980-09-24

An arrangement for detecting liquids in a line, using non-intrusive ultrasonic techniques is disclosed. In this arrangement, four piezoelectric crystals are arranged in pairs about a 0.078 inch o.d. pipe. An ultrasonic tone burst is transmitted along the pipe, between crystal pairs, and the amplitude of the received tone burst indicates the absence/presence of liquid in the pipe.

Contrasting catastrophic eruptions predicted by different intrusion and collapse scenarios.

PubMed

Rincón, M; Márquez, A; Herrera, R; Alonso-Torres, A; Granja-Bruña, J L; van Wyk de Vries, B

2018-04-18

Catastrophic volcanic eruptions triggered by landslide collapses can jet upwards or blast sideways. Magma intrusion is related to both landslide-triggered eruptive scenarios (lateral or vertical), but it is not clear how such different responses are produced, nor if any precursor can be used for forecasting them. We approach this problem with physical analogue modelling enhanced with X-ray Multiple Detector Computed Tomography scanning, used to track evolution of internal intrusion, and its related faulting and surface deformation. We find that intrusions produce three different volcano deformation patterns, one of them involving asymmetric intrusion and deformation, with the early development of a listric slump fault producing pronounced slippage of one sector. This previously undescribed early deep potential slip surface provides a unified explanation for the two different eruptive scenarios (lateral vs. vertical). Lateral blast only occurs in flank collapse when the intrusion has risen into the sliding block. Otherwise, vertical rather than lateral expansion of magma is promoted by summit dilatation and flank buttressing. The distinctive surface deformation evolution detected opens the possibility to forecast the possible eruptive scenarios: laterally directed blast should only be expected when surface deformation begins to develop oblique to the first major fault.

Issues in Developing the IFSP: A Framework for Establishing Family Outcomes.

ERIC Educational Resources Information Center

Beckman, Paula J.; Bristol, Marie M.

1991-01-01

This paper identifies four key issues in the implementation of Individualized Family Service Plans (IFSPs) to provide services to young handicapped children as required by Public Law 99-457. These include sensitivity to cultural diversity, family assessment, intrusiveness, and establishing family outcomes. A typology of family outcomes which…

Evaluation of Vehicle Detection Systems for Traffic Signal Operations

DOT National Transportation Integrated Search

2016-10-16

Typical vehicle detection systems used in traffic signal operations are comprised of inductive loop detectors. Because of costs, installation challenges, and operation and maintenance issues, many alternative non-intrusive systems have been dev...

Research on the technology of detecting the SQL injection attack and non-intrusive prevention in WEB system

NASA Astrophysics Data System (ADS)

Hu, Haibin

2017-05-01

Among numerous WEB security issues, SQL injection is the most notable and dangerous. In this study, characteristics and procedures of SQL injection are analyzed, and the method for detecting the SQL injection attack is illustrated. The defense resistance and remedy model of SQL injection attack is established from the perspective of non-intrusive SQL injection attack and defense. Moreover, the ability of resisting the SQL injection attack of the server has been comprehensively improved through the security strategies on operation system, IIS and database, etc.. Corresponding codes are realized. The method is well applied in the actual projects.

Characterizing and Improving Distributed Intrusion Detection Systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hurd, Steven A; Proebstel, Elliot P.

2007-11-01

Due to ever-increasing quantities of information traversing networks, network administrators are developing greater reliance upon statistically sampled packet information as the source for their intrusion detection systems (IDS). Our research is aimed at understanding IDS performance when statistical packet sampling is used. Using the Snort IDS and a variety of data sets, we compared IDS results when an entire data set is used to the results when a statistically sampled subset of the data set is used. Generally speaking, IDS performance with statistically sampled information was shown to drop considerably even under fairly high sampling rates (such as 1:5). Characterizingmore » and Improving Distributed Intrusion Detection Systems4AcknowledgementsThe authors wish to extend our gratitude to Matt Bishop and Chen-Nee Chuah of UC Davis for their guidance and support on this work. Our thanks are also extended to Jianning Mai of UC Davis and Tao Ye of Sprint Advanced Technology Labs for their generous assistance.We would also like to acknowledge our dataset sources, CRAWDAD and CAIDA, without which this work would not have been possible. Support for OC48 data collection is provided by DARPA, NSF, DHS, Cisco and CAIDA members.« less

Weighted link graphs: a distributed IDS for secondary intrusion detection and defense

NASA Astrophysics Data System (ADS)

Zhou, Mian; Lang, Sheau-Dong

2005-03-01

While a firewall installed at the perimeter of a local network provides the first line of defense against the hackers, many intrusion incidents are the results of successful penetration of the firewalls. One computer"s compromise often put the entire network at risk. In this paper, we propose an IDS that provides a finer control over the internal network. The system focuses on the variations of connection-based behavior of each single computer, and uses a weighted link graph to visualize the overall traffic abnormalities. The functionality of our system is of a distributed personal IDS system that also provides a centralized traffic analysis by graphical visualization. We use a novel weight assignment schema for the local detection within each end agent. The local abnormalities are quantitatively carried out by the node weight and link weight and further sent to the central analyzer to build the weighted link graph. Thus, we distribute the burden of traffic processing and visualization to each agent and make it more efficient for the overall intrusion detection. As the LANs are more vulnerable to inside attacks, our system is designed as a reinforcement to prevent corruption from the inside.

Parental insightfulness and parenting behavior: a two-dimensional analysis of parent contributions to child cognitive outcomes.

PubMed

Gomez, Jessie A; Carter, Alice S; Forbes, Danielle; Gray, Sarah A O

2018-06-01

Utilizing a two-dimensional model of parenting emphasizing both (1) proximity seeking and (2) exploration, consistent with a conceptual framework rooted in attachment theory, the relations between parental insightfulness, observed parenting, and child cognitive outcomes were investigated in a low-income sample of 64 of caregivers and their young 3-5-year-old children. Specifically, observed parental sensitivity (proximity seeking) and intrusiveness (exploration) and parental insightfulness assessed dimensionally to capture Positive Insight and Focus on Child were examined in relation to child cognitive outcomes. Parental intrusiveness was negatively correlated with cognitive performance; however, parental sensitivity was not associated with child cognitive outcomes. Parents' capacity to remain child-focused during the Insightfulness Assessment was negatively correlated with observed intrusiveness and was associated with child cognitive performance. These results suggest unique contributions of dimensions of parental insightfulness and parenting behaviors to child cognitive outcomes - specifically, parents' capacity to remain focused on children's experience during the Insightfulness Assessment and nonintrusive parenting behavior, which may reflect strategies to support children's exploration.

Bedrock geologic map of the Grafton quadrangle, Worcester County, Massachusetts

USGS Publications Warehouse

Walsh, Gregory J.; Aleinikoff, John N.; Dorais, Michael J.

2011-01-01

The bedrock geology of the 7.5-minute Grafton, Massachusetts, quadrangle consists of deformed Neoproterozoic to early Paleozoic crystalline metamorphic and intrusive igneous rocks. Neoproterozoic intrusive, metasedimentary, and metavolcanic rocks crop out in the Avalon zone, and Cambrian to Silurian intrusive, metasedimentary, and metavolcanic rocks crop out in the Nashoba zone. Rocks of the Avalon and Nashoba zones, or terranes, are separated by the Bloody Bluff fault. The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing hydrogeologic characterization of the fractured bedrock of Massachusetts. This report presents mapping by G.J. Walsh, geochronology by J.N. Aleinikoff, geochemistry by M.J. Dorais, and consists of a map, text pamphlet, and GIS database. The map and text pamphlet are available in paper format or as downloadable files (see frame at right). The GIS database is available for download. The database includes contacts of bedrock geologic units, faults, outcrops, structural geologic information, and photographs.

Non-intrusive head movement analysis of videotaped seizures of epileptic origin.

PubMed

Mandal, Bappaditya; Eng, How-Lung; Lu, Haiping; Chan, Derrick W S; Ng, Yen-Ling

2012-01-01

In this work we propose a non-intrusive video analytic system for patient's body parts movement analysis in Epilepsy Monitoring Unit. The system utilizes skin color modeling, head/face pose template matching and face detection to analyze and quantify the head movements. Epileptic patients' heads are analyzed holistically to infer seizure and normal random movements. The patient does not require to wear any special clothing, markers or sensors, hence it is totally non-intrusive. The user initializes the person-specific skin color and selects few face/head poses in the initial few frames. The system then tracks the head/face and extracts spatio-temporal features. Support vector machines are then used on these features to classify seizure-like movements from normal random movements. Experiments are performed on numerous long hour video sequences captured in an Epilepsy Monitoring Unit at a local hospital. The results demonstrate the feasibility of the proposed system in pediatric epilepsy monitoring and seizure detection.

Alerts Analysis and Visualization in Network-based Intrusion Detection Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Dr. Li

2010-08-01

The alerts produced by network-based intrusion detection systems, e.g. Snort, can be difficult for network administrators to efficiently review and respond to due to the enormous number of alerts generated in a short time frame. This work describes how the visualization of raw IDS alert data assists network administrators in understanding the current state of a network and quickens the process of reviewing and responding to intrusion attempts. The project presented in this work consists of three primary components. The first component provides a visual mapping of the network topology that allows the end-user to easily browse clustered alerts. Themore » second component is based on the flocking behavior of birds such that birds tend to follow other birds with similar behaviors. This component allows the end-user to see the clustering process and provides an efficient means for reviewing alert data. The third component discovers and visualizes patterns of multistage attacks by profiling the attacker s behaviors.« less

Non-intrusive appliance monitor apparatus

DOEpatents

Hart, George W.; Kern, Jr., Edward C.; Schweppe, Fred C.

1989-08-15

A non-intrusive monitor of energy consumption of residential appliances is described in which sensors, coupled to the power circuits entering a residence, supply analog voltage and current signals which are converted to digital format and processed to detect changes in certain residential load parameters, i.e., admittance. Cluster analysis techniques are employed to group change measurements into certain categories, and logic is applied to identify individual appliances and the energy consumed by each.

Successional trends in Sonoran Desert abandoned agricultural fields in northern Mexico

USGS Publications Warehouse

Castellanos, A.E.; Martinez, M.J.; Llano, J.M.; Halvorson, W.L.; Espiricueta, M.; Espejel, I.

2005-01-01

Excessive ground-water use and saline intrusion to the aquifer led, in less than three decades, to an increase in abandoned agricultural fields at La Costa de Hermosillo, within the Sonoran Desert. Using a chronosequence from years since abandonment, patterns of field succession were developed. Contrary to most desert literature, species replacement was found, both in fields with and without saline intrusion. Seasonal photosynthetic capacity as well as water and nitrogen use efficiencies were different in dominant early and late successional plant species. These ecological findings provided a framework for a general explanation of species dominance and replacement within abandoned agricultural fields in the Sonoran Desert. ?? 2004 Elsevier Ltd. All rights reserved.

Evaluation of Flow Paths and Confluences for Saltwater Intrusion and Its Influence on Fish Species Diversity in a Deltaic River Network

NASA Astrophysics Data System (ADS)

Shao, X.; Cui, B.; Zhang, Z.; Fang, Y.; Jawitz, J. W.

2016-12-01

Freshwater in a delta is often at risk of saltwater intrusion, which has been a serious issue in estuarine deltas all over the world. Salinity gradients and hydrologic connectivity in the deltas can be disturbed by saltwater intrusion, which can fluctuate frequently and locally in time and space to affect biotic processes and then to affect the distribution patterns of the riverine fishes throughout the river network. Therefore, identifying the major flow paths or locations at risk of saltwater intrusion in estuarine ecosystems is necessary for saltwater intrusion mitigation and fish species diversity conservation. In this study, we use the betweenness centrality (BC) as the weighted attribute of the river network to identify the critical confluences and detect the preferential flow paths for saltwater intrusion through the least-cost-path algorithm from graph theory approach. Moreover, we analyse the responses of the salinity and fish species diversity to the BC values of confluences calculated in the river network. Our results show that the most likely location of saltwater intrusion is not a simple gradient change from sea to land, but closely dependent on the river segments' characteristics. In addition, a significant positive correlation between the salinity and the BC values of confluences is determined in the Pearl River Delta. Changes in the BC values of confluences can produce significant variation in the fish species diversity. Therefore, the dynamics of saltwater intrusion are a growing consideration for understanding the patterns and subsequent processes driving fish community structure. Freshwater can be diverted into these major flow paths and critical confluences to improve river network management and conservation of fish species diversity under saltwater intrusion.

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

NASA Astrophysics Data System (ADS)

Rustam, Z.; Talita, A. S.

2017-07-01

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the security of information systems. IDS can be used to detect the abuse by intruders who try to get into the network system in order to access and utilize the available data sources in the system. There are two approaches of IDS, Misuse Detection and Anomaly Detection (behavior-based intrusion detection). Fuzzy clustering-based methods have been widely used to solve Anomaly Detection problems. Other than using fuzzy membership concept to determine the object to a cluster, other approaches as in combining fuzzy and possibilistic membership or feature-weighted based methods are also used. We propose Fuzzy Kernel k-Medoids that combining fuzzy and possibilistic membership as a powerful method to solve anomaly detection problem since on numerical experiment it is able to classify IDS benchmark data into five different classes simultaneously. We classify IDS benchmark data KDDCup'99 data set into five different classes simultaneously with the best performance was achieved by using 30 % of training data with clustering accuracy reached 90.28 percent.

Modal Composition and Age of Intrusions in North-Central and Northeast Nevada

USGS Publications Warehouse

du Bray, Edward A.; Crafford, A. Elizabeth Jones

2007-01-01

Introduction Data presented in this report characterize igneous intrusions of north-central and northeast Nevada and were compiled as part of the Metallogeny of the Great Basin project conducted by the U.S. Geological Survey (USGS) between 2001 and 2007. The compilation pertains to the area bounded by lats 38.5 and 42 N., long 118.5 W., and the Nevada-Utah border (fig. 1). The area contains numerous large plutons and smaller stocks but also contains equally numerous smaller, shallowly emplaced intrusions, including dikes, sills, and endogenous dome complexes. Igneous intrusions (hereafter, intrusions) of multiple ages are major constituents of the geologic framework of north-central and northeast Nevada (Stewart and Carlson, 1978). Mesozoic and Cenozoic intrusions are particularly numerous and considered to be related to subduction along the west edge of the North American plate during this time. Henry and Ressel (2000) and Ressel and others (2000) have highlighted the association between magmatism and ore deposits along the Carlin trend. Similarly, Theodore (2000) has demonstrated the association between intrusions and ore deposits in the Battle Mountain area. Decades of geologic investigations in north-central and northeast Nevada (hereafter, the study area) demonstrate that most hydrothermal ore deposits are spatially, and probably temporally and genetically, associated with intrusions. Because of these associations, studies of many individual intrusions have been conducted, including those by a large number of Master's and Doctoral thesis students (particularly University of Nevada at Reno students and associated faculty), economic geologists working on behalf of exploration and mining companies, and USGS earth scientists. Although the volume of study area intrusions is large and many are associated with ore deposits, no synthesis of available data that characterize these rocks has been assembled. Compilations that have been produced for intrusions in Nevada pertain to relatively restricted geographic areas and (or) do not include the broad array of data that would best aid interpretation of these rocks. For example, Smith and others (1971) presented potassium-argon geochronologic and basic petrographic data for a limited number of intrusions in northcentral Nevada. Similarly, Silberman and McKee (1971) presented potassium-argon geochronologic data for a significant number of central Nevada intrusions. More recently, Mortensen and others (2000) presented uranium-lead geochronology for a small number of central Nevada intrusions. Sloan and others (2003) released a national geochronologic database that contains age determinations made prior to 1991 for rocks of Nevada. Finally, C.D. Henry (Nevada Bureau of Mines and Geology, written commun., 2006) has assembled geochronologic data for igneous rocks of Nevada produced subsequent to completion of the Sloan and others (2003) compilation. Consequently, although age data for igneous rocks of Nevada have been compiled, data pertaining to other features of these rocks have not been systematically synthesized. Maldonado and others (1988) compiled the distribution and some basic characteristics of intrusions throughout Nevada. Lee (1984), John (1983, 1987, and 1992), John and others (1994), and Ressel (2005) have compiled data that partially characterize intrusions in some parts of the study area. This report documents the first phase of an effort to compile a robust database for study area intrusions; in this initial phase, modal composition and age data are synthesized. In the next phase, geochemical data available for these rocks will be compiled. The ultimate goal is to compile data as a basis for an evaluation of the time-space-compositional evolution of Mesozoic and Cenozoic magmatism in the study area and identification of genetic associations between magmatism and mineralizing processes in this region.

Improvements to video imaging detection for dilemma zone protection.

DOT National Transportation Integrated Search

2009-02-01

The use of video imaging vehicle detection systems (VIVDS) at signalized intersections in Texas has : increased significantly due primarily to safety issues and costs. Installing non-intrusive detectors at : intersections is almost always safer than ...

DETECTION OR WARNING SYSTEM

DOEpatents

Tillman, J E

1953-10-20

This patent application describes a sensitive detection or protective system capable of giving an alarm or warning upon the entrance or intrusion of any body into a defined area or zone protected by a radiation field of suitable direction or extent.

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

PubMed

Kang, Min-Joo; Kang, Je-Won

2016-01-01

A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus.

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security

PubMed Central

Kang, Min-Joo

2016-01-01

A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus. PMID:27271802

Usefulness of DARPA dataset for intrusion detection system evaluation

NASA Astrophysics Data System (ADS)

Thomas, Ciza; Sharma, Vishwas; Balakrishnan, N.

2008-03-01

The MIT Lincoln Laboratory IDS evaluation methodology is a practical solution in terms of evaluating the performance of Intrusion Detection Systems, which has contributed tremendously to the research progress in that field. The DARPA IDS evaluation dataset has been criticized and considered by many as a very outdated dataset, unable to accommodate the latest trend in attacks. Then naturally the question arises as to whether the detection systems have improved beyond detecting these old level of attacks. If not, is it worth thinking of this dataset as obsolete? The paper presented here tries to provide supporting facts for the use of the DARPA IDS evaluation dataset. The two commonly used signature-based IDSs, Snort and Cisco IDS, and two anomaly detectors, the PHAD and the ALAD, are made use of for this evaluation purpose and the results support the usefulness of DARPA dataset for IDS evaluation.

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PubMed

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

Intrusion-Tolerant Location Information Services in Intelligent Vehicular Networks

NASA Astrophysics Data System (ADS)

Yan, Gongjun; Yang, Weiming; Shaner, Earl F.; Rawat, Danda B.

Intelligent Vehicular Networks, known as Vehicle-to-Vehicle and Vehicle-to-Roadside wireless communications (also called Vehicular Ad hoc Networks), are revolutionizing our daily driving with better safety and more infortainment. Most, if not all, applications will depend on accurate location information. Thus, it is of importance to provide intrusion-tolerant location information services. In this paper, we describe an adaptive algorithm that detects and filters the false location information injected by intruders. Given a noisy environment of mobile vehicles, the algorithm estimates the high resolution location of a vehicle by refining low resolution location input. We also investigate results of simulations and evaluate the quality of the intrusion-tolerant location service.

Preventing intrusive memories after trauma via a brief intervention involving Tetris computer game play in the emergency department: a proof-of-concept randomized controlled trial

PubMed Central

Iyadurai, L; Blackwell, S E; Meiser-Stedman, R; Watson, P C; Bonsall, M B; Geddes, J R; Nobre, A C; Holmes, E A

2018-01-01

After psychological trauma, recurrent intrusive visual memories may be distressing and disruptive. Preventive interventions post trauma are lacking. Here we test a behavioural intervention after real-life trauma derived from cognitive neuroscience. We hypothesized that intrusive memories would be significantly reduced in number by an intervention involving a computer game with high visuospatial demands (Tetris), via disrupting consolidation of sensory elements of trauma memory. The Tetris-based intervention (trauma memory reminder cue plus c. 20 min game play) vs attention-placebo control (written activity log for same duration) were both delivered in an emergency department within 6 h of a motor vehicle accident. The randomized controlled trial compared the impact on the number of intrusive trauma memories in the subsequent week (primary outcome). Results vindicated the efficacy of the Tetris-based intervention compared with the control condition: there were fewer intrusive memories overall, and time-series analyses showed that intrusion incidence declined more quickly. There were convergent findings on a measure of clinical post-trauma intrusion symptoms at 1 week, but not on other symptom clusters or at 1 month. Results of this proof-of-concept study suggest that a larger trial, powered to detect differences at 1 month, is warranted. Participants found the intervention easy, helpful and minimally distressing. By translating emerging neuroscientific insights and experimental research into the real world, we offer a promising new low-intensity psychiatric intervention that could prevent debilitating intrusive memories following trauma. PMID:28348380

Detection System of the First Rapidly Relocatable Tagged Neutron Inspection System (RRTNIS), Developed in the Framework of the European H2020 C-BORD Project

NASA Astrophysics Data System (ADS)

Fontana, Cristiano Lino; Carnera, Alberto; Lunardon, Marcello; Pino, Felix; Sada, Cinzia; Soramel, Francesca; Stevanato, Luca; Nebbia, Giancarlo; Carasco, Cédric; Perot, Bertrand; Sardet, Alix; Sannie, Guillaume; Iovene, Alessandro; Tintori, Carlo; Grodzicki, Krystian; Moszyński, Marek; Sibczyński, Paweł; Swiderski, Lukasz; Moretto, Sandra

The European project entitled ;effective Container inspection at BORDer control points; (C-BORD) focuses on the development and in-situ tests of a comprehensive cost-effective solution for the generalized Non-Intrusive Inspection (NII) of containers and large-volume freight at the European Union (EU) border. It copes with a large range of targets, including explosives, chemical warfare agents, illicit drugs, tobacco and Special Nuclear Materials. Within the C-BORD project, a new generation of Tagged Neutron Inspection System (TNIS) for cargo containers is foreseen. Unlike its predecessors, this system would be the first Rapidly Relocatable TNIS (RRTNIS). It will be a second-line defense system, to be used on sealed containers in order to detect explosives, illicit drugs and chemical agents in a suspect voxel (elementary volume unit). We report on the status of the RRTNIS system, in particular the overall design, the characterization of the large-volume NaI(Tl) gamma detectors, the digital analysis of the time measurements and the Data Acquisition System (DAQ).

Magnetic fabric constraints of the emplacement of igneous intrusions

NASA Astrophysics Data System (ADS)

Maes, Stephanie M.

Fabric analysis is critical to evaluating the history, kinematics, and dynamics of geological deformation. This is particularly true of igneous intrusions, where the development of fabric is used to constrain magmatic flow and emplacement mechanisms. Fabric analysis was applied to three mafic intrusions, with different tectonic and petrogenetic histories, to study emplacement and magma flow: the Insizwa sill (Mesozoic Karoo Large Igneous Province, South Africa), Sonju Lake intrusion (Proterozoic Midcontinent Rift, Minnesota, USA), and Palisades sill (Mesozoic rift basin, New Jersey, USA). Multiple fabric analysis techniques were used to define the fabric in each intrusive body. Using digital image analysis techniques on multiple thin sections, the three-dimensional shape-preferred orientation (SPO) of populations of mineral phases were calculated. Low-field anisotropy of magnetic susceptibility (AMS) measurements were used as a proxy for the mineral fabric of the ferromagnetic phases (e.g., magnetite). In addition, a new technique---high-field AMS---was used to isolate the paramagnetic component of the fabric (e.g., silicate fabric). Each fabric analysis technique was then compared to observable field fabrics as a framework for interpretation. In the Insizwa sill, magnetic properties were used to corroborate vertical petrologic zonation and distinguish sub-units within lithologically defined units. Abrupt variation in magnetic properties provides evidence supporting the formation of the Insizwa sill by separate magma intrusions. Low-field AMS fabrics in the Sonju Lake intrusion exhibit consistent SW-plunging lineations and SW-dipping foliations. These fabric orientations provide evidence that the cumulate layers in the intrusion were deposited in a dynamic environment, and indicate magma flowed from southwest to northeast, parallel to the pre-existing rift structures. In the Palisades sill, the magnetite SPO and low-field AMS lineation have developed orthogonal to the plagioclase SPO and high-field AMS lineation. Magma flow in the Palisades magmatic system is interpreted to have originated from a point source feeder. Low-field AMS records the flow direction, whereas high-field AMS records extension within the igneous sheet. The multiple fabric analysis techniques presented in this dissertation have advanced our understanding of the development of fabric and its relationship to internal structure, emplacement, and magma dynamics in mafic igneous systems.

Volumetric Security Alarm Based on a Spherical Ultrasonic Transducer Array

NASA Astrophysics Data System (ADS)

Sayin, Umut; Scaini, Davide; Arteaga, Daniel

Most of the existent alarm systems depend on physical or visual contact. The detection area is often limited depending on the type of the transducer, creating blind spots. Our proposition is a truly volumetric alarm system that can detect any movement in the intrusion area, based on monitoring the change over time of the impulse response of the room, which acts as an acoustic footprint. The device depends on an omnidirectional ultrasonic transducer array emitting sweep signals to calculate the impulse response in short intervals. Any change in the room conditions is monitored through a correlation function. The sensitivity of the alarm to different objects and different environments depends on the sweep duration, sweep bandwidth, and sweep interval. Successful detection of intrusions also depends on the size of the monitoring area and requires an adjustment of emitted ultrasound power. Strong air flow affects the performance of the alarm. A method for separating moving objects from strong air flow is devised using an adaptive thresholding on the correlation function involving a series of impulse response measurements. The alarm system can be also used for fire detection since air flow sourced from heating objects differ from random nature of the present air flow. Several measurements are made to test the integrity of the alarm in rooms sizing from 834-2080m3 with irregular geometries and various objects. The proposed system can efficiently detect intrusion whilst adequate emitting power is provided.

Non-intrusive appliance monitor apparatus

DOEpatents

Hart, G.W.; Kern, E.C. Jr.; Schweppe, F.C.

1989-08-15

A non-intrusive monitor of energy consumption of residential appliances is described in which sensors, coupled to the power circuits entering a residence, supply analog voltage and current signals which are converted to digital format and processed to detect changes in certain residential load parameters, i.e., admittance. Cluster analysis techniques are employed to group change measurements into certain categories, and logic is applied to identify individual appliances and the energy consumed by each. 9 figs.

Magma transport in sheet intrusions of the Alnö carbonatite complex, central Sweden.

PubMed

Andersson, Magnus; Almqvist, Bjarne S G; Burchardt, Steffi; Troll, Valentin R; Malehmir, Alireza; Snowball, Ian; Kübler, Lutz

2016-06-10

Magma transport through the Earth's crust occurs dominantly via sheet intrusions, such as dykes and cone-sheets, and is fundamental to crustal evolution, volcanic eruptions and geochemical element cycling. However, reliable methods to reconstruct flow direction in solidified sheet intrusions have proved elusive. Anisotropy of magnetic susceptibility (AMS) in magmatic sheets is often interpreted as primary magma flow, but magnetic fabrics can be modified by post-emplacement processes, making interpretation of AMS data ambiguous. Here we present AMS data from cone-sheets in the Alnö carbonatite complex, central Sweden. We discuss six scenarios of syn- and post-emplacement processes that can modify AMS fabrics and offer a conceptual framework for systematic interpretation of magma movements in sheet intrusions. The AMS fabrics in the Alnö cone-sheets are dominantly oblate with magnetic foliations parallel to sheet orientations. These fabrics may result from primary lateral flow or from sheet closure at the terminal stage of magma transport. As the cone-sheets are discontinuous along their strike direction, sheet closure is the most probable process to explain the observed AMS fabrics. We argue that these fabrics may be common to cone-sheets and an integrated geology, petrology and AMS approach can be used to distinguish them from primary flow fabrics.

Mechanism of the 1996-97 non-eruptive volcano-tectonic earthquake swarm at Iliamna Volcano, Alaska

USGS Publications Warehouse

Roman, D.C.; Power, J.A.

2011-01-01

A significant number of volcano-tectonic(VT) earthquake swarms, some of which are accompanied by ground deformation and/or volcanic gas emissions, do not culminate in an eruption.These swarms are often thought to represent stalled intrusions of magma into the mid- or shallow-level crust.Real-time assessment of the likelihood that a VTswarm will culminate in an eruption is one of the key challenges of volcano monitoring, and retrospective analysis of non-eruptive swarms provides an important framework for future assessments. Here we explore models for a non-eruptive VT earthquake swarm located beneath Iliamna Volcano, Alaska, in May 1996-June 1997 through calculation and inversion of fault-plane solutions for swarm and background periods, and through Coulomb stress modeling of faulting types and hypocenter locations observed during the swarm. Through a comparison of models of deep and shallow intrusions to swarm observations,we aim to test the hypothesis that the 1996-97 swarm represented a shallow intrusion, or "failed" eruption.Observations of the 1996-97 swarm are found to be consistent with several scenarios including both shallow and deep intrusion, most likely involving a relatively small volume of intruded magma and/or a low degree of magma pressurization corresponding to a relatively low likelihood of eruption. ?? 2011 Springer-Verlag.

Magma transport in sheet intrusions of the Alnö carbonatite complex, central Sweden

PubMed Central

Andersson, Magnus; Almqvist, Bjarne S. G.; Burchardt, Steffi; Troll, Valentin R.; Malehmir, Alireza; Snowball, Ian; Kübler, Lutz

2016-01-01

Magma transport through the Earth’s crust occurs dominantly via sheet intrusions, such as dykes and cone-sheets, and is fundamental to crustal evolution, volcanic eruptions and geochemical element cycling. However, reliable methods to reconstruct flow direction in solidified sheet intrusions have proved elusive. Anisotropy of magnetic susceptibility (AMS) in magmatic sheets is often interpreted as primary magma flow, but magnetic fabrics can be modified by post-emplacement processes, making interpretation of AMS data ambiguous. Here we present AMS data from cone-sheets in the Alnö carbonatite complex, central Sweden. We discuss six scenarios of syn- and post-emplacement processes that can modify AMS fabrics and offer a conceptual framework for systematic interpretation of magma movements in sheet intrusions. The AMS fabrics in the Alnö cone-sheets are dominantly oblate with magnetic foliations parallel to sheet orientations. These fabrics may result from primary lateral flow or from sheet closure at the terminal stage of magma transport. As the cone-sheets are discontinuous along their strike direction, sheet closure is the most probable process to explain the observed AMS fabrics. We argue that these fabrics may be common to cone-sheets and an integrated geology, petrology and AMS approach can be used to distinguish them from primary flow fabrics. PMID:27282420

Automated Network Anomaly Detection with Learning, Control and Mitigation

ERIC Educational Resources Information Center

Ippoliti, Dennis

2014-01-01

Anomaly detection is a challenging problem that has been researched within a variety of application domains. In network intrusion detection, anomaly based techniques are particularly attractive because of their ability to identify previously unknown attacks without the need to be programmed with the specific signatures of every possible attack.…

New Non-Intrusive Inspection Technologies for Nuclear Security and Nonproliferation

NASA Astrophysics Data System (ADS)

Ledoux, Robert J.

2015-10-01

Comprehensive monitoring of the supply chain for nuclear materials has historically been hampered by non-intrusive inspection systems that have such large false alarm rates that they are impractical in the flow of commerce. Passport Systems, Inc. (Passport) has developed an active interrogation system which detects fissionable material, high Z material, and other contraband in land, sea and air cargo. Passport's design utilizes several detection modalities including high resolution imaging, passive radiation detection, effective-Z (EZ-3D™) anomaly detection, Prompt Neutrons from Photofission (PNPF), and Nuclear Resonance Fluorescence (NRF) isotopic identification. These technologies combine to: detect fissionable, high-Z, radioactive and contraband materials, differentiate fissionable materials from high-Z shielding materials, and isotopically identify actinides, Special Nuclear Materials (SNM), and other contraband (e.g. explosives, drugs, nerve agents). Passport's system generates a 3-D image of the scanned object which contains information such as effective-Z and density, as well as a 2-D image and isotopic and fissionable information for regions of interest.

The domain interface method: a general-purpose non-intrusive technique for non-conforming domain decomposition problems

NASA Astrophysics Data System (ADS)

Cafiero, M.; Lloberas-Valls, O.; Cante, J.; Oliver, J.

2016-04-01

A domain decomposition technique is proposed which is capable of properly connecting arbitrary non-conforming interfaces. The strategy essentially consists in considering a fictitious zero-width interface between the non-matching meshes which is discretized using a Delaunay triangulation. Continuity is satisfied across domains through normal and tangential stresses provided by the discretized interface and inserted in the formulation in the form of Lagrange multipliers. The final structure of the global system of equations resembles the dual assembly of substructures where the Lagrange multipliers are employed to nullify the gap between domains. A new approach to handle floating subdomains is outlined which can be implemented without significantly altering the structure of standard industrial finite element codes. The effectiveness of the developed algorithm is demonstrated through a patch test example and a number of tests that highlight the accuracy of the methodology and independence of the results with respect to the framework parameters. Considering its high degree of flexibility and non-intrusive character, the proposed domain decomposition framework is regarded as an attractive alternative to other established techniques such as the mortar approach.

33 CFR 105.260 - Security measures for restricted areas.

Code of Federal Regulations, 2010 CFR

2010-07-01

...; (7) Control the entry, parking, loading and unloading of vehicles; (8) Control the movement and...) Using security personnel, automatic intrusion detection devices, surveillance equipment, or surveillance systems to detect unauthorized entry or movement within restricted areas; (7) Directing the parking...

33 CFR 105.260 - Security measures for restricted areas.

Code of Federal Regulations, 2011 CFR

2011-07-01

...; (7) Control the entry, parking, loading and unloading of vehicles; (8) Control the movement and...) Using security personnel, automatic intrusion detection devices, surveillance equipment, or surveillance systems to detect unauthorized entry or movement within restricted areas; (7) Directing the parking...

On the occurrence, the characterization and the dynamical processes associated with FrIAC's (Frozen In Anticyclones) events

NASA Astrophysics Data System (ADS)

Thiéblemont, R.; Huret, N.; Orsolini, Y.; Hauchecorne, A.; Drouin, M.

2010-12-01

During winter, the polar vortex forms in arctic stratosphere a dynamical barrier which prevents large scale exchanges between high latitude and tropical regions. However, thin tropical air mass intrusions at the edge of the polar vortex have already been detected and modelled. These structures could play an important role for the knowledge of the balance between chemistry and dynamical processes associated with ozone budget. During springtime, after the final stratospheric warming, the breakdown of the polar vortex occurs and the summer circulation starts to develop. Air mass intrusions from the tropics can be trapped into the polar latitudes in an anticyclone which can persist until August, advected by summer easterlies. These structures, named “Frozen In Anticyclones” (FrIAC’s), have already been observed in 2003 and 2005 by MIPAS-ENVISAT and MLS-AURA instruments. We present here a new case of FrIAC in 2007 highlighted using MLS-AURA measurements. Time evolution of N2O and H2O mixing ratios in the core of this FRIAC are compared with the 2005 similar event. In addition, we perform a climatology of tropical air mass intrusions during the last decade based on the results of the potential vorticity contour advection model MIMOSA (Hauchecorne et al., 2002) and MLS-AURA measurements. This climatology reveals a favourite path for exchanges between polar and tropical stratosphere allowing us to establish closed links between FrIAC’s occurrence and Rossby wave activity. Using wind and temperature fields from ECMWF, we performed a study to understand dynamical processes responsible of such dynamical structures. Discussion on the link between them and Sudden Stratospheric Warming, Final Stratsopheric Warming and Quasi Biennal Oscillation will be presented. This study is made in the framework the STRAPOLETE project which has started on January 2009 to study the Arctic stratosphere in the summertime.

Automated Virtual Machine Introspection for Host-Based Intrusion Detection

DTIC Science & Technology

2009-03-01

boxes represent the code and data sections of each process in memory with arrows representing hooks planted by malware to jump to the malware code...a useful indication of intrusion, it is also susceptible to mimicry and concurrency attacks [Pro03,Wat07]. Additionally, most research abstracts away...sequence of system calls that accomplishes his or her intent [WS02]. This “ mimicry attack” takes advantage of the fact that many HIDS discard the pa

Documentation for the MODFLOW 6 framework

USGS Publications Warehouse

Hughes, Joseph D.; Langevin, Christian D.; Banta, Edward R.

2017-08-10

MODFLOW is a popular open-source groundwater flow model distributed by the U.S. Geological Survey. Growing interest in surface and groundwater interactions, local refinement with nested and unstructured grids, karst groundwater flow, solute transport, and saltwater intrusion, has led to the development of numerous MODFLOW versions. Often times, there are incompatibilities between these different MODFLOW versions. The report describes a new MODFLOW framework called MODFLOW 6 that is designed to support multiple models and multiple types of models. The framework is written in Fortran using a modular object-oriented design. The primary framework components include the simulation (or main program), Timing Module, Solutions, Models, Exchanges, and Utilities. The first version of the framework focuses on numerical solutions, numerical models, and numerical exchanges. This focus on numerical models allows multiple numerical models to be tightly coupled at the matrix level.

Do you see what I hear: experiments in multi-channel sound and 3D visualization for network monitoring?

NASA Astrophysics Data System (ADS)

Ballora, Mark; Hall, David L.

2010-04-01

Detection of intrusions is a continuing problem in network security. Due to the large volumes of data recorded in Web server logs, analysis is typically forensic, taking place only after a problem has occurred. This paper describes a novel method of representing Web log information through multi-channel sound, while simultaneously visualizing network activity using a 3-D immersive environment. We are exploring the detection of intrusion signatures and patterns, utilizing human aural and visual pattern recognition ability to detect intrusions as they occur. IP addresses and return codes are mapped to an informative and unobtrusive listening environment to act as a situational sound track of Web traffic. Web log data is parsed and formatted using Python, then read as a data array by the synthesis language SuperCollider [1], which renders it as a sonification. This can be done either for the study of pre-existing data sets or in monitoring Web traffic in real time. Components rendered aurally include IP address, geographical information, and server Return Codes. Users can interact with the data, speeding or slowing the speed of representation (for pre-existing data sets) or "mixing" sound components to optimize intelligibility for tracking suspicious activity.

Non-intrusive optical study of gas and its exchange in human maxillary sinuses

NASA Astrophysics Data System (ADS)

Persson, L.; Andersson, M.; Svensson, T.; Cassel-Engquist, M.; Svanberg, K.; Svanberg, S.

2007-07-01

We demonstrate a novel non-intrusive technique based on tunable diode laser absorption spectroscopy to investigate human maxillary sinuses in vivo. The technique relies on the fact that free gases have much sharper absorption features (typical a few GHz) than the surrounding tissue. Molecular oxygen was detected at 760 nm. Volunteers have been investigated by injecting near-infrared light fibre-optically in contact with the palate inside the mouth. The multiply scattered light was detected externally by a handheld probe on and around the cheek bone. A significant signal difference in oxygen imprint was observed when comparing volunteers with widely different anamnesis regarding maxillary sinus status. Control measurements through the hand and through the cheek below the cheekbone were also performed to investigate any possible oxygen offset in the setup. These provided a consistently non-detectable signal level. The passages between the nasal cavity and the maxillary sinuses were also non-intrusively optically studied, to the best of our knowledge for the first time. These measurements provide information on the channel conductivity which may prove useful in facial sinus diagnostics. The results suggest that a clinical trial together with an ear-nose-throat (ENT) clinic should be carried out to investigate the clinical use of the new technique.

Dynamics of large-diameter water pipes in hydroelectric power plants

NASA Astrophysics Data System (ADS)

Pavić, G.; Chevillotte, F.; Heraud, J.

2017-04-01

An outline is made of physical behaviour of water - filled large pipes. The fluid-wall coupling, the key factor governing the pipe dynamics, is discussed in some detail. Different circumferential pipe modes and the associated cut-on frequencies are addressed from a theoretical as well as practical point of view. Major attention is paid to the breathing mode in view of its importance regarding main dynamic phenomena, such as water hammer. Selected measurement results done at EDF are presented to demonstrate how an external, non-intrusive sensor can detect pressure pulsations of the breathing mode in a pressure pipe. Differences in the pressure measurement using intrusive and non-intrusive sensors reveal the full complexity of large-diameter pipe dynamics.

Robotic guarded motion system and method

DOEpatents

Bruemmer, David J.

2010-02-23

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes instructions for repeating, on each iteration through an event timing loop, the acts of defining an event horizon, detecting a range to obstacles around the robot, and testing for an event horizon intrusion. Defining the event horizon includes determining a distance from the robot that is proportional to a current velocity of the robot and testing for the event horizon intrusion includes determining if any range to the obstacles is within the event horizon. Finally, on each iteration through the event timing loop, the method includes reducing the current velocity of the robot in proportion to a loop period of the event timing loop if the event horizon intrusion occurs.

Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

PubMed Central

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

Geophysical Evidence for Magma Intrusion across the Non-Transform Offset between the Famous and North Famous segments of The Mid-Atlantic Ridge

NASA Astrophysics Data System (ADS)

Giusti, M.; Dziak, R. P.; Maia, M.; Perrot, J.; Sukhovich, A.

2017-12-01

In August of 2010 an unusually large earthquake sequence of >700 events occurred at the Famous and North Famous segments (36.5-37°N) of the Mid-Atlantic Ridge (MAR), recorded by an array of five hydrophones moored on the MAR flanks. The swarm extended spatially >70 km across the two segments. The non-transform offset (NTO) separating the two segements, which is thought to act as strucutural barrier, did not appear to impede or block the earthquake's spatial distribution. Broadband acoustic energy (1-30 Hz) was also observed and accompanied the onset of the swarm, lasting >20 hours. A total of 18 earthquakes from the swarm were detected teleseismically, four had Centroid-Moment Tensor (CMT) solutions derived. The CMT solutions indicated three normal faulting events, and one non-double couple (explosion) event. The spatio-temporal distribution of the seismicity and broadband energy show evidence of two magma dike intrusions at the North Famous segment, with one intrusion crossing the NTO. This is the first evidence for an intrusion event detected on the MAR south of the Azores since the 2001 Lucky Strike intrusion. Gravimetric data were required to identify whether or not the Famous area is indeed comprised of two segments down to the level of the upper mantle. A high resolution gravity anomaly map of the two segments has been realized, based on a two-dimensional polygons model (Chapman, 1979) and will be compared to gravimetric data originated from SUDACORES experiment (1998, Atalante ship, IFREMER research team). Combined with the earthquake observations, this gravity anomaly map should provide a better understanding the geodynamic processes of this non-transform offset and of the deep magmatic system driving the August 2010 swarm.

Multi-User Low Intrusive Occupancy Detection

PubMed Central

Widyawan, Widyawan; Lazovik, Alexander

2018-01-01

Smart spaces are those that are aware of their state and can act accordingly. Among the central elements of such a state is the presence of humans and their number. For a smart office building, such information can be used for saving energy and safety purposes. While acquiring presence information is crucial, using sensing techniques that are highly intrusive, such as cameras, is often not acceptable for the building occupants. In this paper, we illustrate a proposal for occupancy detection which is low intrusive; it is based on equipment typically available in modern offices such as room-level power-metering and an app running on workers’ mobile phones. For power metering, we collect the aggregated power consumption and disaggregate the load of each device. For the mobile phone, we use the Received Signal Strength (RSS) of BLE (Bluetooth Low Energy) nodes deployed around workspaces to localize the phone in a room. We test the system in our offices. The experiments show that sensor fusion of the two sensing modalities gives 87–90% accuracy, demonstrating the effectiveness of the proposed approach. PMID:29509693

Application of the PageRank Algorithm to Alarm Graphs

NASA Astrophysics Data System (ADS)

Treinen, James J.; Thurimella, Ramakrishna

The task of separating genuine attacks from false alarms in large intrusion detection infrastructures is extremely difficult. The number of alarms received in such environments can easily enter into the millions of alerts per day. The overwhelming noise created by these alarms can cause genuine attacks to go unnoticed. As means of highlighting these attacks, we introduce a host ranking technique utilizing Alarm Graphs. Rather than enumerate all potential attack paths as in Attack Graphs, we build and analyze graphs based on the alarms generated by the intrusion detection sensors installed on a network. Given that the alarms are predominantly false positives, the challenge is to identify, separate, and ideally predict future attacks. In this paper, we propose a novel approach to tackle this problem based on the PageRank algorithm. By elevating the rank of known attackers and victims we are able to observe the effect that these hosts have on the other nodes in the Alarm Graph. Using this information we are able to discover previously overlooked attacks, as well as defend against future intrusions.

X-Ray Scan Detection for Cargo Integrity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valencia, Juan D.; Miller, Steven D.

ABSTRACT The increase of terrorism and its global impact has made the determination of the contents of cargo containers a necessity. Existing technology allows non-intrusive inspections to determine the contents of a container rapidly and accurately. However, some cargo shipments are exempt from such inspections. Hence, there is a need for a technology that enables rapid and accurate means of detecting whether such containers were non-intrusively inspected. Non-intrusive inspections are most commonly performed utilizing high powered X-ray equipment. The challenge is creating a device that can detect short duration X-ray scans while maintaining a portable, battery powered, low cost, andmore » easy to use platform. The Pacific Northwest National Laboratory (PNNL) has developed a methodology and prototype device focused on this challenge. The prototype, developed by PNNL, is a battery powered electronic device that continuously measures its X-ray and Gamma exposure, calculates the dose equivalent rate, and makes a determination of whether the device has been exposed to the amount of radiation experienced during an X-ray inspection. Once an inspection is detected, the device will record a timestamp of the event and relay the information to authorized personnel via a visual alert, USB connection, and/or wireless communication. The results of this research demonstrate that PNNL’s prototype device can be effective at determining whether a container was scanned by X-ray equipment typically used for cargo container inspections. This paper focuses on laboratory measurements and test results acquired with the PNNL prototype device using several X-ray radiation levels. Keywords: Radiation, Scan, X-ray, Gamma, Detection, Cargo, Container, Wireless, RF« less

Intrusion dynamics of particle plumes in stratified water with weak crossflow: Application to deep ocean blowouts

NASA Astrophysics Data System (ADS)

Wang, Dayang; Adams, E. Eric

2016-06-01

We present an experimental study of particle plumes in ambient stratification and a mild current. In an inverted framework, the results describe the fate of oil droplets released from a deep ocean blowout. A continuous stream of dense glass beads was released from a carriage towed in a salt-stratified tank. Nondimensional particle slip velocity UN ranged from 0.1 to 1.9, and particles with UN ≤ 0.5 were observed to enter the intrusion layer. The spatial distributions of beads, collected on a bottom sled towed with the source, present a Gaussian distribution in the transverse direction and a skewed distribution in the along-current direction. Dimensions of the distributions increase with decreasing UN. The spreading relations can be used as input to far-field models describing subsequent transport of particles or, in an inverted framework, oil droplets. The average particle settling velocity, Uave, was found to exceed the individual particle slip velocity, Us, which is attributed to the initial plume velocity near the point of release. Additionally, smaller particles exhibit a "group" or "secondary plume" effect as they exit the intrusion as a swarm. The secondary effect becomes more prominent as UN decreases, and might help explain observations from the 2000 Deep Spill field experiment where oil was found to surface more rapidly than predicted based on Us. An analytical model predicting the particle deposition patterns was validated against experimental measurements, and used to estimate near-field oil transport under the Deepwater Horizon spill conditions, with/without chemical dispersants.

Department of Defense counterdrug technology development of non-intrusive inspection systems

NASA Astrophysics Data System (ADS)

Pennella, John J.

1997-02-01

The Naval Surface Warfare Center Dahlgren Division serves as the executive agent for the DoD's Contraband Detection and Cargo Container Inspection Technology Development Program. The goal of the DoD non-intrusive inspection (NII) program is to develop prototype equipment that can be used to inspect containers and vehicles, quickly and in large numbers without unnecessary delays in the movement of legitimate cargo. This paper summaries the past accomplishments of the program, current status, and future plans.

HPNAIDM: The High-Performance Network Anomaly/Intrusion Detection and Mitigation System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yan

Identifying traffic anomalies and attacks rapidly and accurately is critical for large network operators. With the rapid growth of network bandwidth, such as the next generation DOE UltraScience Network, and fast emergence of new attacks/virus/worms, existing network intrusion detection systems (IDS) are insufficient because they: • Are mostly host-based and not scalable to high-performance networks; • Are mostly signature-based and unable to adaptively recognize flow-level unknown attacks; • Cannot differentiate malicious events from the unintentional anomalies. To address these challenges, we proposed and developed a new paradigm called high-performance network anomaly/intrustion detection and mitigation (HPNAIDM) system. The new paradigm ismore » significantly different from existing IDSes with the following features (research thrusts). • Online traffic recording and analysis on high-speed networks; • Online adaptive flow-level anomaly/intrusion detection and mitigation; • Integrated approach for false positive reduction. Our research prototype and evaluation demonstrate that the HPNAIDM system is highly effective and economically feasible. Beyond satisfying the pre-set goals, we even exceed that significantly (see more details in the next section). Overall, our project harvested 23 publications (2 book chapters, 6 journal papers and 15 peer-reviewed conference/workshop papers). Besides, we built a website for technique dissemination, which hosts two system prototype release to the research community. We also filed a patent application and developed strong international and domestic collaborations which span both academia and industry.« less

X-ray scan detection for cargo integrity

NASA Astrophysics Data System (ADS)

Valencia, Juan; Miller, Steve

2011-04-01

The increase of terrorism and its global impact has made the determination of the contents of cargo containers a necessity. Existing technology allows non-intrusive inspections to determine the contents of a container rapidly and accurately. However, some cargo shipments are exempt from such inspections. Hence, there is a need for a technology that enables rapid and accurate means of detecting whether such containers were non-intrusively inspected. Non-intrusive inspections are most commonly performed utilizing high powered X-ray equipment. The challenge is creating a device that can detect short duration X-ray scans while maintaining a portable, battery powered, low cost, and easy to use platform. The Pacific Northwest National Laboratory (PNNL) has developed a methodology and prototype device focused on this challenge. The prototype, developed by PNNL, is a battery powered electronic device that continuously measures its X-ray and Gamma exposure, calculates the dose equivalent rate, and makes a determination of whether the device has been exposed to the amount of radiation experienced during an X-ray inspection. Once an inspection is detected, the device will record a timestamp of the event and relay the information to authorized personnel via a visual alert, USB connection, and/or wireless communication. The results of this research demonstrate that PNNL's prototype device can be effective at determining whether a container was scanned by X-ray equipment typically used for cargo container inspections. This paper focuses on laboratory measurements and test results acquired with the PNNL prototype device using several X-ray radiation levels.

Many-objective robust decision making for water allocation under climate change.

PubMed

Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E

2017-12-31

Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large rivers. The framework was applied to the Pearl River basin (PRB), China where sufficient flow to the delta is required to reduce saltwater intrusion in the dry season. Before identifying and assessing robust water allocation plans for the future, the performance of ten state-of-the-art MOEAs (multi-objective evolutionary algorithms) is evaluated for the water allocation problem in the PRB. The Borg multi-objective evolutionary algorithm (Borg MOEA), which is a self-adaptive optimization algorithm, has the best performance during the historical periods. Therefore it is selected to generate new water allocation plans for the future (2079-2099). This study shows that robust decision making using carefully selected MOEAs can help limit saltwater intrusion in the Pearl River Delta. However, the framework could perform poorly due to larger than expected climate change impacts on water availability. Results also show that subjective design choices from the researchers and/or water managers could potentially affect the ability of the model framework, and cause the most robust water allocation plans to fail under future climate change. Developing robust allocation plans in a river basin suffering from increasing water shortage requires the researchers and water managers to well characterize future climate change of the study regions and vulnerabilities of their tools. Copyright © 2017 Elsevier B.V. All rights reserved.

THE POTENTIAL FOR THE USE OF CANINES IN VAPOR INTRUSION INVESTIGATIONS

EPA Science Inventory

Dogs have been used extensively in law enforcement and military applications to detect narcotics and explosives for over thirty years and in arson investigations to detect accelerants since they are much more accurate at discriminating between accelerants and by-products of combu...

Time-resolved seismic tomography detects magma intrusions at Mount Etna.

PubMed

Patanè, D; Barberi, G; Cocina, O; De Gori, P; Chiarabba, C

2006-08-11

The continuous volcanic and seismic activity at Mount Etna makes this volcano an important laboratory for seismological and geophysical studies. We used repeated three-dimensional tomography to detect variations in elastic parameters during different volcanic cycles, before and during the October 2002-January 2003 flank eruption. Well-defined anomalous low P- to S-wave velocity ratio volumes were revealed. Absent during the pre-eruptive period, the anomalies trace the intrusion of volatile-rich (>/=4 weight percent) basaltic magma, most of which rose up only a few months before the onset of eruption. The observed time changes of velocity anomalies suggest that four-dimensional tomography provides a basis for more efficient volcano monitoring and short- and midterm eruption forecasting of explosive activity.

Passive intrusion detection system

NASA Technical Reports Server (NTRS)

Laue, E. G. (Inventor)

1980-01-01

An intrusion detection system is described in which crystal oscillators are used to provide a frequency which varies as a function of fluctuations of a particular environmental property of the atmosphere, e.g., humidity, in the protected volume. The system is based on the discovery that the frequency of an oscillator whose crystal is humidity sensitive, varies at a frequency or rate which is within a known frequency band, due to the entry of an intruder into the protected volume. The variable frequency is converted into a voltage which is then filtered by a filtering arrangement which permits only voltage variations at frequencies within the known frequency band to activate an alarm, while inhibiting the alarm activation when the voltage frequency is below or above the known frequency band.

Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition.

PubMed

Galbally, Javier; Marcel, Sébastien; Fierrez, Julian

2014-02-01

To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment. The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results, obtained on publicly available data sets of fingerprint, iris, and 2D face, show that the proposed method is highly competitive compared with other state-of-the-art approaches and that the analysis of the general image quality of real biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.

A Non-Intrusive GMA Welding Process Quality Monitoring System Using Acoustic Sensing.

PubMed

Cayo, Eber Huanca; Alfaro, Sadek Crisostomo Absi

2009-01-01

Most of the inspection methods used for detection and localization of welding disturbances are based on the evaluation of some direct measurements of welding parameters. This direct measurement requires an insertion of sensors during the welding process which could somehow alter the behavior of the metallic transference. An inspection method that evaluates the GMA welding process evolution using a non-intrusive process sensing would allow not only the identification of disturbances during welding runs and thus reduce inspection time, but would also reduce the interference on the process caused by the direct sensing. In this paper a nonintrusive method for weld disturbance detection and localization for weld quality evaluation is demonstrated. The system is based on the acoustic sensing of the welding electrical arc. During repetitive tests in welds without disturbances, the stability acoustic parameters were calculated and used as comparison references for the detection and location of disturbances during the weld runs.

A Non-Intrusive GMA Welding Process Quality Monitoring System Using Acoustic Sensing

PubMed Central

Cayo, Eber Huanca; Alfaro, Sadek Crisostomo Absi

2009-01-01

Most of the inspection methods used for detection and localization of welding disturbances are based on the evaluation of some direct measurements of welding parameters. This direct measurement requires an insertion of sensors during the welding process which could somehow alter the behavior of the metallic transference. An inspection method that evaluates the GMA welding process evolution using a non-intrusive process sensing would allow not only the identification of disturbances during welding runs and thus reduce inspection time, but would also reduce the interference on the process caused by the direct sensing. In this paper a nonintrusive method for weld disturbance detection and localization for weld quality evaluation is demonstrated. The system is based on the acoustic sensing of the welding electrical arc. During repetitive tests in welds without disturbances, the stability acoustic parameters were calculated and used as comparison references for the detection and location of disturbances during the weld runs. PMID:22399990

Using Hybrid Algorithm to Improve Intrusion Detection in Multi Layer Feed Forward Neural Networks

ERIC Educational Resources Information Center

Ray, Loye Lynn

2014-01-01

The need for detecting malicious behavior on a computer networks continued to be important to maintaining a safe and secure environment. The purpose of this study was to determine the relationship of multilayer feed forward neural network architecture to the ability of detecting abnormal behavior in networks. This involved building, training, and…

U-Pb (zircon) and geochemical constraints on the age, origin, and evolution of Paleozoic arc magmas in the Oyu Tolgoi porphyry Cu-Au district, southern Mongolia

USGS Publications Warehouse

Wainwright, A.J.; Tosdal, R.M.; Wooden, J.L.; Mazdab, F.K.; Friedman, R.M.

2011-01-01

Uranium-Pb (zircon) ages are linked with geochemical data for porphyry intrusions associated with giant porphyry Cu-Au systems at Oyu Tolgoi to place those rocks within the petrochemical framework of Devonian and Carboniferous rocks of southern Mongolia. In this part of the Gurvansayhan terrane within the Central Asian Orogenic Belt, the transition from Devonian tholeiitic marine rocks to unconformably overlying Carboniferous calc-alkaline subaerial to shallow marine volcanic rocks reflects volcanic arc thickening and maturation. Radiogenic Nd and Pb isotopic compositions (??Nd(t) range from +3.1 to +7.5 and 206Pb/204Pb values for feldspars range from 17.97 to 18.72), as well as low high-field strength element (HFSE) contents of most rocks (mafic rocks typically have <1.5% TiO2) are consistent with magma derivation from depleted mantle in an intra-oceanic volcanic arc. The Late Devonian and Carboniferous felsic rocks are dominantly medium- to high-K calc-alkaline and characterized by a decrease in Sr/Y ratios through time, with the Carboniferous rocks being more felsic than those of Devonian age. Porphyry Cu-Au related intrusions were emplaced in the Late Devonian during the transition from tholeiitic to calc-alkaline arc magmatism. Uranium-Pb (zircon) geochronology indicates that the Late Devonian pre- to syn-mineral quartz monzodiorite intrusions associated with the porphyry Cu-Au deposits are ~372Ma, whereas granodiorite intrusions that post-date major shortening and are associated with less well-developed porphyry Cu-Au mineralization are ~366Ma. Trace element geochemistry of zircons in the Late Devonian intrusions associated with the porphyry Cu-Au systems contain distinct Th/U and Yb/Gd ratios, as well as Hf and Y concentrations that reflect mixing of magma of distinct compositions. These characteristics are missing in the unmineralized Carboniferous intrusions. High Sr/Y and evidence for magma mixing in syn- to late-mineral intrusions distinguish the Late Devonian rocks associated with giant Cu-Au deposits from younger magmatic suites in the district. ?? 2010 Elsevier B.V.

Integration of 2D and 3D reflection seismic data with deep boreholes in the Kevitsa Ni-Cu-PGE deposit, northern Finland

NASA Astrophysics Data System (ADS)

Koivisto, Emilia; Malehmir, Alireza; Voipio, Teemu; Wijns, Chris

2013-04-01

Kevitsa is a large disseminated sulphide Ni-Cu-PGE deposit hosted by the Kevitsa mafic-ultramafic intrusion in northern Finland and dated as about 2.06 Ga old. The Geological Survey of Finland first discovered the Kevitsa deposit in 1987. Open pit mining by Kevitsa Mining Oy/First Quantum Minerals Ltd. commenced in June 2012. The final pit depth is planned to be 550-600 m. The estimated ore reserves of the Kevitsa intrusion are about 240 million tones (using a nickel cut-off grade of 0.1%). The expected life-of-mine is 20-30 years. More than 400 hundred holes have been drilled in the Kevitsa area, but most are concentrated close to the known deposit and do not provide a comprehensive understanding of the extent of the intrusion. The basal contact of the intrusion is penetrated by only about 30 drill holes, most of which are shallow. A better knowledge of the geometry of the intrusion would provide a framework for near-mine and deep exploration in the area. An exact knowledge on the basal contact of the intrusion would also provide an exploration target for the contact-type mineralization that is often more massive and richer in Ni-Cu. In December 2007, a series of 2D reflection seismic profiles was acquired in the Kevitsa area. It consisted of four connected survey lines between 6 and 11 km long. In 2010, the initial positive results of the 2D seismic survey led Kevitsa Mining Oy/First Quantum Minerals Ltd. to initiate a 3D reflection seismic survey. The 3D seismic survey is limited to the closer vicinity of the known deposit, while the 2D seismic survey was designed to provide a more regional view of the Kevitsa intrusive complex. The main aims of the 2D and 3D seismic surveys were to delineate the shape and extent of the ore-bearing Kevitsa intrusion and the geometry of some of the host rock and surrounding units, and extract information about the larger-scale structures and structures important for mine-planning purposes. The 2D and 3D seismic data were used to create a 3D lithological and structural model for the architecture of the whole complex. The information on the extent of the ore-bearing Kevitsa intrusion can be used for more effective exploration in the area. The base of the intrusion is particularly clear in the northern and eastern sectors. Toward the east, the base is mostly defined by disruption of the reflectors internal to the intrusion. The 2D seismic data, which extend beyond the 3D seismic study, reveal that the prominent reflectors at the base of the intrusion continue deeper toward the south-southwest. This has been interpreted as a previously unknown southern continuation of the intrusion. Furthermore, the data reveal strong reflectors at the base of the intrusion that have been penetrated by two deep drill holes in the area. These drill holes reveal contact-type mineralization at the onset of the reflectors. Thus, the seismic data can be directly used for exploration of the contact-type mineralization.

Modified Policy-Delphi study for exploring obesity prevention priorities.

PubMed

Haynes, Emily; Palermo, Claire; Reidlinger, Dianne P

2016-09-06

Until now, industry and government stakeholders have dominated public discourse about policy options for obesity. While consumer involvement in health service delivery and research has been embraced, methods which engage consumers in health policy development are lacking. Conflicting priorities have generated ethical concern around obesity policy. The concept of 'intrusiveness' has been applied to policy decisions in the UK, whereby ethical implications are considered through level of intrusiveness to choice; however, the concept has also been used to avert government regulation to address obesity. The concept of intrusiveness has not been explored from a stakeholder's perspective. The aim is to investigate the relevance of intrusiveness and autonomy to health policy development, and to explore consensus on obesity policy priorities of under-represented stakeholders. The Policy-Delphi technique will be modified using the James Lind Alliance approach to collaborative priority setting. A total of 60 participants will be recruited to represent three stakeholder groups in the Australian context: consumers, public health practitioners and policymakers. A three-round online Policy-Delphi survey will be undertaken. Participants will prioritise options informed by submissions to the 2009 Australian Government Inquiry into Obesity, and rate the intrusiveness of those proposed. An additional round will use qualitative methods in a face-to-face discussion group to explore stakeholder perceptions of the intrusiveness of options. The novelty of this methodology will redress the balance by bringing the consumer voice forward to identify ethically acceptable obesity policy options. Ethical approval was granted by the Bond University Health Research Ethics Committee. The findings will inform development of a conceptual framework for analysing and prioritising obesity policy options, which will be relevant internationally and to ethical considerations of wider public health issues. The findings will be disseminated through peer-reviewed publications, conference presentations and collaborative platforms of policy and science. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Non-intrusive practitioner pupil detection for unmodified microscope oculars.

PubMed

Fuhl, Wolfgang; Santini, Thiago; Reichert, Carsten; Claus, Daniel; Herkommer, Alois; Bahmani, Hamed; Rifai, Katharina; Wahl, Siegfried; Kasneci, Enkelejda

2016-12-01

Modern microsurgery is a long and complex task requiring the surgeon to handle multiple microscope controls while performing the surgery. Eye tracking provides an additional means of interaction for the surgeon that could be used to alleviate this situation, diminishing surgeon fatigue and surgery time, thus decreasing risks of infection and human error. In this paper, we introduce a novel algorithm for pupil detection tailored for eye images acquired through an unmodified microscope ocular. The proposed approach, the Hough transform, and six state-of-the-art pupil detection algorithms were evaluated on over 4000 hand-labeled images acquired from a digital operating microscope with a non-intrusive monitoring system for the surgeon eyes integrated. Our results show that the proposed method reaches detection rates up to 71% for an error of ≈3% w.r.t the input image diagonal; none of the state-of-the-art pupil detection algorithms performed satisfactorily. The algorithm and hand-labeled data set can be downloaded at:: www.ti.uni-tuebingen.de/perception. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of graph-based semi-supervised learning for development of cyber COP and network intrusion detection

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Colonna-Romano, John; Eslami, Mohammed

2017-05-01

The United States increasingly relies on cyber-physical systems to conduct military and commercial operations. Attacks on these systems have increased dramatically around the globe. The attackers constantly change their methods, making state-of-the-art commercial and military intrusion detection systems ineffective. In this paper, we present a model to identify functional behavior of network devices from netflow traces. Our model includes two innovations. First, we define novel features for a host IP using detection of application graph patterns in IP's host graph constructed from 5-min aggregated packet flows. Second, we present the first application, to the best of our knowledge, of Graph Semi-Supervised Learning (GSSL) to the space of IP behavior classification. Using a cyber-attack dataset collected from NetFlow packet traces, we show that GSSL trained with only 20% of the data achieves higher attack detection rates than Support Vector Machines (SVM) and Naïve Bayes (NB) classifiers trained with 80% of data points. We also show how to improve detection quality by filtering out web browsing data, and conclude with discussion of future research directions.

Computer-Mediated Communication in Intimate Relationships: Associations of Boundary Crossing, Intrusion, Relationship Satisfaction, and Partner Responsiveness.

PubMed

Norton, Aaron M; Baptist, Joyce; Hogan, Bernie

2018-01-01

This study examined the impact of technology on couples in committed relationships through the lens of the couple and technology framework. Specifically, we used data from 6,756 European couples to examine associations between online boundary crossing, online intrusion, relationship satisfaction, and partner responsiveness. The results suggest that participants' reports of online boundary crossing were linked with lower relationship satisfaction and partner responsiveness. Also, lower relationship satisfaction and partner responsiveness were associated with increased online boundary crossing. The results suggest that men, but not women, who reported greater acceptability for online boundary crossing were more likely to have partners who reported lower relationship satisfaction in their relationships. Implications for clinicians, relationship educators, and researchers are discussed. © 2017 American Association for Marriage and Family Therapy.

FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection.

PubMed

Noto, Keith; Brodley, Carla; Slonim, Donna

2012-01-01

Anomaly detection involves identifying rare data instances (anomalies) that come from a different class or distribution than the majority (which are simply called "normal" instances). Given a training set of only normal data, the semi-supervised anomaly detection task is to identify anomalies in the future. Good solutions to this task have applications in fraud and intrusion detection. The unsupervised anomaly detection task is different: Given unlabeled, mostly-normal data, identify the anomalies among them. Many real-world machine learning tasks, including many fraud and intrusion detection tasks, are unsupervised because it is impractical (or impossible) to verify all of the training data. We recently presented FRaC, a new approach for semi-supervised anomaly detection. FRaC is based on using normal instances to build an ensemble of feature models, and then identifying instances that disagree with those models as anomalous. In this paper, we investigate the behavior of FRaC experimentally and explain why FRaC is so successful. We also show that FRaC is a superior approach for the unsupervised as well as the semi-supervised anomaly detection task, compared to well-known state-of-the-art anomaly detection methods, LOF and one-class support vector machines, and to an existing feature-modeling approach.

FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection

PubMed Central

Brodley, Carla; Slonim, Donna

2011-01-01

Anomaly detection involves identifying rare data instances (anomalies) that come from a different class or distribution than the majority (which are simply called “normal” instances). Given a training set of only normal data, the semi-supervised anomaly detection task is to identify anomalies in the future. Good solutions to this task have applications in fraud and intrusion detection. The unsupervised anomaly detection task is different: Given unlabeled, mostly-normal data, identify the anomalies among them. Many real-world machine learning tasks, including many fraud and intrusion detection tasks, are unsupervised because it is impractical (or impossible) to verify all of the training data. We recently presented FRaC, a new approach for semi-supervised anomaly detection. FRaC is based on using normal instances to build an ensemble of feature models, and then identifying instances that disagree with those models as anomalous. In this paper, we investigate the behavior of FRaC experimentally and explain why FRaC is so successful. We also show that FRaC is a superior approach for the unsupervised as well as the semi-supervised anomaly detection task, compared to well-known state-of-the-art anomaly detection methods, LOF and one-class support vector machines, and to an existing feature-modeling approach. PMID:22639542

Characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts

NASA Astrophysics Data System (ADS)

Chen, Siyue; Leung, Henry; Dondo, Maxwell

2014-05-01

As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.

A Comprehensive Reasoning Framework for Information Survivability (User Intent Encapsulation and Reasoning About Intrusion: Implementation and Performance Assessment)

DTIC Science & Technology

2006-08-01

obvious and apparent attacks such as transferring the /etc/ passwd file from one host to another, password-cracking by comparing the entries in the /etc... passwd file to entries in another file, using a dictionary file for the same, and exploiting the vulnerabilities such as rdist, perl 5.0.1, etc. The

Active Learning Framework for Non-Intrusive Load Monitoring: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Xin

2016-05-16

Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimate the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too much data without class labels yet being unable to label the data manually for cost or time constraints. This paper presents an active learning framework that helps existing NILM techniques to overcome this challenge. Active learning is an advanced machine learning method that interactively queries a user for the class label information. Unlike most existing NILM systems that heuristically requestmore » user inputs, the proposed method only needs minimally sufficient information from a user to build a compact and yet highly representative load signature library. Initial results indicate the proposed method can reduce the user inputs by up to 90% while still achieving similar disaggregation performance compared to a heuristic method. Thus, the proposed method can substantially reduce the burden on the user, improve the performance of a NILM system with limited user inputs, and overcome the key market barriers to the wide adoption of NILM technologies.« less

Detection of deep stratospheric intrusions by cosmogenic 35S

PubMed Central

Su, Lin; Shaheen, Robina; Fung, Jimmy C. H.; Thiemens, Mark H.

2016-01-01

The extent to which stratospheric intrusions on synoptic scales influence the tropospheric ozone (O3) levels remains poorly understood, because quantitative detection of stratospheric air has been challenging. Cosmogenic 35S mainly produced in the stratosphere has the potential to identify stratospheric air masses at ground level, but this approach has not yet been unambiguously shown. Here, we report unusually high 35S concentrations (7,390 atoms m−3; ∼16 times greater than annual average) in fine sulfate aerosols (aerodynamic diameter less than 0.95 µm) collected at a coastal site in southern California on May 3, 2014, when ground-level O3 mixing ratios at air quality monitoring stations across southern California (43 of 85) exceeded the recently revised US National Ambient Air Quality Standard (daily maximum 8-h average: 70 parts per billion by volume). The stratospheric origin of the significantly enhanced 35S level is supported by in situ measurements of air pollutants and meteorological variables, satellite observations, meteorological analysis, and box model calculations. The deep stratospheric intrusion event was driven by the coupling between midlatitude cyclones and Santa Ana winds, and it was responsible for the regional O3 pollution episode. These results provide direct field-based evidence that 35S is an additional sensitive and unambiguous tracer in detecting stratospheric air in the boundary layer and offer the potential for resolving the stratospheric influences on the tropospheric O3 level. PMID:27655890

A climatology of frozen-in anticyclones in the spring arctic stratosphere over the period 1960-2011

NASA Astrophysics Data System (ADS)

ThiéBlemont, RéMi; Orsolini, Yvan J.; Hauchecorne, Alain; Drouin, Marc-Antoine; Huret, Nathalie

2013-02-01

During springtime, following the stratospheric final warming, intrusions from low latitudes can become trapped at polar latitudes in long-lived anticyclones. Such "frozen-in" anticyclones (FrIACs) have occasionally been observed to persist as late as August, advected by summer easterlies. In this study, the high-resolution advection contour model MIMOSA is used to advect a pseudo-potential vorticity tracer. The model is driven by ERA-40 and the ERA-Interim reanalyses over the period 1960-2011. We first identify a remarkable FrIAC event in spring 2011. In addition, we developed a method to detect the characteristic size of low-latitude intrusions into the polar region at the time of the spring transition, over the period 1960-2011. Years are classified as either Type-A when the intrusions are small or as Type-B when intrusions are large, potentially evolving into FrIACs. For a FrIAC to occur, we require an additional criterion based on the in-phase character of the core of the intrusions and the anticyclone. During the 52 analyzed years, 9 events have been identified: 1 in the 1960s, 1 in the 1980s, 2 in the 1990s, and 5 from 2002. FrIAC are predominantly long-lived intrusions, which occur in association with abrupt and early reversal to summer easterlies with a large heat flux pulse around the date of this wind reversal. Finally, the results are discussed in a climatological context.

A Climatology of Frozen-In Anticyclones in the Spring Arctic Stratosphere over the Period 1960-2011

NASA Astrophysics Data System (ADS)

Thiéblemont, Rémi; Orsolini, Yvan J.; Huret, Nathalie; Hauchecorne, Alain; Drouin, Marc-Antoine

2013-04-01

During springtime, following the stratospheric final warming, intrusions from low latitudes can become trapped at polar latitudes in long-lived anticyclones. Such "frozen-in" anticyclones (FrIACs) have occasionally been observed to persist as late as August, advected by summer easterlies. In this study, the high-resolution advection contour model MIMOSA is used to advect a pseudo-potential vorticity tracer. The model is driven by ERA-40 and the ERA-Interim reanalyses over the period 1960-2011. We first identify a remarkable FrIAC event in spring 2011. In addition, we developed a method to detect the characteristic size of low-latitude intrusions into the polar region at the time of the spring transition, over the period 1960-2011. Years are classified as either Type-A when the intrusions are small, or as Type-B when intrusions are large, potentially evolving into FrIACs. For a FrIAC to occur, we require an additional criterion based on the in-phase character of the core of the intrusions and the anticyclone. During the 52 analysed years, 9 events have been identified: 1 in the 1960s, 1 in the 1980s, 2 in the 1990s and 5 from 2002. FrIAC are predominantly long-lived intrusions, which occur in association with abrupt and early reversal to summer easterlies with a large heat flux pulse around the date of this wind reversal. Finally, the results are discussed in a climatological context.

Extruded upper first molar intrusion: Comparison between unilateral and bilateral miniscrew anchorage.

PubMed

Sugii, Mari Miura; Barreto, Bruno de Castro Ferreira; Francisco Vieira-Júnior, Waldemir; Simone, Katia Regina Izola; Bacchi, Ataís; Caldas, Ricardo Armini

2018-01-01

The aim of his study was to evaluate the stress on tooth and alveolar bone caused by orthodontic intrusion forces in a supraerupted upper molar, by using a three-dimensional Finite Element Method (FEM). A superior maxillary segment was modeled in the software SolidWorks 2010 (SolidWorks Corporation, Waltham, MA, USA) containing: cortical and cancellous bone, supraerupted first molar, periodontal tissue and orthodontic components. A finite element model has simulated intrusion forces of 4N onto a tooth, directed to different mini-screw locations. Three different intrusion mechanics vectors were simulated: anchoring on a buccal mini-implant; anchoring on a palatal mini-implant and the association of both anchorage systems. All analyses were performed considering the minimum principal stress and total deformation. Qualitative analyses exhibited stress distribution by color maps. Quantitative analysis was performed with a specific software for reading and solving numerical equations (ANSYS Workbench 14, Ansys, Canonsburg, Pennsylvania, USA). Intrusion forces applied from both sides (buccal and palatal) resulted in a more homogeneous stress distribution; no high peak of stress was detected and it has allowed a vertical resultant movement. Buccal or palatal single-sided forces resulted in concentrated stress zones with higher values and tooth tipping to respective force side. Unilateral forces promoted higher stress in root apex and higher dental tipping. The bilateral forces promoted better distribution without evidence of dental tipping. Bilateral intrusion technique suggested lower probability of root apex resorption.

Holistic Network Defense: Fusing Host and Network Features for Attack Classification

DTIC Science & Technology

2011-03-01

Measures for Anomaly Detection," IEEE Symposium on Security and Privacy, Oakland, CA, (May 2001). 33. Mahoney , Matthew V, and Phillip K. Chan...University of London, August 2005. 44. Newman , Daniel, Kristina M. Manalo, and Ed Tittel. "Intrusion Detection Overview," InformIT, (June 2004). 20 Feb

The Unexplored Impact of IPv6 on Intrusion Detection Systems

DTIC Science & Technology

2012-03-01

of cross-NIDS, standardized, rule sets such as SNORT’s VRT [23]. • Continuously monitor vulnerability or exploit development sites. For example, the...and BRO polices should be written to enhance detection. The bolstering of built-in databases and repositories such as VRT [23] for specific IPv6 issues

Forced-folding by laccolith and saucer-shaped sill intrusions on the Earth, planets and icy satellites

NASA Astrophysics Data System (ADS)

Michaut, Chloé

2017-04-01

Horizontal intrusions probably initially start as cracks, with negligible surface deformation. Once their horizontal extents become large enough compared to their depths, they make room for themselves by lifting up their overlying roofs, creating characteristic surface deformations that can be observed at the surface of planets. We present a model where magma flows below a thin elastic overlying layer characterized by a flexural wavelength Λ and study the dynamics and morphology of such a magmatic intrusion. Our results show that, depending on its size, the intrusion present different shapes and thickness-to-radius relationships. During a first phase, elastic bending of the overlying layer is the main source of driving pressure in the flow; the pressure decreases as the flow radius increases, the intrusion is bell-shaped and its thickness is close to being proportional to its radius. When the intrusion radius becomes larger than 4 times Λ, the flow enters a gravity current regime and progressively develops a pancake shape with a flat top. We study the effect of topography on flow spreading in particular in the case where the flow is constrained by a lithostatic barrier within a depression, such as an impact crater on planets or a caldera on Earth. We show that the resulting shape for the flow depends on the ratio between the flexural wavelength of the layer overlying the intrusion and the depression radius. The model is tested against terrestrial data and is shown to well explain the size and morphology of laccoliths and saucer-shaped sills on Earth. We use our results to detect and characterize shallow solidified magma reservoirs in the crust of terrestrial planets and potential shallow water reservoirs in the ice shell of icy satellites.

Geophysical Framework of a Rare Earth Element Enriched Terrane, Mountain Pass, California

NASA Astrophysics Data System (ADS)

Denton, K. M.; Ponce, D. A.; Peacock, J.; Miller, D. M.; Miller, J. S.

2016-12-01

Carbonatite ore deposits continue to be the primary source for rare earth elements (REEs), however large viable REE ore deposits are uncommon. The Mountain Pass carbonatite deposit, located in the eastern Mojave Desert of California, is the largest economic deposit of light REEs in North America. A 1.417 Ga ultrapotassic suite (shonkinite, syenite, and granite) and a 1.375 Ga barite-bastnasite-rich carbonatite (sovite) ore deposit comprise the enclave of REE-enriched outcrops and dikes that occupy a narrow ( 3 km) zone of 1.7 Ga gneiss extending at least 10-km to the southeast from southern Clark Mountain. Modeling of gravity, magnetic, and magnetotelluric (MT) data reveals subsurface features that form the structural framework of the REE terrane. The carbonatite and ultrapotassic mafic suite is associated with a local gravity high that is superimposed on a 4 km-wide gravity terrace, likely related to less dense granitic gneiss basement. Although physical property data indicate that the intrusive suite and carbonatite are essentially and nonmagnetic, aeromagnetic data indicate that these rocks occur along the eastern edge of a prominent north-northwest trending aeromagnetic high. This relationship suggests that they may have been preferentially emplaced along a zone of weakness or fault. The source of the magnetic high is 2-3 km below the surface and coincides with a relatively electrically conductive (3 orders of magnitude higher than surrounding rock) feature. MT data indicate that the western edge of the magnetic feature could be connected to a deeper ( 8 km) conductive feature related to possible intrusions and/or hydrothermal systems. The lack of a magnetic signature of the REE terrane can be explained by alteration of magnetite, given that the terrane lies within a broader alteration zone and observed magnetic low. If so, such an alteration event, capable of remobilizing rare earth elements, likely occurred during or after emplacement of the intrusive suite. Furthermore, an alteration event is consistent with local geology, high rare-earth element concentration, and unusual geochemistry of the carbonatite deposit and associated intrusive suite.

Associations of hallucination proneness with free-recall intrusions and response bias in a nonclinical sample.

PubMed

Brébion, Gildas; Larøi, Frank; Van der Linden, Martial

2010-10-01

Hallucinations in patients with schizophrenia have been associated with a liberal response bias in signal detection and recognition tasks and with various types of source-memory error. We investigated the associations of hallucination proneness with free-recall intrusions and false recognitions of words in a nonclinical sample. A total of 81 healthy individuals were administered a verbal memory task involving free recall and recognition of one nonorganizable and one semantically organizable list of words. Hallucination proneness was assessed by means of a self-rating scale. Global hallucination proneness was associated with free-recall intrusions in the nonorganizable list and with a response bias reflecting tendency to make false recognitions of nontarget words in both types of list. The verbal hallucination score was associated with more intrusions and with a reduced tendency to make false recognitions of words. The associations between global hallucination proneness and two types of verbal memory error in a nonclinical sample corroborate those observed in patients with schizophrenia and suggest that common cognitive mechanisms underlie hallucinations in psychiatric and nonclinical individuals.

Autonomous navigation system and method

DOEpatents

Bruemmer, David J [Idaho Falls, ID; Few, Douglas A [Idaho Falls, ID

2009-09-08

A robot platform includes perceptors, locomotors, and a system controller, which executes instructions for autonomously navigating a robot. The instructions repeat, on each iteration through an event timing loop, the acts of defining an event horizon based on the robot's current velocity, detecting a range to obstacles around the robot, testing for an event horizon intrusion by determining if any range to the obstacles is within the event horizon, and adjusting rotational and translational velocity of the robot accordingly. If the event horizon intrusion occurs, rotational velocity is modified by a proportion of the current rotational velocity reduced by a proportion of the range to the nearest obstacle and translational velocity is modified by a proportion of the range to the nearest obstacle. If no event horizon intrusion occurs, translational velocity is set as a ratio of a speed factor relative to a maximum speed.

Security barriers with automated reconnaissance

DOEpatents

McLaughlin, James O; Baird, Adam D; Tullis, Barclay J; Nolte, Roger Allen

2015-04-07

An intrusion delaying barrier includes primary and secondary physical structures and can be instrumented with multiple sensors incorporated into an electronic monitoring and alarm system. Such an instrumented intrusion delaying barrier may be used as a perimeter intrusion defense and assessment system (PIDAS). Problems with not providing effective delay to breaches by intentional intruders and/or terrorists who would otherwise evade detection are solved by attaching the secondary structures to the primary structure, and attaching at least some of the sensors to the secondary structures. By having multiple sensors of various types physically interconnected serves to enable sensors on different parts of the overall structure to respond to common disturbances and thereby provide effective corroboration that a disturbance is not merely a nuisance or false alarm. Use of a machine learning network such as a neural network exploits such corroboration.

Groundwater modelling as a tool for the European Water Framework Directive (WFD) application: The Llobregat case

NASA Astrophysics Data System (ADS)

Vázquez-Suñé, E.; Abarca, E.; Carrera, J.; Capino, B.; Gámez, D.; Pool, M.; Simó, T.; Batlle, F.; Niñerola, J. M.; Ibáñez, X.

The European Water Framework Directive establishes the basis for Community action in the field of water policy. Water authorities in Catalonia, together with users are designing a management program to improve groundwater status and to assess the impact of infrastructures and city-planning activities on the aquifers and their associated natural systems. The objective is to describe the role of groundwater modelling in addressing the issues raised by the Water Framework Directive, and its application to the Llobregat Delta, Barcelona, Spain. In this case modelling was used to address Water Framework Directive in the following: (1) Characterisation of aquifers and the status of groundwater by integration of existing knowledge and new hydrogeological information. Inverse modelling allowed us to reach an accurate description of the paths and mechanisms for the evolution of seawater intrusion. (2) Quantification of groundwater budget (mass balance). This is especially relevant for those terms that are difficult to asses, such as recharge from river infiltration during floods, which we have found to be very important. (3) Evaluation of groundwater-related environmental needs in aquatic ecosystems. The model allows quantifying groundwater input under natural conditions, which can be used as a reference level for stressed conditions. (4) Evaluation of possible impacts of territory planning (Llobregat river course modification, new railway tunnels, airport and docks enlargement, etc.). (5) Definition of management areas. (6) The assessment of possible future scenarios combined with optimization processes to quantify sustainable pumping rates and design measures to control seawater intrusion. The resulting model has been coupled to a user-friendly interface to allow water managers to design and address corrective measures in an agile and effective way.

Detection and Classification of Network Intrusions Using Hidden Markov Models

DTIC Science & Technology

2002-01-01

31 2.2.3 High-level state machines for misuse detection . . . . . . . 32 2.2.4 EMERALD ...Solaris host audit data to detect Solaris R2L (Remote-to-Local) and U2R (User-to-Root) attacks. 7 login as a legitimate user on a local system and use a...as suspicious rather than the entire login session and it can detect some anomalies that are difficult to detect with traditional approaches. It’s

Geologic Insights and Suggestions on Mineral Potential Based on Analyses of Geophysical Data of the Southern Toquima Range, Nye County, Nevada

USGS Publications Warehouse

Shawe, D.R.; Kucks, R.P.; Hildenbrand, T.G.

2004-01-01

Aeromagnetic and gravity data provide confirmation of major structural and lithologic units in the southern Toquima Range, Nevada. These units include Cretaceous granite plutons and Tertiary calderas. In addition, the geophysical maps pinpoint numerous faults and lesser intrusions, and they suggest locations of several inferred subsurface intrusions. They also corroborate a system of northwesterly and northeasterly conjugate structures that probably are fundamental to the structural framework of the Toquima Range. A combination of geophysical, geochemical, and geologic data available for the widely mineralized and productive area suggests additional mineral resource potential, especially in and (or) adjacent to the Round Mountain, Jefferson, Manhattan, and Belmont mining districts. Also, evidence for mineral potential exists for areas near the Flower mercury mine south of Mount Jefferson caldera, and in the Bald Mountain Canyon belt of gold-quartz veins in the Manhattan caldera. A few other areas also show potential for mineral resources. The various geologic environments indicated within the map area suggest base- and precious-metal potential in porphyry deposits as well as in quartz-vein and skarn deposits associated with intrusive stocks.

Dispersion and transport of hypersaline gravity currents in the presence of internal waves at a pycnocline

NASA Astrophysics Data System (ADS)

Hogg, C. A. R.; Pietrasz, V. B.; Ouellette, N. T.; Koseff, J. R.

2015-12-01

Desalination of seawater offers a source of potable water in arid regions and during drought. However, hypersaline discharge from desalination facilities presents environmental risks, particularly to benthic organisms. The risks posed by salt levels and chemical additives, which can be toxic to local ecosystems, are typically mitigated by ensuring high levels of dilution close to the source. We report on laboratory flume experiments examining how internal waves at the pycnocline of a layered ambient density stratification influence the transport of hypersaline effluent moving as a gravity current down the slope. We found that some of the hypersaline fluid from the gravity current was diverted away from the slope into an intrusion along the pycnocline. A parametric study investigated how varying the energy of the internal wave altered the amount of dense fluid that was diverted into the pycnocline intrusion. The results are compared to an analytical framework that compares the incident energy in the internal wave to potential energy used in diluting the gravity current. These results are significant for desalination effluents because fluid diverted into the intrusion avoids the ecologically sensitive benthic layer and disperses more quickly than if it had continued to propagate along the bed.

Single-process versus multiple-strategy models of decision making: evidence from an information intrusion paradigm.

PubMed

Söllner, Anke; Bröder, Arndt; Glöckner, Andreas; Betsch, Tilmann

2014-02-01

When decision makers are confronted with different problems and situations, do they use a uniform mechanism as assumed by single-process models (SPMs) or do they choose adaptively from a set of available decision strategies as multiple-strategy models (MSMs) imply? Both frameworks of decision making have gathered a lot of support, but only rarely have they been contrasted with each other. Employing an information intrusion paradigm for multi-attribute decisions from givens, SPM and MSM predictions on information search, decision outcomes, attention, and confidence judgments were derived and tested against each other in two experiments. The results consistently support the SPM view: Participants seemingly using a "take-the-best" (TTB) strategy do not ignore TTB-irrelevant information as MSMs would predict, but adapt the amount of information searched, choose alternative choice options, and show varying confidence judgments contingent on the quality of the "irrelevant" information. The uniformity of these findings underlines the adequacy of the novel information intrusion paradigm and comprehensively promotes the notion of a uniform decision making mechanism as assumed by single-process models. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Multifidelity, Multidisciplinary Design Under Uncertainty with Non-Intrusive Polynomial Chaos

NASA Technical Reports Server (NTRS)

West, Thomas K., IV; Gumbert, Clyde

2017-01-01

The primary objective of this work is to develop an approach for multifidelity uncertainty quantification and to lay the framework for future design under uncertainty efforts. In this study, multifidelity is used to describe both the fidelity of the modeling of the physical systems, as well as the difference in the uncertainty in each of the models. For computational efficiency, a multifidelity surrogate modeling approach based on non-intrusive polynomial chaos using the point-collocation technique is developed for the treatment of both multifidelity modeling and multifidelity uncertainty modeling. Two stochastic model problems are used to demonstrate the developed methodologies: a transonic airfoil model and multidisciplinary aircraft analysis model. The results of both showed the multifidelity modeling approach was able to predict the output uncertainty predicted by the high-fidelity model as a significant reduction in computational cost.

An Ontology for Identifying Cyber Intrusion Induced Faults in Process Control Systems

NASA Astrophysics Data System (ADS)

Hieb, Jeffrey; Graham, James; Guan, Jian

This paper presents an ontological framework that permits formal representations of process control systems, including elements of the process being controlled and the control system itself. A fault diagnosis algorithm based on the ontological model is also presented. The algorithm can identify traditional process elements as well as control system elements (e.g., IP network and SCADA protocol) as fault sources. When these elements are identified as a likely fault source, the possibility exists that the process fault is induced by a cyber intrusion. A laboratory-scale distillation column is used to illustrate the model and the algorithm. Coupled with a well-defined statistical process model, this fault diagnosis approach provides cyber security enhanced fault diagnosis information to plant operators and can help identify that a cyber attack is underway before a major process failure is experienced.

Quantifying Performance Bias in Label Fusion

DTIC Science & Technology

2012-08-21

detect ), may provide the end-user with the means to appropriately adjust the performance and optimal thresholds for performance by fusing legacy systems...boolean combination of classification systems in ROC space: An application to anomaly detection with HMMs. Pattern Recognition, 43(8), 2732-2752. 10...Shamsuddin, S. (2009). An overview of neural networks use in anomaly intrusion detection systems. Paper presented at the Research and Development (SCOReD

75 FR 37483 - Request for Comments on the Draft Policy Statement on the Protection of Cesium-137 Chloride...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-29

... instruments for end users. This network of facilities ensures that every radiation detection instrument that... associated test-and-evaluation protocols for radiation detection, instrumentation, and personal dosimetry... intrusion. The NRC supports efforts to develop alternate forms of Cs-137 that would reduce the security...

The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

DTIC Science & Technology

2004-01-01

login identity to the one under which the system call is executed, the parameters of the system call execution - file names including full path...Anomaly detection COAST-EIMDT Distributed on target hosts EMERALD Distributed on target hosts and security servers Signature recognition Anomaly...uses a centralized architecture, and employs an anomaly detection technique for intrusion detection. The EMERALD project [80] proposes a

Department of Defense Fiscal Year (FY) 2005 Budget Estimates. Research, Development, Test and Evaluation, Defense-Wide. Volume 1 - Defense Advanced Research Projects Agency

DTIC Science & Technology

2004-02-01

UNCLASSIFIED − Conducted experiments to determine the usability of general-purpose anomaly detection algorithms to monitor a large, complex military...reaction and detection modules to perform tailored analysis sequences to monitor environmental conditions, health hazards and physiological states...scalability of lab proven anomaly detection techniques for intrusion detection in real world high volume environments. Narrative Title FY 2003

Acoustic intrusion detection and positioning system

NASA Astrophysics Data System (ADS)

Berman, Ohad; Zalevsky, Zeev

2002-08-01

Acoustic sensors are becoming more and more applicable as a military battlefield technology. Those sensors allow a detection and direciton estimation with low false alarm rate and high probability of detection. The recent technological progress related to these fields of reserach, together with an evolution of sophisticated algorithms, allow the successful integration of those sensoe in battlefield technologies. In this paper the performances of an acoustic sensor for a detection of avionic vessels is investigated and analyzed.

Sill intrusion in volcanic calderas: implications for vent opening probability

NASA Astrophysics Data System (ADS)

Giudicepietro, Flora; Macedonio, Giovanni; Martini, Marcello; D'Auria, Luca

2017-04-01

Calderas show peculiar behaviors with remarkable dynamic processes, which do not often culminate in eruptions. Observations and studies conducted in recent decades have shown that the most common cause of unrest in the calderas is due to magma intrusion; in particular, the intrusion of sills at shallow depths. Monogenic cones, with large areal dispersion, are quite common in the calderas, suggesting that the susceptibility analysis based on geological features, is not strictly suitable for estimating the vent opening probability in calderas. In general, the opening of a new eruptive vent can be regarded as a rock failure process. The stress field in the rocks that surrounds and tops the magmatic reservoirs plays an important role in causing the rock failure and creating the path that magma can follow towards the surface. In this conceptual framework, we approach the problem of getting clues about the probability of vent opening in volcanic calderas through the study of the stress field produced by the intrusion of magma, in particular, by the intrusion of a sill. We simulate the intrusion of a sill free to expand radially, with shape and dimensions which vary with time. The intrusion process is controlled by the elastic response of the rock plate above the sill, which bends because of the intrusion, and by gravity, that drives the magma towards the zones where the thickness of the sill is smaller. We calculated the stress field in the plate rock above the sill. We found that at the bottom of the rock plate above the sill the maximum intensity of tensile stress is concentrated at the front of the sill and spreads radially with it, over time. For this reason, we think that the front of the spreading sill is prone to open for eruptive vents. Even in the central area of the sill the intensity of stress is relatively high, but at the base of the rock plate stress is compressive. Under isothermal conditions, the stress soon reaches its maximum value (time interval depending on the model parameters) and then decreases over time during the intrusion. However, if we consider the effect of the cooling of magma, with the temperature which decreases with time and the viscosity that increases, we'll find that the stress in the rock above the sill gradually increases with time and becomes higher than in isothermal case. In order to investigate the role of the physical properties of magma and rock above the sill in the generation of the stress field we have carried out different simulations by varying the viscosity of magma and the rigidity of the rock and found that high viscosity magma produces a relatively high stress intensity, as well as a high rock rigidity does.

Laser spectroscopy for totally non-intrusive detection of oxygen in modified atmosphere food packages

NASA Astrophysics Data System (ADS)

Cocola, L.; Fedel, M.; Poletto, L.; Tondello, G.

2015-04-01

A device for measuring the oxygen concentration inside packages in modified atmosphere working in a completely non-intrusive way has been developed and tested. The device uses tunable diode laser spectroscopy in a geometry similar to a short distance LIDAR: A laser beam is sent through the top film of a food package, and the absorption is measured by detecting the light scattered by the bottom of the container or by a portion of the food herein contained. The device can operate completely in a contactless way from the package, and the distances of absorption both outside and inside the package are measured with a triangulation system. The performances of the device have been tested for various types of containers, and absolute values for the oxygen concentration have been compared with standard albeit destructive measurements.

Research on regional intrusion prevention and control system based on target tracking

NASA Astrophysics Data System (ADS)

Liu, Yanfei; Wang, Jieling; Jiang, Ke; He, Yanhui; Wu, Zhilin

2017-08-01

In view of the fact that China’s border is very long and the border prevention and control measures are single, we designed a regional intrusion prevention and control system which based on target-tracking. The system consists of four parts: solar panel, radar, electro-optical equipment, unmanned aerial vehicle and intelligent tracking platform. The solar panel provides independent power for the entire system. The radar detects the target in real time and realizes the high precision positioning of suspicious targets, then through the linkage of electro-optical equipment, it can achieve full-time automatic precise tracking of targets. When the target appears within the range of detection, the drone will be launched to continue the tracking. The system is mainly to realize the full time, full coverage, whole process integration and active realtime control of the border area.

Implementation of Multipattern String Matching Accelerated with GPU for Intrusion Detection System

NASA Astrophysics Data System (ADS)

Nehemia, Rangga; Lim, Charles; Galinium, Maulahikmah; Rinaldi Widianto, Ahmad

2017-04-01

As Internet-related security threats continue to increase in terms of volume and sophistication, existing Intrusion Detection System is also being challenged to cope with the current Internet development. Multi Pattern String Matching algorithm accelerated with Graphical Processing Unit is being utilized to improve the packet scanning performance of the IDS. This paper implements a Multi Pattern String Matching algorithm, also called Parallel Failureless Aho Corasick accelerated with GPU to improve the performance of IDS. OpenCL library is used to allow the IDS to support various GPU, including popular GPU such as NVIDIA and AMD, used in our research. The experiment result shows that the application of Multi Pattern String Matching using GPU accelerated platform provides a speed up, by up to 141% in term of throughput compared to the previous research.

A proposed ethical framework for vaccine mandates: competing values and the case of HPV.

PubMed

Field, Robert I; Caplan, Arthur L

2008-06-01

Debates over vaccine mandates raise intense emotions, as reflected in the current controversy over whether to mandate the vaccine against human papilloma virus (HPV), the virus that can cause cervical cancer. Public health ethics so far has failed to facilitate meaningful dialogue between the opposing sides. When stripped of its emotional charge, the debate can be framed as a contest between competing ethical values. This framework can be conceptualized graphically as a conflict between autonomy on the one hand, which militates against government intrusion, and beneficence, utilitarianism, justice, and nonmaleficence on the other, which may lend support to intervention. When applied to the HPV vaccine, this framework would support a mandate based on utilitarianism, if certain conditions are met and if herd immunity is a realistic objective.

High-resolution seismic imaging of the Kevitsa mafic-ultramafic Cu-Ni-PGE hosted intrusion, northern Finland

NASA Astrophysics Data System (ADS)

Malehmir, Alireza; Koivisto, Emilia; Wjins, Chris; Tryggvason, Ari; Juhlin, Christopher

2014-05-01

Kevitsa, in northern Finland, is a large nickel/copper ore body hosted by a massive mafic-ultramafic intrusion with measured and indicated resources of 240 million tons (cutoff 0.1%) grading 0.30% Ni and 0.41% Cu. Mining started in 2012 with an open pit that will extend down to about 550-600 m depth. The expected mine life is more than 20 years. Numerous boreholes are available in the area, but the majority of them are shallow and do not provide a comprehensive understanding of the dimensions of the intrusion. However, a number of boreholes do penetrate the basal contact of the intrusion. Most of these are also shallow and concentrated at the edge of the intrusion. A better knowledge of the geometry of the intrusion would provide a framework for near-mine and deep exploration in the area, but also a better understanding of the geology. Exact mapping of the basal contact of the intrusion would also provide an exploration target for the contact-type mineralization that is often more massive and richer in Ni-Cu than the disseminated mineralization away from the contact. With the objective of better characterizing the intrusion, a series of 2D profiles were acquired followed by a 3D reflection survey that covered an area of about 3 km by 3 km. Even though the geology is complex and the seismic P-wave velocity ranges between 5 to 8 km/s, conventional processing results show gently- to steeply-dipping reflections from depths of approximately 2 km to as shallow as 100 m. Many of these reflections are interpreted to originate from either fault systems or internal magmatic layering within the Kevitsa main intrusion. Correlations between the 3D surface seismic data and VSP data, based upon time shifts or phase changes along the reflections, support the interpretation that numerous faults are imaged in the volume. Some of these faults cross the planned open-pit mine at depths of about 300-500 m, and it is, therefore, critical to map them for mine planning. The seismic 3D volume better represents the geology around the mine and in the vicinity of the known deposit, while the 2D seismic profiles were designed to provide information on larger-scale structures in the area. Both the 2D and 3D seismic data were used to create a 3D lithological and structural model of the entire complex. Information on the dimensions of the ore-bearing Kevitsa intrusion can be used for more effective exploration in the area. The base of the intrusion is particularly clear in the northern and western sectors of the seismic data. Toward the east, the base is mostly defined by disruption of the reflectors internal to the intrusion. Recent tests using prestack migration methods on the 3D data show partial improvements in the image, especially at shallow depths. 3D seismic tomography has also been performed and the results indicate low velocity zones crossing the open pit that can be interpreted as zones of weakness. Future studies will focus on using the tomography results as the input velocity field for prestack depth migration of the 3D data and also improving the 3D geological model of the study area. Acknowledgments: FQM, GTK, HiSeis and Vibrometric

Distributed fiber optic moisture intrusion sensing system

DOEpatents

Weiss, Jonathan D.

2003-06-24

Method and system for monitoring and identifying moisture intrusion in soil such as is contained in landfills housing radioactive and/or hazardous waste. The invention utilizes the principle that moist or wet soil has a higher thermal conductance than dry soil. The invention employs optical time delay reflectometry in connection with a distributed temperature sensing system together with heating means in order to identify discrete areas within a volume of soil wherein temperature is lower. According to the invention an optical element and, optionally, a heating element may be included in a cable or other similar structure and arranged in a serpentine fashion within a volume of soil to achieve efficient temperature detection across a large area or three dimensional volume of soil. Remediation, moisture countermeasures, or other responsive action may then be coordinated based on the assumption that cooler regions within a soil volume may signal moisture intrusion where those regions are located.

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

2015-03-01

We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

Subsurface Intrusion Detection System

DTIC Science & Technology

2014-02-25

deployed along the boundary. The outputs of the vibration sensors are taken as an indication of underground activity and can therefore be used to...for detecting underground activity. The system has a first sensor located at a first depth below the surface of the ground and a second sensor...and the second sensor has a second output indicative of vibrations at the second depth. A processor adapted to detect underground activity compares

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection

Potential for portal detection of human chemical and biological contamination

NASA Astrophysics Data System (ADS)

Settles, Gary S.; McGann, William J.

2001-08-01

The walk-through metal-detection portal is a paradigm of non-intrusive passenger screening in aviation security. Modern explosive detection portals based on this paradigm will soon appear in airports. This paper suggests that the airborne trace detection technology developed for that purpose can also be adapted to human chemical and biological contamination. The waste heat of the human body produces a rising warm-air sheath of 50-80 liters/sec known as the human thermal plume. Contained within this plume are hundreds of bioeffluents from perspiration and breath, and millions of skin flakes. Since early medicine, the airborne human scent was used in the diagnosis of disease. Recent examples also include toxicity and substance abuse, but this approach has never been quantified. The appearance of new bioeffluents or subtle changes in the steady-state may signal the onset of a chemical/biological attack. Portal sampling of the human thermal plume is suggested, followed by a pre-concentration step and the detection of the attacking agent or the early human response. The ability to detect nanogram levels of explosive trace contamination this way was already demonstrated. Key advantages of the portal approach are its rapidity and non-intrusiveness, and the advantage that it does not require the traditional bodily fluid or tissue sampling.

SUPPLEMENT TO EPA COMPENDIUM METHOD TO-15 - REDUCTION OF METHOD DETECTION LIMITS TO MEET VAPOR INTRUSION MONITORING NEEDS

EPA Science Inventory

The Supplement to EPA Compendium Method TO-15 provides guidance for reducing the method detection limit (MDL) for the compound 1,1- dichloroethene (1,1-DCE) and for other volatile organic compounds (VOCs) from 0.5 ppbv, as cited in Method TO-15, to much lower concentrations. R...

SUPPLEMENT TO EPA COMPENDIUM METHOD TO-15 - REDUCTION OF METHOD DETECTION LIMITS TO MEET VAPOR INTRUSION MONITORING NEEDS

EPA Science Inventory

The Supplement to EPA Compendium Method TO-15 provides guidance for reducing the method detection limit (MDL) for the compound 1,1-dichloroethene (1,1-DCE) and for other volatile organic compounds (VOCs) from 0.5 parts per billion by volume (ppbv), as cited in Method TO-15, to ...

Final work plan : supplemental upward vapor intrusion investigation at the former CCC/USDA grain storage facility in Hanover, Kansas.

DOE Office of Scientific and Technical Information (OSTI.GOV)

LaFreniere, L. M.; Environmental Science Division

The Commodity Credit Corporation (CCC), an agency of the U.S. Department of Agriculture (USDA), operated a grain storage facility at the northeastern edge of the city of Hanover, Kansas, from 1950 until the early 1970s. During this time, commercial grain fumigants containing carbon tetrachloride were in common use by the grain storage industry to preserve grain in their facilities. In February 1998, trace to low levels of carbon tetrachloride (below the maximum contaminant level [MCL] of 5.0 {micro}g/L) were detected in two private wells near the former grain storage facility at Hanover, as part of a statewide USDA private wellmore » sampling program that was implemented by the Kansas Department of Health and Environment (KDHE) near former CCC/USDA facilities. In 2007, the CCC/USDA conducted near-surface soil sampling at 61 locations and also sampled indoor air at nine residences on or adjacent to its former Hanover facility to address the residents concerns regarding vapor intrusion. Low levels of carbon tetrachloride were detected at four of the nine homes. The results were submitted to the KDHE in October 2007 (Argonne 2007). On the basis of the results, the KDHE requested sub-slab sampling and/or indoor air sampling (KDHE 2007). This Work Plan describes, in detail, the proposed additional scope of work requested by the KDHE and has been developed as a supplement to the comprehensive site investigation work plan that is pending (Argonne 2008). Indoor air samples collected previously from four homes at Hanover were shown to contain the carbon tetrachloride at low concentrations (Table 2.1). It cannot be concluded from these previous data that the source of the detected carbon tetrachloride is vapor intrusion attributable to former grain storage operations of the CCC/USDA at Hanover. The technical objective of the vapor intrusion investigation described here is to assess the risk to human health due to the potential for upward migration of carbon tetrachloride and chloroform into four homes located on or adjacent to the former CCC/USDA facility. The technical objective will be accomplished by collecting sub-slab vapor samples. The preliminary data collected during the July 2007 investigation did not fully address the source of or migration pathway for the carbon tetrachloride detected in the four homes. The scope of work proposed here will generate additional data needed to help evaluate whether the source of the detected carbon tetrachloride is vapor intrusion attributable to activities of the CCC/USDA. The additional vapor sampling at Hanover will be performed, on behalf of the CCC/USDA, by the Environmental Science Division of Argonne National Laboratory and H&P Mobile Geochemistry of San Diego (http://www.handpmg.com). Argonne is a nonprofit, multidisciplinary research center operated by UChicago Argonne, LLC, for the U.S. Department of Energy (DOE). The CCC/USDA has entered into an interagency agreement with DOE, under which Argonne provides technical assistance to the CCC/USDA with environmental site characterization and remediation at its former grain storage facilities. The professional staff members of H&P Mobile Geochemistry are nationally leading experts in soil gas sampling and vapor intrusion investigations.« less

IDAS : ITS Deployment Analysis System

DOT National Transportation Integrated Search

1997-05-01

This report documents the activities and results of a 2-year test of non-intrusive traffic detection technologies. The test was initiated by the Federal Highway Administration (FHWA) and conducted by the Minnesota Department of Transportation (Mn/DOT...

RTO Technical Report: A Quarterly Listing

NASA Technical Reports Server (NTRS)

2002-01-01

This is a listing of recent unclassified RTO technical publications processed by the NASA Center for AeroSpace Information from April 1,2002 through June 30, 2002. Topics covered include: intrusion detection and design loads for aircraft.

Effectiveness of Audible Warning Devices on Emergency Vehicles.

DOT National Transportation Integrated Search

1977-08-01

The purpose of the study was to examine the effectiveness of audible warning devices (AWD's) on emergency vehicles in terms of aural detectability. Community noise intrusion and opportunities for AWD optimization were also investigated. Measurements ...

Relationship between vapor intrusion and human exposure to trichloroethylene.

PubMed

Archer, Natalie P; Bradford, Carrie M; Villanacci, John F; Crain, Neil E; Corsi, Richard L; Chambers, David M; Burk, Tonia; Blount, Benjamin C

2015-01-01

Trichloroethylene (TCE) in groundwater has the potential to volatilize through soil into indoor air where it can be inhaled. The purpose of this study was to determine whether individuals living above TCE-contaminated groundwater are exposed to TCE through vapor intrusion. We examined associations between TCE concentrations in various environmental media and TCE concentrations in residents. For this assessment, indoor air, outdoor air, soil gas, and tap water samples were collected in and around 36 randomly selected homes; blood samples were collected from 63 residents of these homes. Additionally, a completed exposure survey was collected from each participant. Environmental and blood samples were analyzed for TCE. Mixed model multiple linear regression analyses were performed to determine associations between TCE in residents' blood and TCE in indoor air, outdoor air, and soil gas. Blood TCE concentrations were above the limit of quantitation (LOQ; ≥ 0.012 µg L(-1)) in 17.5% of the blood samples. Of the 36 homes, 54.3%, 47.2%, and >84% had detectable concentrations of TCE in indoor air, outdoor air, and soil gas, respectively. Both indoor air and soil gas concentrations were statistically significantly positively associated with participants' blood concentrations (P = 0.0002 and P = 0.04, respectively). Geometric mean blood concentrations of residents from homes with indoor air concentrations of >1.6 µg m(-3) were approximately 50 times higher than geometric mean blood TCE concentrations in participants from homes with no detectable TCE in indoor air (P < .0001; 95% CI 10.4-236.4). This study confirms the occurrence of vapor intrusion and demonstrates the magnitude of exposure from vapor intrusion of TCE in a residential setting.

Relationship between vapor intrusion and human exposure to trichloroethylene

PubMed Central

ARCHER, NATALIE P.; BRADFORD, CARRIE M.; VILLANACCI, JOHN F.; CRAIN, NEIL E.; CORSI, RICHARD L.; CHAMBERS, DAVID M.; BURK, TONIA; BLOUNT, BENJAMIN C.

2015-01-01

Trichloroethylene (TCE) in groundwater has the potential to volatilize through soil into indoor air where it can be inhaled. The purpose of this study was to determine whether individuals living above TCE-contaminated groundwater are exposed to TCE through vapor intrusion. We examined associations between TCE concentrations in various environmental media and TCE concentrations in residents. For this assessment, indoor air, outdoor air, soil gas, and tap water samples were collected in and around 36 randomly selected homes; blood samples were collected from 63 residents of these homes. Additionally, a completed exposure survey was collected from each participant. Environmental and blood samples were analyzed for TCE. Mixed model multiple linear regression analyses were performed to determine associations between TCE in residents' blood and TCE in indoor air, outdoor air, and soil gas. Blood TCE concentrations were above the limit of quantitation (LOQ; ≥0.012 μg/L) in 17.5% of the blood samples. Of the 36 homes, 54.3%, 47.2%, and >84% had detectable concentrations of TCE in indoor air, outdoor air, and soil gas, respectively. Both indoor air and soil gas concentrations were statistically significantly positively associated with participants' blood concentrations (p=0.0002 and p=0.04, respectively). Geometric mean blood concentrations of residents from homes with indoor air concentrations of >1.6 μg/m3 were approximately 50 times higher than geometric mean blood TCE concentrations in participants from homes with no detectable TCE in indoor air (p<.0001; 95% CI 10.4 – 236.4). This study confirms the occurrence of vapor intrusion and demonstrates the magnitude of exposure from vapor intrusion of TCE in a residential setting. PMID:26259926

ODOT research news : winter quarter 2003.

DOT National Transportation Integrated Search

2003-01-01

The newsletter includes: : 1) Cracked Bridges; : 2) Research Outreach; : 3) LTPP Update: A Long Shot Pays Off; : 4) Railroad Crossing Intrusion Detection Update; : 5) Guiding Drivers through Work Zones; : 6) New Projects to start in July; : and other...

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

High-speed and high-fidelity system and method for collecting network traffic

DOEpatents

Weigle, Eric H [Los Alamos, NM

2010-08-24

A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.

Intrusion detection using secure signatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, Trent Darnel; Haile, Jedediah

A method and device for intrusion detection using secure signatures comprising capturing network data. A search hash value, value employing at least one one-way function, is generated from the captured network data using a first hash function. The presence of a search hash value match in a secure signature table comprising search hash values and an encrypted rule is determined. After determining a search hash value match, a decryption key is generated from the captured network data using a second hash function, a hash function different form the first hash function. One or more of the encrypted rules of themore » secure signatures table having a hash value equal to the generated search hash value are then decrypted using the generated decryption key. The one or more decrypted secure signature rules are then processed for a match and one or more user notifications are deployed if a match is identified.« less

Critical Infrastructure Protection and Resilience Literature Survey: Modeling and Simulation

DTIC Science & Technology

2014-11-01

2013 Page 34 of 63 Below the yellow set is a purple cluster bringing together detection , anomaly , intrusion, sensors, monitoring and alerting (early...hazards and threats to security56 Water ADWICE, PSS®SINCAL ADWICE for real-time anomaly detection in water management systems57 One tool that...Systems. Cybernetics and Information Technologies. 2008;8(4):57-68. 57. Raciti M, Cucurull J, Nadjm-Tehrani S. Anomaly detection in water management

Modified Policy-Delphi study for exploring obesity prevention priorities

PubMed Central

Haynes, Emily; Palermo, Claire; Reidlinger, Dianne P

2016-01-01

Introduction Until now, industry and government stakeholders have dominated public discourse about policy options for obesity. While consumer involvement in health service delivery and research has been embraced, methods which engage consumers in health policy development are lacking. Conflicting priorities have generated ethical concern around obesity policy. The concept of ‘intrusiveness’ has been applied to policy decisions in the UK, whereby ethical implications are considered through level of intrusiveness to choice; however, the concept has also been used to avert government regulation to address obesity. The concept of intrusiveness has not been explored from a stakeholder's perspective. The aim is to investigate the relevance of intrusiveness and autonomy to health policy development, and to explore consensus on obesity policy priorities of under-represented stakeholders. Methods and analysis The Policy-Delphi technique will be modified using the James Lind Alliance approach to collaborative priority setting. A total of 60 participants will be recruited to represent three stakeholder groups in the Australian context: consumers, public health practitioners and policymakers. A three-round online Policy-Delphi survey will be undertaken. Participants will prioritise options informed by submissions to the 2009 Australian Government Inquiry into Obesity, and rate the intrusiveness of those proposed. An additional round will use qualitative methods in a face-to-face discussion group to explore stakeholder perceptions of the intrusiveness of options. The novelty of this methodology will redress the balance by bringing the consumer voice forward to identify ethically acceptable obesity policy options. Ethics and dissemination Ethical approval was granted by the Bond University Health Research Ethics Committee. The findings will inform development of a conceptual framework for analysing and prioritising obesity policy options, which will be relevant internationally and to ethical considerations of wider public health issues. The findings will be disseminated through peer-reviewed publications, conference presentations and collaborative platforms of policy and science. PMID:27601495

Impact of zeolite-Y framework on the geometry and reactivity of Ru (III) benzimidazole complexes - A DFT study

NASA Astrophysics Data System (ADS)

Selvaraj, Tamilmani; Rajalingam, Renganathan; Balasubramanian, Viswanathan

2018-03-01

A detailed comparative Density Functional Theory (DFT) study is made to understand the structural changes of the guest complex due to steric and electronic interactions with the host framework. In this study, Ru(III) benzimidazole and 2- ethyl Ru(III) benzimidazole complexes encapsulated in a supercage of zeolite Y. The zeolitic framework integrity is not disturbed by the intrusion of the large guest complex. A blue shift in the d-d transition observed in the UV-Visible spectroscopic studies of the zeolite encapsulated complexes and they shows a higher catalytic efficiency. Encapsulation of zeolite matrix makes the metal center more viable to nucleophilic attack and favors the phenol oxidation reaction. Based on the theoretical calculations, transition states and structures of reaction intermediates involved in the catalytic cycles are derived.

Intrusion Pattern of the Offshore Kuroshio Branch Current and Its Effects on Nutrient Contributions in the East China Sea

NASA Astrophysics Data System (ADS)

Wang, Wentao; Yu, Zhiming; Song, Xiuxian; Yuan, Yongquan; Wu, Zaixing; Zhou, Peng; Cao, Xihua

2018-03-01

During the autumn season of 2014 (October-November), nutrient samples and nitrogen and oxygen isotope samples from the East China Sea (ECS) were collected and analyzed, and auxiliary physical parameters were determined. Distinctive high-salinity water column conditions with significant haloclines and pycnoclines similar to those observed during the spring were detected at the bottom of the ECS during the autumn. These water column conditions were attributed to the intrusion of the Kuroshio Subsurface Water (KSSW), which then separated into two currents, including the Offshore Kuroshio Branch Current (OKBC). Compared with spring, this intrusion transported higher phosphorus (P) concentrations onto the ECS continental shelf in autumn. However, according to multiple analyses, biogeochemical nitrogen processes are unable to explain the variations in the P concentrations (increase) while assuming that each distinctive water column is consistent. Identifying the water columns by their salinities and P concentrations revealed that the northern ECS water column was similar to the deep KSSW while the southern ECS water column was similar to the shallow KSSW. Therefore, we speculate that the distinctions among the seasonal variations of P-enriched water masses were attributable to the different intrusion positions of the Kuroshio. The shift of the KSSW intrusion location moved toward the northeast during the autumn relative to the spring. This shift, which was proved by the oceanic vortex data, caused the deeper KSSW water upwelled to the ECS and formed the OKBC, thereby supplying additional P during the autumn.

Resolving the architecture of monogenetic feeder systems from exposures of extinct volcanic fields

NASA Astrophysics Data System (ADS)

Muirhead, J.; Van Eaton, A. R.; Re, G.; White, J. D. L.; Ort, M. H.

2016-12-01

Monogenetic volcanic fields pose hazards to a number of major cities worldwide. During an eruption, the evolution of the intrusive feeder network modulates eruption behavior and location, as well as the warning signs of impending activity. However, historical examples of monogenetic eruptions are rare, particularly those monitored with the modern tools required to constrain the geometry and interconnectivity of subsurface intrusive feeders (e.g., InSAR, GPS). Geologic exposures in extinct fields around the Colorado Plateau provide clues to the geometry of shallow intrusions (<1000 m depth) that feed monogenetic volcanoes. We present field- and satellite-based observations of exposed intrusions in the Hopi Buttes volcanic field (Arizona), which reveal that many eruptions were fed by interconnected dike-sill systems. Results from the Hopi Buttes show that volcanic cone alignment studies are biased to the identification of dike intrusions, and thereby neglect the important contributions of sills to shallow feeder systems. For example, estimates of intruded volumes in fields exhumed by uplift and erosion in Utah and Arizona show that sills make up 30 - 92% of the shallow intruded volume within 1000 m of the paleosurface. By transporting magma toward and away from eruptive conduits, these sills likely played a role in modulating eruption styles (e.g., explosive vs effusive) and controlling lateral vent migrations. Sill transitions at Hopi Buttes would have produced detectable surface uplifts, and illustrate the importance of geological studies for informing interpretations of geodetic and seismological data during volcanic crises.

Non-Intrusive Magneto-Optic Detecting System for Investigations of Air Switching Arcs

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Zhang, Guogang; Dong, Jinlong; Liu, Wanying; Geng, Yingsan

2014-07-01

In current investigations of electric arc plasmas, experiments based on modern testing technology play an important role. To enrich the testing methods and contribute to the understanding and grasping of the inherent mechanism of air switching arcs, in this paper, a non-intrusive detecting system is described that combines the magneto-optic imaging (MOI) technique with the solution to inverse electromagnetic problems. The detecting system works in a sequence of main steps as follows: MOI of the variation of the arc flux density over a plane, magnetic field information extracted from the magneto-optic (MO) images, arc current density distribution and spatial pattern reconstruction by inverting the resulting field data. Correspondingly, in the system, an MOI set-up is designed based on the Faraday effect and the polarization properties of light, and an intelligent inversion algorithm is proposed that involves simulated annealing (SA). Experiments were carried out for high current (2 kA RMS) discharge cases in a typical low-voltage switchgear. The results show that the MO detection system possesses the advantages of visualization, high resolution and response, and electrical insulation, which provides a novel diagnostics tool for further studies of the arc.

Shape-based human detection for threat assessment

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Zhan, Pengcheng; Thomas, Aaron; Schoenberger, Robert B.

2004-07-01

Detection of intrusions for early threat assessment requires the capability of distinguishing whether the intrusion is a human, an animal, or other objects. Most low-cost security systems use simple electronic motion detection sensors to monitor motion or the location of objects within the perimeter. Although cost effective, these systems suffer from high rates of false alarm, especially when monitoring open environments. Any moving objects including animals can falsely trigger the security system. Other security systems that utilize video equipment require human interpretation of the scene in order to make real-time threat assessment. Shape-based human detection technique has been developed for accurate early threat assessments for open and remote environment. Potential threats are isolated from the static background scene using differential motion analysis and contours of the intruding objects are extracted for shape analysis. Contour points are simplified by removing redundant points connecting short and straight line segments and preserving only those with shape significance. Contours are represented in tangent space for comparison with shapes stored in database. Power cepstrum technique has been developed to search for the best matched contour in database and to distinguish a human from other objects from different viewing angles and distances.

A conceptual framework and monitoring strategy for movement of saltwater in the coastal plain aquifer system of Virginia

USGS Publications Warehouse

Mcfarland, E. Randolph

2015-09-04

The saltwater-movement monitoring strategy is limited and constrained. Relative monitoring needs among groundwater-production wells, and construction of observation wells, depend on the accuracy of previously mapped groundwater chloride iso-concentration surfaces. Production wells in similar proximity to saltwater can differ in aquifer hydraulic conductivity, rates of withdrawal, and screened-interval lengths. Only production wells making withdrawals reported to the Virginia Department of Environmental Quality have been accounted for; undocumented production wells can result in spurious changes in groundwater chloride concentration. Upconing observation wells should be as close as possible to corresponding production wells, so long as production wells are not damaged by borehole deviation. Projected locations of some lateral-intrusion observation wells may be precluded and require adjustment. Depths of upconing and lateral-intrusion observation wells may also require adjustment to be within the same aquifer as their corresponding production wells. Existing unused wells can be adapted as observation wells if differences from specified locations and construction are kept to a minimum and are accounted for. Where multiple production wells are in proximity, a modified monitoring approach may be needed to determine their net effect on changes in chloride concentration, and may require more than one lateral-intrusion observation well depending on the vertical positions of production-well screened intervals.

Gaining the necessary geologic, hydrologic, and geochemical understanding for additional brackish groundwater development, coastal San Diego, California, USA

USGS Publications Warehouse

Danskin, Wesley R.

2012-01-01

Local water agencies and the United States Geological Survey are using a combination of techniques to better understand the scant freshwater resources and the much more abundant brackish resources in coastal San Diego, California, USA. Techniques include installation of multiple-depth monitoring well sites; geologic and paleontological analysis of drill cuttings; geophysical logging to identify formations and possible seawater intrusion; sampling of pore-water obtained from cores; analysis of chemical constituents including trace elements and isotopes; and use of scoping models including a three-dimensional geologic framework model, rainfall-runoff model, regional groundwater flow model, and coastal density-dependent groundwater flow model. Results show that most fresh groundwater was recharged during the last glacial period and that the coastal aquifer has had recurring intrusions of fresh and saline water. These intrusions disguise the source, flowpaths, and history of ground water near the coast. The flow system includes a freshwater lens resting on brackish water; a 100-meter-thick flowtube of freshwater discharging under brackish estuarine water and above highly saline water; and broad areas of fine-grained coastal sediment filled with fairly uniform brackish water. Stable isotopes of hydrogen and oxygen indicate the recharged water flows through many kilometers of fractured crystalline rock before entering the narrow coastal aquifer.

A network security monitor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heberlein, L.T.; Dias, G.V.; Levitt, K.N.

1989-11-01

The study of security in computer networks is a rapidly growing area of interest because of the proliferation of networks and the paucity of security measures in most current networks. Since most networks consist of a collection of inter-connected local area networks (LANs), this paper concentrates on the security-related issues in a single broadcast LAN such as Ethernet. Specifically, we formalize various possible network attacks and outline methods of detecting them. Our basic strategy is to develop profiles of usage of network resources and then compare current usage patterns with the historical profile to determine possible security violations. Thus, ourmore » work is similar to the host-based intrusion-detection systems such as SRI's IDES. Different from such systems, however, is our use of a hierarchical model to refine the focus of the intrusion-detection mechanism. We also report on the development of our experimental LAN monitor currently under implementation. Several network attacks have been simulated and results on how the monitor has been able to detect these attacks are also analyzed. Initial results demonstrate that many network attacks are detectable with our monitor, although it can surely be defeated. Current work is focusing on the integration of network monitoring with host-based techniques. 20 refs., 2 figs.« less

Low-Cost Ground Sensor Network for Intrusion Detection

DTIC Science & Technology

2017-09-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release. Distribution is unlimited. LOW- COST GROUND...Gurminder Singh THIS PAGE INTENTIONALLY LEFT BLANK i REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this...

Detailed Field Investigation of Vapor Intrusion Processes

DTIC Science & Technology

2008-08-01

difluoroethane DQO data quality objective ESTCP Environmental Security Technology Certification Program HCl hydrochloric acid OU-5 Operable Unit...impacted by significant leakage of ambient air. Some leak tracer compounds such as difluoroethane (DFA) and isopropyl alcohol may cause elevated detection

Early Warning Systems Assure Safe Schools

ERIC Educational Resources Information Center

Greenhalgh, John

1973-01-01

Fairfield, Connecticut, public schools are protected by an automatic fire detection system covering every area of every building through an electric monitor. An intrusion alarm system that relies primarily on pulsed infra-red beams protects the plant investment. (Author/MF)

A hierarchical detection method in external communication for self-driving vehicles based on TDMA.

PubMed

Alheeti, Khattab M Ali; Al-Ani, Muzhir Shaban; McDonald-Maier, Klaus

2018-01-01

Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms.

Watchdog Sensor Network with Multi-Stage RF Signal Identification and Cooperative Intrusion Detection

DTIC Science & Technology

2012-03-01

detection and physical layer authentication in mobile Ad Hoc networks and wireless sensor networks (WSNs) have been investigated. Résume Le rapport...IEEE 802.16 d and e (WiMAX); (b) IEEE 802.11 (Wi-Fi) family of a, b, g, n, and s (c) Sensor networks based on IEEE 802.15.4: Wireless USB, Bluetooth... sensor network are investigated for standard compatible wireless signals. The proposed signal existence detection and identification process consists

Distributed intrusion monitoring system with fiber link backup and on-line fault diagnosis functions

NASA Astrophysics Data System (ADS)

Xu, Jiwei; Wu, Huijuan; Xiao, Shunkun

2014-12-01

A novel multi-channel distributed optical fiber intrusion monitoring system with smart fiber link backup and on-line fault diagnosis functions was proposed. A 1× N optical switch was intelligently controlled by a peripheral interface controller (PIC) to expand the fiber link from one channel to several ones to lower the cost of the long or ultra-long distance intrusion monitoring system and also to strengthen the intelligent monitoring link backup function. At the same time, a sliding window auto-correlation method was presented to identify and locate the broken or fault point of the cable. The experimental results showed that the proposed multi-channel system performed well especially whenever any a broken cable was detected. It could locate the broken or fault point by itself accurately and switch to its backup sensing link immediately to ensure the security system to operate stably without a minute idling. And it was successfully applied in a field test for security monitoring of the 220-km-length national borderline in China.

Report: Improvements Needed in EPA’s Network Traffic Management Practices

EPA Pesticide Factsheets

Report #11-P-0159, March 14, 2011. OEI does not have consistent, repeatable intrusion detection system monitoring practices in place, which inhibits EPA’s ability to monitor unusual network activity and thus protect Agency systems and associated data.

Off-road axle detection sensor (ORADS) : executive summary, April 2001.

DOT National Transportation Integrated Search

2001-04-01

Spectra Research has developed a non-intrusive lane monitoring sensor which can be used to measure and classify vehicular traffic over multiple lane roadways. This sensor employs dual beam laser radar (LADAR) that accurately measures location and pas...

Off-road axle detection sensor (ORADS) : final report, April 2001.

DOT National Transportation Integrated Search

2001-04-01

Spectra Research has developed a non-intrusive lane monitoring sensor which can be used to measure and classify vehicular traffic over multiple lane roadways. This sensor employs dual beam laser radar (LADAR) that accurately measures location and pas...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2014 CFR

2014-07-01

... operational limitations; (vi) Methods of conducting audits, inspection and control and monitoring techniques... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition...) Techniques used to circumvent security measures; (xii) Methods of physical screening and non-intrusive...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2013 CFR

2013-07-01

... operational limitations; (vi) Methods of conducting audits, inspection and control and monitoring techniques... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition...) Techniques used to circumvent security measures; (xii) Methods of physical screening and non-intrusive...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2012 CFR

2012-07-01

... operational limitations; (vi) Methods of conducting audits, inspection and control and monitoring techniques... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition...) Techniques used to circumvent security measures; (xii) Methods of physical screening and non-intrusive...

75 FR 76426 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-08

..., access control lists, file system permissions, intrusion detection and prevention systems and log..., address, mailing address, country, organization, phone, fax, mobile, pager, Defense Switched Network (DSN..., address, mailing address, country, organization, phone, fax, mobile, pager, Defense Switched Network (DSN...

Application of Remote-Sensing Observations for Detecting Patterns of Localization of Cu-Ni Mineralization of the Norilsk Ore Region

NASA Astrophysics Data System (ADS)

Milovsky, G. A.; Ishmukhametova, V. T.; Shemyakina, E. M.

2017-12-01

The methods of a complex analysis of materials of space, gravimetric, and magnetometric surveys were developed on the basis of a study of reference fields of the Norilsk ore region (Imangda, etc.) for detection patterns of the localization of Cu-Ni (with PGMs) mineralization in intrusive complexes of the northwestern frame of the Siberian Platform.

Information Assurance Technology Analysis Center Information Assurance Tools Report Intrusion Detection

DTIC Science & Technology

1998-01-01

such as central processing unit (CPU) usage, disk input/output (I/O), memory usage, user activity, and number of logins attempted. The statistics... EMERALD Commercial anomaly detection, system monitoring SRI porras@csl.sri.com www.csl.sri.com/ emerald /index. html Gabriel Commercial system...sensors, it starts to protect the network with minimal configuration and maximum intelligence. T 11 EMERALD TITLE EMERALD (Event Monitoring

Collaborative Point Paper on Border Surveillance Technology

DTIC Science & Technology

2007-06-01

Systems PLC LORHIS (Long Range Hyperspectral Imaging System ) can be configured for either manned or unmanned aircraft to automatically detect and...Airships, and/or Aerostats, (RF, Electro-Optical, Infrared, Video) • Land- based Sensor Systems (Attended/Mobile and Unattended: e.g., CCD, Motion, Acoustic...electronic surveillance technologies for intrusion detection and warning. These ground- based systems are primarily short-range, up to around 500 meters

Large Scale System Defense

DTIC Science & Technology

2008-10-01

AD); Aeolos, a distributed intrusion detection and event correlation infrastructure; STAND, a training-set sanitization technique applicable to ADs...UU 18. NUMBER OF PAGES 25 19a. NAME OF RESPONSIBLE PERSON Frank H. Born a. REPORT U b. ABSTRACT U c . THIS PAGE U 19b. TELEPHONE...Summary of findings 2 (a) Automatic Patch Generation 2 (b) Better Patch Management 2 ( c ) Artificial Diversity 3 (d) Distributed Anomaly Detection 3

Developments toward a Low-Cost Approach for Long-Term, Unattended Vapor Intrusion Monitoring

PubMed Central

Tolley, William K.

2014-01-01

There are over 450,000 sites contaminated by chemicals in the US. This large number of contaminated sites and the speed of subsurface migration of chemicals pose considerable risk to nearby residences and commercial buildings. The high costs for monitoring around these site stem from the labor involved in placing and replacing the passive sorbent vapor samplers and the resultant laboratory analysis. This monitoring produces sparse data sets that do not track temporal changes well. To substantially reduce costs and better track exposures, less costly, unattended systems for monitoring soil gases and vapor intrusion into homes and businesses are desirable to aid in the remediation of contaminated sites. This paper describes progress toward the development of an inexpensive system specifically for monitoring vapor intrusion; the system can operate repeatedly without user intervention with low detection limits (1 × 10−9, or 1 part-per-billion). Targeted analytes include chlorinated hydrocarbons (dichloroethylene, trichloroethane, trichloroethylene, and perchloroethylene) and benzene. The system consists of a trap-and-purge preconcentrator for vapor collection in conjunction with a compact gas chromatography instrument to separate individual compounds. Chemical detection is accomplished with an array of chemicapacitors and a metal-oxide semiconductor combustibles sensor. Both the preconcentrator and the chromatography column are resistively heated. All components are compatible with ambient air, which serves as the carrier gas for the gas chromatography and detectors. PMID:24903107

Intrusion Triggering of Explosive Eruptions: Lessons Learned from EYJAFJALLAJÖKULL 2010 Eruptions and Crustal Deformation Studies

NASA Astrophysics Data System (ADS)

Sigmundsson, F.; Hreinsdottir, S.; Hooper, A. J.; Arnadottir, T.; Pedersen, R.; Roberts, M. J.; Oskarsson, N.; Auriac, A.; Decriem, J.; Einarsson, P.; Geirsson, H.; Hensch, M.; Ofeigsson, B. G.; Sturkell, E. C.; Sveinbjornsson, H.; Feigl, K.

2010-12-01

Gradual inflation of magma chambers often precedes eruptions at highly active volcanoes. During eruptions, rapid deflation occurs as magma flows out and pressure is reduced. Less is known about the deformation style at moderately active volcanoes, such as Eyjafjallajökull, Iceland, where an explosive summit eruption of trachyandesite beginning on 14 April 2010 caused exceptional disruption to air traffic. This eruption was preceded by an effusive flank eruption of olivine basalt from 20 March - 12 April 2010. Geodetic and seismic observations revealed the growth of an intrusive complex in the roots of the volcano during three months prior to eruptions. After initial horizontal growth, modelling indicates both horizontal and sub-vertical growth in three weeks prior the first eruption. The behaviour is attributed to subsurface variations in crustal stress and strength originating from complicated volcano foundations. A low-density layer may capture magma allowing pressure to build before an intrusion can ascend towards higher levels. The intrusive complex was formed by olivine basalt as erupted on the volcano flank 20 March - 12 April; the intrusive growth halted at the onset of this eruption. Deformation associated with the eruption onset was minor as the dike had reached close to the surface in the days before. Isolated eruptive vents opening on long-dormant volcanoes may represent magma leaking upwards from extensive pre-eruptive intrusions formed at depth. A deflation source activated during the summit eruption of trachyandesite is distinct from, and adjacent to, all documented sources of inflation in the volcano roots. Olivine basalt magma which recharged the volcano appears to have triggered the summit eruption, although the exact mode of triggering is uncertain. Scenarios include stress triggering or propagation of olivine basalt into more evolved magma. The trachyandesite includes crystals that can be remnants of minor recent intrusion of olivine basalt. Alternatively, mixing of larger portion of olivine basalt with more evolved magma may have occurred. Intrusions may lead to eruptions not only when they find their way to the surface; at Eyjafjallajökull our observation show how primitive melts in an intrusive complex active since 1992 catalyzed an explosive eruption of trachyandesite. Eyjafjallajökull’s behaviour can be attributed to its off-rift setting with a relatively cold subsurface structure and limited magma at shallow depth, as may be typical for moderately active volcanoes. Clear signs of volcanic unrest signals over years to weeks may indicate reawakening of such volcanoes whereas immediate short-term precursors may be subtle and difficult to detect.

Stochastic reduced order models for inverse problems under uncertainty

PubMed Central

Warner, James E.; Aquino, Wilkins; Grigoriu, Mircea D.

2014-01-01

This work presents a novel methodology for solving inverse problems under uncertainty using stochastic reduced order models (SROMs). Given statistical information about an observed state variable in a system, unknown parameters are estimated probabilistically through the solution of a model-constrained, stochastic optimization problem. The point of departure and crux of the proposed framework is the representation of a random quantity using a SROM - a low dimensional, discrete approximation to a continuous random element that permits e cient and non-intrusive stochastic computations. Characterizing the uncertainties with SROMs transforms the stochastic optimization problem into a deterministic one. The non-intrusive nature of SROMs facilitates e cient gradient computations for random vector unknowns and relies entirely on calls to existing deterministic solvers. Furthermore, the method is naturally extended to handle multiple sources of uncertainty in cases where state variable data, system parameters, and boundary conditions are all considered random. The new and widely-applicable SROM framework is formulated for a general stochastic optimization problem in terms of an abstract objective function and constraining model. For demonstration purposes, however, we study its performance in the specific case of inverse identification of random material parameters in elastodynamics. We demonstrate the ability to efficiently recover random shear moduli given material displacement statistics as input data. We also show that the approach remains effective for the case where the loading in the problem is random as well. PMID:25558115

Subsurface event detection and classification using Wireless Signal Networks.

PubMed

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

2012-11-05

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

Subsurface Event Detection and Classification Using Wireless Signal Networks

PubMed Central

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

2012-01-01

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

Effects of sea-level rise and pumpage elimination on saltwater intrusion in the Hilton Head Island area, South Carolina, 2004-2104

USGS Publications Warehouse

Payne, Dorothy F.

2010-01-01

Saltwater intrusion of the Upper Floridan aquifer has been observed in the Hilton Head area, South Carolina since the late 1970s and currently affects freshwater supply. Rising sea level in the Hilton Head Island area may contribute to the occurrence of and affect the rate of saltwater intrusion into the Upper Floridan aquifer by increasing the hydraulic gradient and by inundating an increasing area with saltwater, which may then migrate downward into geologic units that presently contain freshwater. Rising sea level may offset any beneficial results from reductions in groundwater pumpage, and thus needs to be considered in groundwater-management decisions. A variable-density groundwater flow and transport model was modified from a previously existing model to simulate the effects of sea-level rise in the Hilton Head Island area. Specifically, the model was used to (1) simulate trends of saltwater intrusion from predevelopment to the present day (1885-2004) and evaluate the conceptual model, (2) project these trends from the present day into the future based on different potential rates of sea-level change, and (3) evaluate the relative influences of pumpage and sea-level rise on saltwater intrusion. Four scenarios were simulated for 2004-2104: (1) continuation of the estimated sea-level rise rate over the last century, (2) a doubling of the sea-level rise, (3) a cessation of sea-level rise, and (4) continuation of the rate over the last century coupled with an elimination of all pumpage. Results show that, if present-day (year 2004) pumping conditions are maintained, the extent of saltwater in the Upper Floridan aquifer will increase, whether or not sea level continues to rise. Furthermore, if all pumpage is eliminated and sea level continues to rise, the simulated saltwater extent in the Upper Floridan aquifer is reduced. These results indicate that pumpage is a strong driving force for simulated saltwater intrusion, more so than sea-level rise at current rates. However, results must be considered in light of limitations in the model, including, but not limited to uncertainty in field data, the conceptual model, the physical properties and representation of the hydrogeologic framework, and boundary and initial conditions, as well as uncertainty in future conditions, such as the rate of sea-level rise.

Percolation of isotopically heterogeneous interstitial melts in the crystal mush of the Rum layered intrusion, NW Scotland

NASA Astrophysics Data System (ADS)

O'Driscoll, B.; Hepworth, L. N.; Daly, J. S.; Gertisser, R.; Emeleus, C. H.

2017-12-01

The cumulate stratigraphy of layered intrusions offers a means of interrogating the replenishment and solidification histories of mafic magma chambers. Cumulates comprise cumulus minerals, which accumulate to form a silicate framework, and intercumulus minerals, which represent melt crystallised within the crystal mush. This fundamental textural distinction lies at the heart of cumulus theory and underpins some of the classic models of crystal-liquid differentiation that are based on layered intrusions. In order to shed further light on the importance of postcumulus processes in layered intrusions, and to demonstrate that crystal mushes may behave as open-systems during the crystallisation of cumulates, we investigated mineral-scale textural and geochemical heterogeneity in Unit 10 of the 60 Ma Rum layered intrusion. Numerous ( 1 mm thick) Cr-spinel seams occur throughout the 65 m Unit 10 peridotite stratigraphy. Unusually, intercumulus plagioclase and clinopyroxene crystals in the peridotite several centimetres above and below these seams exhibit complex optical and major element zoning. Sampling of individual intra-crystal zones in these phases was carried out using a New Wave Micromill, for analysis of their 87Sr/86Sr compositions to be measured on unspiked samples by TIMS. Both minerals reveal intra-crystalline isotopic heterogeneity. The maximum range (with 2σ uncertainties) of 87Sr/86Sr in the Unit 10 plagioclase is 0.704026±17-0.704591±8 and in clinopyroxene is 0.703533±23-0.704517±17. Within a single, oscillatory-zoned plagioclase, three discrete zones yield 87Sr/86Sr values of 0.704337±20, 0.704095±20 and 0.704052±11. A complex patchily-zoned clinopyroxene yields a 87Sr/86Sr range of 0.703533±23-0.703894±23. The new data demonstrate that multiple generations of isotopically distinct melts percolated through the Unit 10 crystal mush, suggesting solidification from cumulates that underwent repeated cycles of resorption and recrystallisation at the postcumulus stage. The cumulate products of layered intrusions may therefore form from magma addition within the crystal mush, and such a process might be especially relevant for precious metal enrichment, given the association between isotopic disequilibrium and the locations of Cr-spinel seams observed here.

Surface deformation induced by magmatic processes at Pacaya Volcano, Guatemala revealed by InSAR

NASA Astrophysics Data System (ADS)

Wnuk, K.; Wauthier, C.

2017-09-01

Pacaya Volcano, Guatemala is a continuously active, basaltic volcano with an unstable western flank. Despite continuous activity since 1961, a lack of high temporal resolution geodetic surveying has prevented detailed modeling of Pacaya's underlying magmatic plumbing system. A new, temporally dense dataset of Interferometric Synthetic Aperture Radar (InSAR) RADARSAT-2 images, spanning December 2012 to March 2014, show magmatic deformation before and during major eruptions in January and March 2014. Inversion of InSAR surface displacements using simple analytical forward models suggest that three magma bodies are responsible for the observed deformation: (1) a 4 km deep spherical reservoir located northwest of the summit, (2) a 0.4 km deep spherical source located directly west of the summit, and (3) a shallow dike below the summit. Periods of heightened volcanic activity are instigated by magma pulses at depth, resulting in rapid inflation of the edifice. We observe an intrusion cycle at Pacaya that consists of deflation of one or both magma reservoirs followed by dike intrusion. Intrusion volumes are proportional to reservoir volume loss and do not always result in an eruption. Periods of increased activity culminate with larger dike-fed eruptions. Large eruptions are followed by inter-eruptive periods marked by a decrease in crater explosions and a lack of detected deformation. Co-eruptive flank motion appears to have initiated a new stage of volcanic rifting at Pacaya defined by repeated NW-SE oriented dike intrusions. This creates a positive feedback relationship whereby magmatic forcing from eruptive dike intrusions induce flank motion.

Trust Management in Mobile Ad Hoc Networks for Bias Minimization and Application Performance Maximization

DTIC Science & Technology

2014-02-26

set of anomaly detection rules 62 I.-R. Chen et al. / Ad Hoc Networks 19 (2014) 59–74 Author’s personal copy including the interval rule (for...deficiencies in anomaly detection (e.g., imperfection of rules) by a false negative probability (PHfn) of misidentifying an unhealthy node as a...multimedia servers, Multimedia Syst. 8 (2) (2000) 83–91. [53] R. Mitchell, I.R. Chen, Adaptive intrusion detection for unmanned aircraft systems based on

Quantifying Associations between Environmental Stressors and Demographic Factors

EPA Science Inventory

Association rule mining (ARM) [1-3], also known as frequent item set mining [4] or market basket analysis [1], has been widely applied in many different areas, such as business product portfolio planning [5], intrusion detection infrastructure design [6], gene expression analysis...

Techniques for Cyber Attack Attribution

DTIC Science & Technology

2003-10-01

Asaka, Midori, Shunji Okazawa, Atsushi Taguchi, and Shigeki Goto. June 1999. “A Method of Tracing Intruders by Use of Mobile Agents”, INET’99. http...Tsuchiya, Takefumi Onabuta, Shunji Okazawa, and Shigeki Goto. November 1999. “Local Attack Detection and Intrusion Route Tracing”, IEICE Transaction on

Development and evaluation of a decision-supporting model for identifying the source location of microbial intrusions in real gravity sewer systems.

PubMed

Kim, Minyoung; Choi, Christopher Y; Gerba, Charles P

2013-09-01

Assuming a scenario of a hypothetical pathogenic outbreak, we aimed this study at developing a decision-support model for identifying the location of the pathogenic intrusion as a means of facilitating rapid detection and efficient containment. The developed model was applied to a real sewer system (the Campbell wash basin in Tucson, AZ) in order to validate its feasibility. The basin under investigation was divided into 14 sub-basins. The geometric information associated with the sewer network was digitized using GIS (Geological Information System) and imported into an urban sewer network simulation model to generate microbial breakthrough curves at the outlet. A pre-defined amount of Escherichia coli (E. coli), which is an indicator of fecal coliform bacteria, was hypothetically introduced into 56 manholes (four in each sub-basin, chosen at random), and a total of 56 breakthrough curves of E. coli were generated using the simulation model at the outlet. Transport patterns were classified depending upon the location of the injection site (manhole), various known characteristics (peak concentration and time, pipe length, travel time, etc.) extracted from each E. coli breakthrough curve and the layout of sewer network. Using this information, we back-predicted the injection location once an E. coli intrusion was detected at a monitoring site using Artificial Neural Networks (ANNs). The results showed that ANNs identified the location of the injection sites with 57% accuracy; ANNs correctly recognized eight out of fourteen expressions with relying on data from a single detection sensor. Increasing the available sensors within the basin significantly improved the accuracy of the simulation results (from 57% to 100%). Copyright © 2013 Elsevier Ltd. All rights reserved.

Hybrid methods for cybersecurity analysis :

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Warren Leon,; Dunlavy, Daniel M.

2014-01-01

Early 2010 saw a signi cant change in adversarial techniques aimed at network intrusion: a shift from malware delivered via email attachments toward the use of hidden, embedded hyperlinks to initiate sequences of downloads and interactions with web sites and network servers containing malicious software. Enterprise security groups were well poised and experienced in defending the former attacks, but the new types of attacks were larger in number, more challenging to detect, dynamic in nature, and required the development of new technologies and analytic capabilities. The Hybrid LDRD project was aimed at delivering new capabilities in large-scale data modeling andmore » analysis to enterprise security operators and analysts and understanding the challenges of detection and prevention of emerging cybersecurity threats. Leveraging previous LDRD research e orts and capabilities in large-scale relational data analysis, large-scale discrete data analysis and visualization, and streaming data analysis, new modeling and analysis capabilities were quickly brought to bear on the problems in email phishing and spear phishing attacks in the Sandia enterprise security operational groups at the onset of the Hybrid project. As part of this project, a software development and deployment framework was created within the security analyst work ow tool sets to facilitate the delivery and testing of new capabilities as they became available, and machine learning algorithms were developed to address the challenge of dynamic threats. Furthermore, researchers from the Hybrid project were embedded in the security analyst groups for almost a full year, engaged in daily operational activities and routines, creating an atmosphere of trust and collaboration between the researchers and security personnel. The Hybrid project has altered the way that research ideas can be incorporated into the production environments of Sandias enterprise security groups, reducing time to deployment from months and years to hours and days for the application of new modeling and analysis capabilities to emerging threats. The development and deployment framework has been generalized into the Hybrid Framework and incor- porated into several LDRD, WFO, and DOE/CSL projects and proposals. And most importantly, the Hybrid project has provided Sandia security analysts with new, scalable, extensible analytic capabilities that have resulted in alerts not detectable using their previous work ow tool sets.« less

Seismogenic structures activated during the pre-eruptive and intrusive swarms of Piton de la Fournaise volcano (La Réunion island) between 2008 and 2011

NASA Astrophysics Data System (ADS)

Battaglia, J.; Brenguier, F.

2011-12-01

Piton de la Fournaise is a frequently active basaltic volcano with more than 30 fissure eruptions since 1998. These eruptions are always preceded by pre-eruptive swarms of volcano-tectonic earthquakes which accompany dike propagation. Occasionally, intrusion swarms occur without leading to any eruption. From October 2008 to May 2011, as part of the research project Undervolc, a temporary network of 15 broadband stations has been installed on the volcano to complement the local monitoring network. We examined in detail the 6 intrusive and 5 pre-eruptive swarms which occurred during the temporary experiment. All the crises lasted for a few hours and only included shallow events clustered below the summit craters, around and above sea level, showing no signs of deeper magma transfers. These characteristics are common to most swarms observed at Piton de la Fournaise arising questions about the origin of the seismicity which seems to be poorly linked with dike propagation. With the aim to identify the main seismogenic structures active during the swarms, we applied precise earthquake detection and classification techniques based on waveform cross-correlation. For each swarm, the onsets of all transients, including small amplitude ones, have been precisely detected at a single station by scanning the continuous data with reference waveforms. The classification of the detected transients indicates the presence of several families of similar earthquakes. The two main families (F01 and F02) include several hundred events. They are systematically activated at the beginning of each pre-eruptive swarm but are inactive during the intrusive ones. They group more than 50 percent of the detected events for the corresponding crises. The other clusters are mostly associated with single swarms. To determine the spatial characteristics of the structures corresponding to the main families, we applied precise relocation techniques. Based on the one-station classification, the events have first been picked at all available stations by cross-correlating waveforms with those of master events whose arrival times have been manually determined. All events have been located using a 3D velocity model to determine accurate hypocentral azimuths and take-off angles. Precise relative locations have been computed for each multiplet using cross-correlation delays calculated for all available stations between all pairs of events. The results indicate the presence at sea level of a major structure grouping families F01 and F02 and describing an East-West elongated pattern with sub-vertical extension. Small scale earthquake migrations, mostly horizontal, occur during the pre-eruptive swarms along that structure. The smaller multiplets define vertically elongated patterns extending around and above the main F01-F02 multiplet. Our results show that different processes are involved in pre-eruptive and intrusive crises and that a structure located around 2.5 km below the summit controls the occurrence of recent eruptions of Piton de la Fournaise volcano.

A circumpolar monitoring framework for polar bears

USGS Publications Warehouse

Vongraven, Dag; Aars, Jon; Amstrup, Steven C.; Atkinson, Stephen N.; Belikov, Stanislav; Born, Erik W.; DeBruyn, T.D.; Derocher, Andrew E.; Durner, George M.; Gill, Michael J.; Lunn, Nicholas J.; Obbard, Martyn E.; Omelak, Jack; Ovsyanikov, Nikita; Peacock, Elizabeth; Richardson, E.E.; Sahanatien, Vicki; Stirling, Ian; Wiig, Øystein

2012-01-01

Polar bears (Ursus maritimus) occupy remote regions that are characterized by harsh weather and limited access. Polar bear populations can only persist where temporal and spatial availability of sea ice provides adequate access to their marine mammal prey. Observed declines in sea ice availability will continue as long as greenhouse gas concentrations rise. At the same time, human intrusion and pollution levels in the Arctic are expected to increase. A circumpolar understanding of the cumulative impacts of current and future stressors is lacking, long-term trends are known from only a few subpopulations, and there is no globally coordinated effort to monitor effects of stressors. Here, we describe a framework for an integrated circumpolar monitoring plan to detect ongoing patterns, predict future trends, and identify the most vulnerable polar bear subpopulations. We recommend strategies for monitoring subpopulation abundance and trends, reproduction, survival, ecosystem change, human-caused mortality, human–bear conflict, prey availability, health, stature, distribution, behavioral change, and the effects that monitoring itself may have on polar bears. We assign monitoring intensity for each subpopulation through adaptive assessment of the quality of existing baseline data and research accessibility. A global perspective is achieved by recommending high intensity monitoring for at least one subpopulation in each of four major polar bear ecoregions. Collection of data on harvest, where it occurs, and remote sensing of habitat, should occur with the same intensity for all subpopulations. We outline how local traditional knowledge may most effectively be combined with the best scientific methods to provide comparable and complementary lines of evidence. We also outline how previously collected intensive monitoring data may be sub-sampled to guide future sampling frequencies and develop indirect estimates or indices of subpopulation status. Adoption of this framework will inform management and policy responses to changing worldwide polar bear status and trends.

A hybrid protection approaches for denial of service (DoS) attacks in wireless sensor networks

NASA Astrophysics Data System (ADS)

Gunasekaran, Mahalakshmi; Periakaruppan, Subathra

2017-06-01

Wireless sensor network (WSN) contains the distributed autonomous devices with the sensing capability of physical and environmental conditions. During the clustering operation, the consumption of more energy causes the draining in battery power that leads to minimum network lifetime. Hence, the WSN devices are initially operated on low-power sleep mode to maximise the lifetime. But, the attacks arrival cause the disruption in low-power operating called denial of service (DoS) attacks. The conventional intrusion detection (ID) approaches such as rule-based and anomaly-based methods effectively detect the DoS attacks. But, the energy consumption and false detection rate are more. The absence of attack information and broadcast of its impact to the other cluster head (CH) leads to easy DoS attacks arrival. This article combines the isolation and routing tables to detect the attack in the specific cluster and broadcasts the information to other CH. The intercommunication between the CHs prevents the DoS attacks effectively. In addition, the swarm-based defence approach is proposed to migrate the fault channel to normal operating channel through frequency hop approaches. The comparative analysis between the proposed table-based intrusion detection systems (IDSs) and swarm-based defence approaches with the traditional IDS regarding the parameters of transmission overhead/efficiency, energy consumption, and false positive/negative rates proves the capability of DoS prediction/prevention in WSN.

Practical results from a mathematical analysis of guard patrols

DOE Office of Scientific and Technical Information (OSTI.GOV)

Indusi, Joseph P.

1978-12-01

Using guard patrols as a primary detection mechanism is not generally viewed as a highly efficient detection method when compared to electronic means. Many factors such as visibility, alertness, and the space-time coincidence of guard and adversary presence all have an effect on the probability of detection. Mathematical analysis of the guard patrol detection problem is related to that of classical search theory originally developed for naval search operations. The results of this analysis tend to support the current practice of using guard forces to assess and respond to previously detected intrusions and not as the primary detection mechanism. 6more » refs.« less

A hierarchical detection method in external communication for self-driving vehicles based on TDMA

PubMed Central

Al-ani, Muzhir Shaban; McDonald-Maier, Klaus

2018-01-01

Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms. PMID:29315302

Acoustic measurements of soil-pipeflow and internal erosion

USDA-ARS?s Scientific Manuscript database

Internal erosion of soil pipes can lead to embankment failures, landslides, and gully erosion. Therefore, non-intrusive methods are needed to detect and monitor soil pipeflow and the resulting internal erosion. This paper presents a laboratory study using both active and passive acoustic techniques ...

Acoustic measurements of soil pipeflow and internal erosion

USDA-ARS?s Scientific Manuscript database

Internal erosion of soil pipes can lead to embankment failures, landslides, and gully erosion therefore non-intrusive methods are needed to detect and monitor soil pipeflow and the resulting internal erosion. This paper presents a laboratory study using both active and passive acoustic techniques to...

Molecular oxygen detection using frequency modulation diode laser spectroscopy

NASA Technical Reports Server (NTRS)

Wang, Liang-Guo; Sachse, Glen

1990-01-01

A high-sensitivity spectroscopic measurement of O2 using two-tone frequency modulation spectroscopy with a GaAlAs diode laser is presented. An oxygen sensor based on this technique would be non-intrusive, compact and possess high sensitivity and fast time response.

Numerical Analysis for Relevant Features in Intrusion Detection (NARFid)

DTIC Science & Technology

2009-03-01

Rosenblatt, Frank. Principles of Neurodynamics : Perceptrons and the Theory of Brain Mechanisms. Spartan Books, Washington DC, 1961. 74. Rossey, Lee M., Robert...editors), Parallel distributed process- ing: Explorations in the microstructure of cognition , Volume 1: Foundations. MIT Press, 1986. 76. Russel, Stuart and

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, J.; Modlin, C.W.; Frerking, C.J.

HIPROTECT (pronounced High-protect) is a system designed to protect national archaeological and natural treasures from destruction by vandals or looters. The system is being developed jointly by the Lawrence Livermore National Laboratory and the University of California at Riverside under the DOD Legacy Resource Management Program. Thousands of archaeological sites are located on military bases and national park lands. Treasure hunters or vandals are pillaging and destroying these sites at will, since the sites are generally located in remote areas, unattended and unprotected. The HIPROTECT system is designed to detect trespassers at the protected sites and to alert park officialsmore » or military officials of intrusions. An array of sensors is used to detect trespassers. The sensors are triggered when a person or vehicle approaches the site. Alarm messages are transmitted to alert park officials or law enforcement officials by way of a cellular telephone link. A video and audio system is included to assist the officials in verifying that an intrusion has occurred and to allow two-way communication with the intruders.« less

Network traffic intelligence using a low interaction honeypot

NASA Astrophysics Data System (ADS)

Nyamugudza, Tendai; Rajasekar, Venkatesh; Sen, Prasad; Nirmala, M.; Madhu Viswanatham, V.

2017-11-01

Advancements in networking technology have seen more and more devices becoming connected day by day. This has given organizations capacity to extend their networks beyond their boundaries to remote offices and remote employees. However as the network grows security becomes a major challenge since the attack surface also increases. There is need to guard the network against different types of attacks like intrusion and malware through using different tools at different networking levels. This paper describes how network intelligence can be acquired through implementing a low-interaction honeypot which detects and track network intrusion. Honeypot allows an organization to interact and gather information about an attack earlier before it compromises the network. This process is important because it allows the organization to learn about future attacks of the same nature and allows them to develop counter measures. The paper further shows how honeypot-honey net based model for interruption detection system (IDS) can be used to get the best valuable information about the attacker and prevent unexpected harm to the network.

Pyroelectric IR sensor arrays for fall detection in the older population

NASA Astrophysics Data System (ADS)

Sixsmith, A.; Johnson, N.; Whatmore, R.

2005-09-01

Uncooled pyroelectric sensor arrays have been studied over many years for their uses in thermal imaging applications. These arrays will only detect changes in IR flux and so systems based upon them are very good at detecting movements of people in the scene without sensing the background, if they are used in staring mode. Relatively-low element count arrays (16 x 16) can be used for a variety of people sensing applications, including people counting (for safety applications), queue monitoring etc. With appropriate signal processing such systems can be also be used for the detection of particular events such as a person falling over. There is a considerable need for automatic fall detection amongst older people, but there are important limitations to some of the current and emerging technologies available for this. Simple sensors, such as 1 or 2 element pyroelectric infra-red sensors provide crude data that is difficult to interpret; the use of devices worn on the person, such as wrist communicator and motion detectors have potential, but are reliant on the person being able and willing to wear the device; video cameras may be seen as intrusive and require considerable human resources to monitor activity while machine-interpretation of camera images is complex and may be difficult in this application area. The use of a pyroelectric thermal array sensor was seen to have a number of potential benefits. The sensor is wall-mounted and does not require the user to wear a device. It enables detailed analysis of a subject's motion to be achieved locally, within the detector, using only a modest processor. This is possible due to the relative ease with which data from the sensor can be interpreted relative to the data generated by alternative sensors such as video devices. In addition to the cost-effectiveness of this solution, it was felt that the lack of detail in the low-level data, together with the elimination of the need to transmit data outside the detector, would help to avert feelings intrusiveness on the part of the end-user.The main benefits of this type of technology would be for older people who spend time alone in unsupervised environments. This would include people living alone in ordinary housing or in sheltered accommodation (apartment complexes for older people with local warden) and non-communal areas in residential/nursing home environments (e.g. bedrooms and ensuite bathrooms and toilets). This paper will review the development of the array, the pyroelectric ceramic material upon which it is based and the system capabilities. It will present results from the Framework 5 SIMBAD project, which used the system to monitor the movements of elderly people over a considerable period of time.

An Efficient Method for Detecting Misbehaving Zone Manager in MANET

NASA Astrophysics Data System (ADS)

Rafsanjani, Marjan Kuchaki; Pakzad, Farzaneh; Asadinia, Sanaz

In recent years, one of the wireless technologies increased tremendously is mobile ad hoc networks (MANETs) in which mobile nodes organize themselves without the help of any predefined infrastructure. MANETs are highly vulnerable to attack due to the open medium, dynamically changing network topology, cooperative algorithms, lack of centralized monitoring, management point and lack of a clear defense line. In this paper, we report our progress in developing intrusion detection (ID) capabilities for MANET. In our proposed scheme, the network with distributed hierarchical architecture is partitioned into zones, so that in each of them there is one zone manager. The zone manager is responsible for monitoring the cluster heads in its zone and cluster heads are in charge of monitoring their members. However, the most important problem is how the trustworthiness of the zone manager can be recognized. So, we propose a scheme in which "honest neighbors" of zone manager specify the validation of their zone manager. These honest neighbors prevent false accusations and also allow manager if it is wrongly misbehaving. However, if the manger repeats its misbehavior, then it will lose its management degree. Therefore, our scheme will be improved intrusion detection and also provide a more reliable network.

Case-Based Multi-Sensor Intrusion Detection

NASA Astrophysics Data System (ADS)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

Temporal, geomagnetic and related attributes of kimberlite magmatism at Ekati, Northwest Territories, Canada

NASA Astrophysics Data System (ADS)

Lockhart, Grant; Grütter, Herman; Carlson, Jon

2004-09-01

This paper outlines the development of a multi-disciplinary strategy to focus exploration for economic kimberlites on the Ekati property. High-resolution aeromagnetic data provide an over-arching spatial and magnetostratigraphic framework for exploration and kimberlite discovery at Ekati, and hence also for this investigation. The temporal, geomagnetic, spatial and related attributes of kimberlites with variable diamond content have been constrained by judiciously augmenting the information gathered during routine exploration with detailed, laboratory-based or field-based investigations. The natural remanent magnetisation of 36 Ekati kimberlites has been correlated with their age as determined by isotopic dating techniques, and placed in the context of a well-constrained geomagnetic polarity timescale. Kimberlite magmatism occurred over the period 75 to 45 Ma, in at least five temporally discrete intrusive episodes. Based on current evidence, the older kimberlites (75 to 59 Ma) have low diamond contents and are distributed throughout the property. Younger kimberlites (56 to 45 Ma) have moderate to high diamond contents and occur in three distinct intrusive corridors with NNE to NE orientations. Economic kimberlite pipes erupted at 55.4±0.4 Ma along the A154-Lynx intrusive corridor, which is 7 km wide and oriented at 015°, and at 53.2±0.3 Ma along the Panda intrusive corridor, which is 1 km wide and oriented at 038°. The intrusion ages straddle a paleopole reversal at Chron C24n, consistent with the observation that the older economic kimberlites present as aeromagnetic "low" anomalies while the younger economic pipes are characterised as aeromagnetic "highs". The aeromagnetic responses for these kimberlites are generally muted because they contain volcaniclastic rock types with low magnetic susceptibility. Kimberlites throughout the Ekati property carry a primary natural magnetic remanence (NRM) vector in Ti-bearing groundmass magnetite, and it dominates over vectors related to induced magnetisation. Magnetostratigraphic correlation of Ekati kimberlites may therefore present a powerful adjunct to existing exploration techniques, mainly because the diamond content of Ekati kimberlites apparently is related more to the age of eruption than to any other parameter investigated in this work.

Assessing the severity of sleep apnea syndrome based on ballistocardiogram

PubMed Central

Zhou, Xingshe; Zhao, Weichao; Liu, Fan; Ni, Hongbo; Yu, Zhiwen

2017-01-01

Background Sleep Apnea Syndrome (SAS) is a common sleep-related breathing disorder, which affects about 4-7% males and 2-4% females all around the world. Different approaches have been adopted to diagnose SAS and measure its severity, including the gold standard Polysomnography (PSG) in sleep study field as well as several alternative techniques such as single-channel ECG, pulse oximeter and so on. However, many shortcomings still limit their generalization in home environment. In this study, we aim to propose an efficient approach to automatically assess the severity of sleep apnea syndrome based on the ballistocardiogram (BCG) signal, which is non-intrusive and suitable for in home environment. Methods We develop an unobtrusive sleep monitoring system to capture the BCG signals, based on which we put forward a three-stage sleep apnea syndrome severity assessment framework, i.e., data preprocessing, sleep-related breathing events (SBEs) detection, and sleep apnea syndrome severity evaluation. First, in the data preprocessing stage, to overcome the limits of BCG signals (e.g., low precision and reliability), we utilize wavelet decomposition to obtain the outline information of heartbeats, and apply a RR correction algorithm to handle missing or spurious RR intervals. Afterwards, in the event detection stage, we propose an automatic sleep-related breathing event detection algorithm named Physio_ICSS based on the iterative cumulative sums of squares (i.e., the ICSS algorithm), which is originally used to detect structural breakpoints in a time series. In particular, to efficiently detect sleep-related breathing events in the obtained time series of RR intervals, the proposed algorithm not only explores the practical factors of sleep-related breathing events (e.g., the limit of lasting duration and possible occurrence sleep stages) but also overcomes the event segmentation issue (e.g., equal-length segmentation method might divide one sleep-related breathing event into different fragments and lead to incorrect results) of existing approaches. Finally, by fusing features extracted from multiple domains, we can identify sleep-related breathing events and assess the severity level of sleep apnea syndrome effectively. Conclusions Experimental results on 136 individuals of different sleep apnea syndrome severities validate the effectiveness of the proposed framework, with the accuracy of 94.12% (128/136). PMID:28445548

75 FR 69644 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-15

..., organization, phone, fax, mobile, pager, Defense Switched Network (DSN) phone, other fax, other mobile, other.../Transport Layer Security (SSL/ TLS) connections, access control lists, file system permissions, intrusion detection and prevention systems and log monitoring. Complete access to all records is restricted to and...

Composition and source of salinity of ore-bearing fluids in Cu-Au systems of the Carajás Mineral Province, Brazil

USGS Publications Warehouse

Xavier, Roberto; Rusk, Brian; Emsbo, Poul; Monteiro, Lena

2009-01-01

The composition and Cl/Br – NaCl ratios of highly saline aqueous inclusions from large tonnage (> 100 t) IOCG deposits (Sossego, Alvo 118, and Igarapé Bahia) and a Paleoproterozoic intrusion-related Cu-Au-(Mo-W-Bi-Sn) deposit (Breves; < 50 Mt)) in the Carajás Mineral Province have been analysed by LA-ICP-MS and ion chromatography. In both Cu-Au systems, brine inclusions are Ca-dominated (5 to 10 times more than in porphyry Cu-Au fluids), and contain percent level concentrations of Na and K. IOCG inclusion fluids, however, contain higher Sr, Ba, Pb, and Zn concentrations, but significantly less Bi, than the intrusion-related Breves inclusion fluids. Cu is consistently below detection limits in brine inclusions from the IOCG and intrusion-related systems and Fe was not detected in the latter. Cl/Br and Na/Cl ratios of the IOCG inclusion fluids range from entirely evaporative brines (bittern fluids; e.g. Igarapé Bahia and Alvo 118) to values that indicate mixing with magma-derived brines. Cl/Br and Na/Cl ratios of the Breves inclusion fluids strongly suggest the involvement of magmatic brines, but that possibly also incorporated bittern fluids. Collectively, these data demonstrate that residual evaporative and magmatic brines were important components of the fluid regime involved in the formation of Cu-Au systems in the Carajás Mineral Province.

Verifying the secure setup of UNIX client/servers and detection of network intrusion

NASA Astrophysics Data System (ADS)

Feingold, Richard; Bruestle, Harry R.; Bartoletti, Tony; Saroyan, R. A.; Fisher, John M.

1996-03-01

This paper describes our technical approach to developing and delivering Unix host- and network-based security products to meet the increasing challenges in information security. Today's global `Infosphere' presents us with a networked environment that knows no geographical, national, or temporal boundaries, and no ownership, laws, or identity cards. This seamless aggregation of computers, networks, databases, applications, and the like store, transmit, and process information. This information is now recognized as an asset to governments, corporations, and individuals alike. This information must be protected from misuse. The Security Profile Inspector (SPI) performs static analyses of Unix-based clients and servers to check on their security configuration. SPI's broad range of security tests and flexible usage options support the needs of novice and expert system administrators alike. SPI's use within the Department of Energy and Department of Defense has resulted in more secure systems, less vulnerable to hostile intentions. Host-based information protection techniques and tools must also be supported by network-based capabilities. Our experience shows that a weak link in a network of clients and servers presents itself sooner or later, and can be more readily identified by dynamic intrusion detection techniques and tools. The Network Intrusion Detector (NID) is one such tool. NID is designed to monitor and analyze activity on the Ethernet broadcast Local Area Network segment and product transcripts of suspicious user connections. NID's retrospective and real-time modes have proven invaluable to security officers faced with ongoing attacks to their systems and networks.

Modeling And Detecting Anomalies In Scada Systems

NASA Astrophysics Data System (ADS)

Svendsen, Nils; Wolthusen, Stephen

The detection of attacks and intrusions based on anomalies is hampered by the limits of specificity underlying the detection techniques. However, in the case of many critical infrastructure systems, domain-specific knowledge and models can impose constraints that potentially reduce error rates. At the same time, attackers can use their knowledge of system behavior to mask their manipulations, causing adverse effects to observed only after a significant period of time. This paper describes elementary statistical techniques that can be applied to detect anomalies in critical infrastructure networks. A SCADA system employed in liquefied natural gas (LNG) production is used as a case study.

The Later Paleozoic granites of the Greater Caucasus Fore Range zone: geochemistry, magnetic properties and the structural and metamorphic evolution.

NASA Astrophysics Data System (ADS)

Kamzolkin, Vladimir; Latyshev, Anton; Ivanov, Stanislav; Vidjapin, Jury

2017-04-01

Clarification of the position of the granitic intrusions associated with the Blyb Metamorphic Complex is the important problem of the reconstruction of the structural evolution of the Greater Caucasus Fore Range zone. Based of the rock geochemistry we found out that the quartz diorites, granodiorites and syeno-granites of the BMC formed in suprasubduction conditions and refer to I-type granites. However, their emplacement was multistage coinciding with the various stages of the BMC evolution. We detected the mineral associations typical for the epidote-amphibolite facies in the Balkan massif, but these metamorphic features are absent in the granodiorite intrusions in the southern part of the Fore Range zone. Thus, quartz diorites of the Balkan intrusion intruded after the high-pressure metamorphism of the host rocks, but before the epidote-amphibolite stage, and the Southern granodiorite intrusions are younger. The measurements of the anisotropy of the magnetic susceptibility (AMS) in the Balkan intrusion indicated the shallow orientation of the minimal (north-eastern strike) and maximal (north-western strike) axes of the AMS ellipsoid. This result is compatible with the idea of the north-east compression fixed in the fold deformation structures of the BMC host rocks (Vidyapin, Kamzolkin, 2015). However, the macroscopic foliation in the granites dips to the east steeply. The discrepancy of the texture orientation of the granites, the host rock structure and the magnetic fabric can be explained as a result of the repeated changes of the stress field during the evolution of the Fore Range nappe structures. The reported study was partially supported by RFBR, research projects No. 16-35-00571mol_a; 16-05-01012a.

Dykes and structures of the NE rift of Tenerife, Canary Islands: a record of stabilisation and destabilisation of ocean island rift zones

NASA Astrophysics Data System (ADS)

Delcamp, A.; Troll, V. R.; van Wyk de Vries, B.; Carracedo, J. C.; Petronis, M. S.; Pérez-Torrado, F. J.; Deegan, F. M.

2012-07-01

Many oceanic island rift zones are associated with lateral sector collapses, and several models have been proposed to explain this link. The North-East Rift Zone (NERZ) of Tenerife Island, Spain offers an opportunity to explore this relationship, as three successive collapses are located on both sides of the rift. We have carried out a systematic and detailed mapping campaign on the rift zone, including analysis of about 400 dykes. We recorded dyke morphology, thickness, composition, internal textural features and orientation to provide a catalogue of the characteristics of rift zone dykes. Dykes were intruded along the rift, but also radiate from several nodes along the rift and form en échelon sets along the walls of collapse scars. A striking characteristic of the dykes along the collapse scars is that they dip away from rift or embayment axes and are oblique to the collapse walls. This dyke pattern is consistent with the lateral spreading of the sectors long before the collapse events. The slump sides would create the necessary strike-slip movement to promote en échelon dyke patterns. The spreading flank would probably involve a basal decollement. Lateral flank spreading could have been generated by the intense intrusive activity along the rift but sectorial spreading in turn focused intrusive activity and allowed the development of deep intra-volcanic intrusive complexes. With continued magma supply, spreading caused temporary stabilisation of the rift by reducing slopes and relaxing stress. However, as magmatic intrusion persisted, a critical point was reached, beyond which further intrusion led to large-scale flank failure and sector collapse. During the early stages of growth, the rift could have been influenced by regional stress/strain fields and by pre-existing oceanic structures, but its later and mature development probably depended largely on the local volcanic and magmatic stress/strain fields that are effectively controlled by the rift zone growth, the intrusive complex development, the flank creep, the speed of flank deformation and the associated changes in topography. Using different approaches, a similar rift evolution has been proposed in volcanic oceanic islands elsewhere, showing that this model likely reflects a general and widespread process. This study, however, shows that the idea that dykes orient simply parallel to the rift or to the collapse scar walls is too simple; instead, a dynamic interplay between external factors (e.g. collapse, erosion) and internal forces (e.g. intrusions) is envisaged. This model thus provides a geological framework to understand the evolution of the NERZ and may help to predict developments in similar oceanic volcanoes elsewhere.

Profiler-2000: Attacking the Insider Threat

DTIC Science & Technology

2005-09-01

detection approach and its incorporation into a number of current automated intrusion-detection strategies (e.g., AT&T’s Com- puterWatch, SRI’s Emerald ...administrative privileges, to be activated upon his or her next login . The system calls required to implement this method are chmod and exit. These two calls...kinds of information that can be derived from these (and other) logs are: time of login , physical location of login , duration of user session

Investigation of a Neural Network Implementation of a TCP Packet Anomaly Detection System

DTIC Science & Technology

2004-05-01

reconnatre les nouvelles variantes d’attaque. Les réseaux de neurones artificiels (ANN) ont les capacités d’apprendre à partir de schémas et de...Computational Intelligence Techniques in Intrusion Detection Systems. In IASTED International Conference on Neural Networks and Computational Intelligence , pp...Neural Network Training: Overfitting May be Harder than Expected. In Proceedings of the Fourteenth National Conference on Artificial Intelligence , AAAI-97

Perceptual processing advantages for trauma-related visual cues in post-traumatic stress disorder

PubMed Central

Kleim, B.; Ehring, T.; Ehlers, A.

2012-01-01

Background Intrusive re-experiencing in post-traumatic stress disorder (PTSD) comprises distressing sensory impressions from the trauma that seem to occur ‘out of the blue’. A key question is how intrusions are triggered. One possibility is that PTSD is characterized by a processing advantage for stimuli that resemble those that accompanied the trauma, which would lead to increased detection of such cues in the environment. Method We used a blurred picture identification task in a cross-sectional (n=99) and a prospective study (n=221) of trauma survivors. Results Participants with acute stress disorder (ASD) or PTSD, but not trauma survivors without these disorders, identified trauma-related pictures, but not general threat pictures, better than neutral pictures. There were no group differences in the rate of trauma-related answers to other picture categories. The relative processing advantage for trauma-related pictures correlated with re-experiencing and dissociation, and predicted PTSD at follow-up. Conclusions A perceptual processing bias for trauma-related stimuli may contribute to the involuntary triggering of intrusive trauma memories in PTSD. PMID:21733208

Designing and Implementing a Family of Intrusion Detection Systems

DTIC Science & Technology

2004-11-01

configure (train), generates many false alarms – Misuse detection (signature analysis) (NFR, Emerald , Snort, STAT) • Generates few false alarms • Detects...to create .rhosts file in world-writable ftp home directory – rlogin using bogus .rhosts file S0 create_file read_rhosts S3S2 login S1 STAT KN-14...world-writable ftp home directory – rlogin using bogus .rhosts file S0 create_file read_rhosts S3S2 login S1 STAT KN-17 ftp-write in STATL use ustat

Initial assessment of the ground-water resources in the Monterey Bay region, California

USGS Publications Warehouse

Muir, K.S.

1977-01-01

Because urban growth has placed an increasing demand on the ground-water resources of the Monterey Bay region, Calif., an assessment of the ground-water conditions was made to aid the development of local and regional plans. Ground water provides 80 percent of the water used in the region, which includes six ground-water subbasins. In several of the subbasins, pumpage exceeds safe yield. Existing water-quality degradation results from seawater intrusion, septic-tank effluent, and irrigation-return water. Potential sources of degradation include municipal sewage disposal, leachates from solid-waste disposal sites, and poor-quality connate water. High-priority items for future study include location of recharge areas, detection of seawater intrusion, and well-monitoring of landfill sites. (Woodard-USGS)

Project WP#422: Consolidated Research Program, Right of Way Automated Monitoring Threat Prevention (Topic Area #1); Leak Detection (Topic Area #2)

DOT National Transportation Integrated Search

2012-08-30

Preventing unauthorized intrusions on pipeline Right of Ways (ROWs) and mechanical damage due to third party strikes by machinery is a constant challenge for the pipeline industry. Equally important for safety and environmental protection is the dete...

Evaluation of intrusion detection technologies for high speed rail grade crossings : final report.

DOT National Transportation Integrated Search

2003-12-01

The rail industry is in the process of developing a prototype system for high speed rail. One of the concerns when using high speed rail is the danger of obstructions on the track. This level of danger is much higher than with traditional railway veh...

Security of Data, Stored in Information Systems of Bulgarian Municipal Administrations

NASA Astrophysics Data System (ADS)

Kapralyakov, Petko

2011-12-01

Massive influx of information technology in municipal administrations increases their efficiency in delivering public services but increased the risk of theft of confidential information electronically. The report proposed an approach for improving information security for small municipal governments in Bulgaria through enhanced intrusion detection and prevention system.

10 CFR 73.23 - Protection of Safeguards Information-Modified Handling: Specific requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... Information not classified as Restricted Data or National Security Information related to physical protection... stored in a locked file drawer or cabinet. (3) A mobile device (such as a laptop computer) may also be... of intrusion detection devices, alarm assessment equipment, alarm system wiring, emergency power...

10 CFR 73.23 - Protection of Safeguards Information-Modified Handling: Specific requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

.... Information not classified as Restricted Data or National Security Information related to physical protection... stored in a locked file drawer or cabinet. (3) A mobile device (such as a laptop computer) may also be... of intrusion detection devices, alarm assessment equipment, alarm system wiring, emergency power...

10 CFR 73.23 - Protection of Safeguards Information-Modified Handling: Specific requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

.... Information not classified as Restricted Data or National Security Information related to physical protection... stored in a locked file drawer or cabinet. (3) A mobile device (such as a laptop computer) may also be... of intrusion detection devices, alarm assessment equipment, alarm system wiring, emergency power...

10 CFR 73.23 - Protection of Safeguards Information-Modified Handling: Specific requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

.... Information not classified as Restricted Data or National Security Information related to physical protection... stored in a locked file drawer or cabinet. (3) A mobile device (such as a laptop computer) may also be... of intrusion detection devices, alarm assessment equipment, alarm system wiring, emergency power...

10 CFR 73.23 - Protection of Safeguards Information-Modified Handling: Specific requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

.... Information not classified as Restricted Data or National Security Information related to physical protection... stored in a locked file drawer or cabinet. (3) A mobile device (such as a laptop computer) may also be... of intrusion detection devices, alarm assessment equipment, alarm system wiring, emergency power...

An Intelligent Tutor for Intrusion Detection on Computer Systems.

ERIC Educational Resources Information Center

Rowe, Neil C.; Schiavo, Sandra

1998-01-01

Describes an intelligent tutor incorporating a program using artificial-intelligence planning methods to generate realistic audit files reporting actions of simulated users and intruders of a UNIX system, and a program simulating the system afterwards that asks students to inspect the audit and fix problems. Experiments show that students using…

Information Communications Technology Support to Reconstruction and Development: Some Observations from Afghanistan

DTIC Science & Technology

2007-06-01

banditry. Afghan women are still among the worst off in the world: most are illite many have no access to healthcare, and child and forced marriages...Cyber security » Virus and spyware protection, intrusion detection-protection, firewalls » Control use of pirated software and porn surfing by

Getting Employees Involved in Information Security: The Case of Strong Passwords

ERIC Educational Resources Information Center

Taylor, Richard G.

2009-01-01

With the increasing amount and severity of information security incidents, organizations are constantly looking for better ways to protect their information. The implementation of physical safeguards such as firewalls and intrusion detection systems is an integral part on an organization's overall information security; however these safeguards…

Impact of CO2 Intrusion into USDWs, the Vadose Zone, and Indoor Air

EPA Science Inventory

The U.S. Environmental Protection Agency’s (EPA) Water Research Program in the Office of Research and Development is conducting research to better detect and quantify leakage into USDWs, the vadose zone, the atmosphere, and buildings. Research in this initiative is focused in thr...

A framework for periodic outlier pattern detection in time-series sequences.

PubMed

Rasheed, Faraz; Alhajj, Reda

2014-05-01

Periodic pattern detection in time-ordered sequences is an important data mining task, which discovers in the time series all patterns that exhibit temporal regularities. Periodic pattern mining has a large number of applications in real life; it helps understanding the regular trend of the data along time, and enables the forecast and prediction of future events. An interesting related and vital problem that has not received enough attention is to discover outlier periodic patterns in a time series. Outlier patterns are defined as those which are different from the rest of the patterns; outliers are not noise. While noise does not belong to the data and it is mostly eliminated by preprocessing, outliers are actual instances in the data but have exceptional characteristics compared with the majority of the other instances. Outliers are unusual patterns that rarely occur, and, thus, have lesser support (frequency of appearance) in the data. Outlier patterns may hint toward discrepancy in the data such as fraudulent transactions, network intrusion, change in customer behavior, recession in the economy, epidemic and disease biomarkers, severe weather conditions like tornados, etc. We argue that detecting the periodicity of outlier patterns might be more important in many sequences than the periodicity of regular, more frequent patterns. In this paper, we present a robust and time efficient suffix tree-based algorithm capable of detecting the periodicity of outlier patterns in a time series by giving more significance to less frequent yet periodic patterns. Several experiments have been conducted using both real and synthetic data; all aspects of the proposed approach are compared with the existing algorithm InfoMiner; the reported results demonstrate the effectiveness and applicability of the proposed approach.

Intrusive images and intrusive thoughts as different phenomena: two experimental studies.

PubMed

Hagenaars, Muriel A; Brewin, Chris R; van Minnen, Agnes; Holmes, Emily A; Hoogduin, Kees A L

2010-01-01

According to the dual representation theory of PTSD, intrusive trauma images and intrusive verbal thoughts are produced by separate memory systems. In a previous article it was shown that after watching an aversive film, participants in non-movement conditions reported more intrusive images than participants in a free-to-move control condition (Hagenaars, Van Minnen, Holmes, Brewin, & Hoogduin, 2008). The present study investigates whether the experimental conditions of the Hagenaars et al. study had a different effect on intrusive thoughts than on intrusive images. Experiment 2 further investigated the image-thoughts distinction by manipulating stimulus valence (trauma film versus neutral film) and assessing the subsequent development of intrusive images and thoughts. In addition, both experiments studied the impact of peri-traumatic emotions on subsequent intrusive images and thoughts frequency across conditions. Results showed that experimental manipulations (non-movement and trauma film) caused higher levels of intrusive images relative to control conditions (free movement and neutral film) but they did not affect intrusive thoughts. Peri-traumatic anxiety and horror were associated with subsequent higher levels of intrusive images, but not intrusive thoughts. Correlations were inconclusive for anger and sadness. The results suggest intrusive images and thoughts can be manipulated independently and as such can be considered different phenomena.

Threat assessment and sensor management in a modular architecture

NASA Astrophysics Data System (ADS)

Page, S. F.; Oldfield, J. P.; Islip, S.; Benfold, B.; Brandon, R.; Thomas, P. A.; Stubbins, D. J.

2016-10-01

Many existing asset/area protection systems, for example those deployed to protect critical national infrastructure, are comprised of multiple sensors such as EO/IR, radar, and Perimeter Intrusion Detection Systems (PIDS), loosely integrated with a central Command and Control (C2) system. Whilst some sensors provide automatic event detection and C2 systems commonly provide rudimentary multi-sensor rule based alerting, the performance of such systems is limited by the lack of deep integration and autonomy. As a result, these systems have a high degree of operator burden. To address these challenges, an architectural concept termed "SAPIENT" was conceived. SAPIENT is based on multiple Autonomous Sensor Modules (ASMs) connected to a High-Level Decision Making Module (HLDMM) that provides data fusion, situational awareness, alerting, and sensor management capability. The aim of the SAPIENT concept is to allow for the creation of a surveillance system, in a modular plug-and-play manner, that provides high levels of autonomy, threat detection performance, and reduced operator burden. This paper considers the challenges associated with developing an HLDMM aligned with the SAPIENT concept, through the discussion of the design of a realised HLDMM. Particular focus is drawn to how high levels of system level performance can be achieved whilst retaining modularity and flexibility. A number of key aspects of our HLDMM are presented, including an integrated threat assessment and sensor management framework, threat sequence matching, and ASM trust modelling. The results of real-world testing of the HLDMM, in conjunction with multiple Laser, Radar, and EO/IR sensors, in representative semi-urban environments, are discussed.

Heterogeneous VM Replication: A New Approach to Intrusion Detection, Active Response and Recovery in Cloud Data Centers

DTIC Science & Technology

2015-08-17

from the same execution history, and cost-effective active response by proactively setting up standby VM replicas: migration from a compromised VM...the guest OSes system call code to be reused inside a “shadowed” portion of the context of the out-of- guest inspection program. Besides...by the rootkits in cloud environments. RootkitDet detects rootkits by identifying suspicious code region in the kernel space of guest OSes through

Report of the Task Group on Independent Research and Development

DTIC Science & Technology

1967-02-01

in 1959 when the technology used in prospecting for oil by seismic means was employed to detect and sug- gest the source of earth shocks generated by...result of TI’ s work in seismology for oil exploration. The use of seismometers for intrusion detection stemmed from the large, unde- sirable signals...produced by any human movement during oil -field seismic tests. The first military contract for six test models of these devices was received in 1963

Real-time determination of the efficacy of residual disinfection to limit wastewater contamination in a water distribution system using filtration-based luminescence.

PubMed

Lee, Jiyoung; Deininger, Rolf A

2010-05-01

Water distribution systems can be vulnerable to microbial contamination through cross-connections, wastewater backflow, the intrusion of soiled water after a loss of pressure resulting from an electricity blackout, natural disaster, or intentional contamination of the system in a bioterrrorism event. The most urgent matter a water treatment utility would face in this situation is detecting the presence and extent of a contamination event in real-time, so that immediate action can be taken to mitigate the problem. The current approved microbiological detection methods are culture-based plate count methods, which require incubation time (1 to 7 days). This long period of time would not be useful for the protection of public health. This study was designed to simulate wastewater intrusion in a water distribution system. The objectives were 2-fold: (1) real-time detection of water contamination, and (2) investigation of the sustainability of drinking water systems to suppress the contamination with secondary disinfectant residuals (chlorine and chloramine). The events of drinking water contamination resulting from a wastewater addition were determined by filtration-based luminescence assay. The water contamination was detected by luminescence method within 5 minutes. The signal amplification attributed to wastewater contamination was clear-102-fold signal increase. After 1 hour, chlorinated water could inactivate 98.8% of the bacterial contaminant, while chloraminated water reduced 77.2%.

Non-intrusive tunable resonant microwave cavity for optical detected magnetic resonance of NV centres in nanodiamonds

NASA Astrophysics Data System (ADS)

Le Floch, Jean-Michel; Bradac, Carlo; Volz, Thomas; Tobar, Michael E.; Castelletto, Stefania

2013-12-01

Optically detected magnetic resonance (ODMR) in nanodiamond nitrogen-vacancy (NV) centres is usually achieved by applying a microwave field delivered by micron-size wires, strips or antennas directly positioned in very close proximity (~ μm) of the nanodiamond crystals. The microwave field couples evanescently with the ground state spin transition of the NV centre (2.87 GHz at zero magnetic field), which results in a reduction of the centre photoluminescence. We propose an alternative approach based on the construction of a dielectric resonator. We show that such a resonator allows for the efficient detection of NV spins in nanodiamonds without the constraints associated to the laborious positioning of the microwave antenna next to the nanodiamonds, providing therefore improved flexibility. The resonator is based on a tunable Transverse Electric Mode in a dielectric-loaded cavity, and we demonstrate that the resonator can detect single NV centre spins in nanodiamonds using less microwave power than alternative techniques in a non-intrusive manner. This method can achieve higher precision measurement of ODMR of paramagnetic defects spin transition in the micro to millimetre-wave frequency domain. Our approach would permit the tracking of NV centres in biological solutions rather than simply on the surface, which is desirable in light of the recently proposed applications of using nanodiamonds containing NV centres for spin labelling in biological systems with single spin and single particle resolution.

Petrology of Ortsog-Uul peridotite-gabbro massif in Western Mongolia

NASA Astrophysics Data System (ADS)

Shapovalova, M.; Tolstykh, N.; Shelepaev, R.; Cherdantseva, M.

2017-12-01

The Ortsog-Uul mafic-ultramafic massif of Western Mongolia is located in a tectonic block with overturned bedding. The massif hosts two intrusions: a rhythmically-layered peridotite-gabbro association (Intrusion 1) and massive Bt-bearing amphibole-olivine gabbro (Intrusion 2). Intrusions 1 and 2 have different petrology features. Early Intrusion 1 (278±2.5Ma) is characterized by lower concentrations of alkalis, titanium and phosphorus than late Intrusion 2 (272±2Ma). The chondrite-normalized REE and primitive mantle-normalized rare elements patterns of Ortsog-Uul intrusions have similar curves of elements distribution. However, Intrusion 2 is characterized higher contents of REE and rare elements. High concentrations of incompatible elements are indicative of strong fractionation process. It has been suggested that Intrusions 1 and 2 derived from compositionally different parental melts. Model calculations (COMAGMAT-3.57) show that parental melts of two intrusions were close to high-Mg picrobasaltic magmas. The concentration of MgO in melt is 16.21 (Intrusion 1) and 16.17 (Intrusion 2). Isotopic data of Ortsog-Uul magmatic rocks exhibit different values of εNd (positive and negative) for Intrusion 1 and 2, respectively.

A python framework for environmental model uncertainty analysis

USGS Publications Warehouse

White, Jeremy; Fienen, Michael N.; Doherty, John E.

2016-01-01

We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

Does the arousal system contribute to near death experience?

PubMed

Nelson, Kevin R; Mattingly, Michelle; Lee, Sherman A; Schmitt, Frederick A

2006-04-11

The neurophysiologic basis of near death experience (NDE) is unknown. Clinical observations suggest that REM state intrusion contributes to NDE. Support for the hypothesis follows five lines of evidence: REM intrusion during wakefulness is a frequent normal occurrence, REM intrusion underlies other clinical conditions, NDE elements can be explained by REM intrusion, cardiorespiratory afferents evoke REM intrusion, and persons with an NDE may have an arousal system predisposing to REM intrusion. To investigate a predisposition to REM intrusion, the life-time prevalence of REM intrusion was studied in 55 NDE subjects and compared with that in age/gender-matched control subjects. Sleep paralysis as well as sleep-related visual and auditory hallucinations were substantially more common in subjects with an NDE. These findings anticipate that under circumstances of peril, an NDE is more likely in those with previous REM intrusion. REM intrusion could promote subjective aspects of NDE and often associated syncope. Suppression of an activated locus ceruleus could be central to an arousal system predisposed to REM intrusion and NDE.

Data based abnormality detection

NASA Astrophysics Data System (ADS)

Purwar, Yashasvi

Data based abnormality detection is a growing research field focussed on extracting information from feature rich data. They are considered to be non-intrusive and non-destructive in nature which gives them a clear advantage over conventional methods. In this study, we explore different streams of data based anomalies detection. We propose extension and revisions to existing valve stiction detection algorithm supported with industrial case study. We also explored the area of image analysis and proposed a complete solution for Malaria diagnosis. The proposed method is tested over images provided by pathology laboratory at Alberta Health Service. We also address the robustness and practicality of the solution proposed.

Geologic map of the Callville Bay Quadrangle, Clark County, Nevada, and Mohave County, Arizona

USGS Publications Warehouse

Anderson, R. Ernest

2003-01-01

Report: 139 Map Scale: 1:24,000 Map Type: colored geologic map A 1:24,000-scale, full-color geologic map and four cross sections of the Callville Bay 7-minute quadrangle in Clark County, Nevada and Mohave County, Arizona. An accompanying text describes 21 stratigraphic units of Paleozoic and Mesozoic sedimentary rocks and 40 units of Cenozoic sedimentary, volcanic, and intrusive rocks. It also discusses the structural setting, framework, and history of the quadrangle and presents a model for its tectonic development.

Synchrotron applications in wood preservation and deterioration

Treesearch

Barbara L. Illman

2003-01-01

Several non-intrusive synchrotron techniques are being used to detect and study wood decay. The techniques use high intensity synchrotron-generated X-rays to determine the atomic structure of materials with imaging, diffraction, and absorption. Some of the techniques are X-ray absorption near edge structure (XANES), X-ray fluorescence spectroscopy (XFS), X-ray...

Intrusion Detection and Forensics for Self-Defending Wireless Networks

DTIC Science & Technology

2012-12-01

ICNP), Nov. 2007. 5. Yao Zhao, Yan Chen, Bo Li, and Qian Zhang, Hop ID: A Virtual Coordinate based Routing for Sparse Mobile Ad Hoc Networks, in...Liu, Hongbo Zhao, Kai Chen and Yan Chen, " DISCO : Memory Efficient and Accurate Flow Statistics for Network Measurement", in the Proc. of IEEE ICDCS

A Comparative Analysis of the Snort and Suricata Intrusion-Detection Systems

DTIC Science & Technology

2011-09-01

Category: Test Rules Test #6: Simple LFI Attack 43 Snort True Positive: Snort generated an alert based on the ‘/etc/ passwd ’ string passed...through an HTTP command. Suricata True Positive: Suricata generated an alert based on the ‘/etc/ passwd ’ string passed through an HTTP command

A Multilevel Secure Constrained Intrusion Detection System Prototype

DTIC Science & Technology

2010-12-01

information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and...Reduction Project (0704-0188) Washington DC 20503. 1 . AGENCY USE ONLY (Leave blank) 2. REPORT DATE December 2010 3. REPORT TYPE AND DATES COVERED... 1 A. MOTIVATION....................................................................................... 1 B. PURPOSE OF STUDY

75 FR 16123 - Dave & Buster’s, Inc.; Analysis of Proposed Consent Order to Aid Public Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-31

... computer networks or to conduct security investigations, such as by employing an intrusion detection system and monitoring system logs; (b) failed to adequately restrict third-party access to its networks, such... reasonable and appropriate security for personal information on its computer networks. Among other things...

Impedance Spectroscopy as a Tool for Non-Intrusive Detection of Extracellular Mediators in Microbial Fuel Cells

DTIC Science & Technology

2009-12-01

bioseparation. Hoboken, NJ: John Wiley & Sons, p. 267. HernandezME, Kappler A, Newman DK. 2004. Phenazines and other redox active antibiotics promote...Verstraete W. 2005. Microbial phenazine production enhances electron transfer in biofuel cells. Environ Sci Technol 39:3401. Ramasamy RP, Ren Z, Mench MM

Global Journal of Computer Science and Technology. Volume 1.2

ERIC Educational Resources Information Center

Dixit, R. K.

2009-01-01

Articles in this issue of "Global Journal of Computer Science and Technology" include: (1) Input Data Processing Techniques in Intrusion Detection Systems--Short Review (Suhair H. Amer and John A. Hamilton, Jr.); (2) Semantic Annotation of Stock Photography for CBIR Using MPEG-7 standards (R. Balasubramani and V. Kannan); (3) An Experimental Study…

Wireless Intrusion Detection

DTIC Science & Technology

2007-03-01

32 4.4 Algorithm Pseudo - Code ...................................................................................34 4.5 WIND Interface With a...difference estimates of xc temporal derivatives, or by using a polynomial fit to the previous values of xc. 34 4.4 ALGORITHM PSEUDO - CODE Pseudo ...Phase Shift Keying DQPSK Differential Quadrature Phase Shift Keying EVM Error Vector Magnitude FFT Fast Fourier Transform FPGA Field Programmable

Characterizing and Managing Intrusion Detection System (IDS) Alerts with Multi-Server/Multi-Priority Queuing Theory

DTIC Science & Technology

2014-12-26

administrators dashboard , so that they can be effectively triaged, analyzed, and used to implement defensive actions to keep the network safe and...For the bank teller, some customers will require straight forward services (a quick deposit or cashing a check) while others will have questions or

Mechanisms affecting water quality in an intermittent piped water supply.

PubMed

Kumpel, Emily; Nelson, Kara L

2014-01-01

Drinking water distribution systems throughout the world supply water intermittently, leaving pipes without pressure between supply cycles. Understanding the multiple mechanisms that affect contamination in these intermittent water supplies (IWS) can be used to develop strategies to improve water quality. To study these effects, we tested water quality in an IWS system with infrequent and short water delivery periods in Hubli-Dharwad, India. We continuously measured pressure and physicochemical parameters and periodically collected grab samples to test for total coliform and E. coli throughout supply cycles at 11 sites. When the supply was first turned on, water with elevated turbidity and high concentrations of indicator bacteria was flushed out of pipes. At low pressures (<10 psi), elevated indicator bacteria were frequently detected even when there was a chlorine residual, suggesting persistent contamination had occurred through intrusion or backflow. At pressures between 10 and 17 psi, evidence of periodic contamination suggested that transient intrusion, backflow, release of particulates, or sloughing of biofilms from pipe walls had occurred. Few total coliform and no E. coli were detected when water was delivered with a chlorine residual and at pressures >17 psi.

Hysteretic behavior in seawater intrusion in response to discontinuous drought periods

NASA Astrophysics Data System (ADS)

Salandin, P.; Darvini, G.

2017-12-01

The seawater intrusion (SWI) represents a relevant problem for communities living in many coastal regions and in small islands, where the amount of fresh water available for human consumption or irrigation purposes depends on the equilibrium between the natural groundwater recharge from precipitations and the surrounding sea. This issue is exacerbated by climate changes, and, as a consequence, the reduction of natural groundwater recharge and the decrease the seaward flows of fresh water rather than sea level rise, as recently demonstrated by Ketabchi et al. (2016), leads to magnify the seawater intrusion into coastal aquifers. The temporal fluctuation of the fresh water table level are a natural consequence of the interaction of the aquifer with a water body or due to the seasonal replenishment of the water table. The severe and prolonged drought phenomena as that observed in last years in some areas of the Mediterranean, as over the central western Mediterranean basin, Italy and Spain, where a decreasing trend in total precipitation was detected (Alpert et al., 2002) in addition to the rise in temperature, enlarges the variation of the freshwater flux and can magnify the progression of the saline wedge. In the present study we demonstrate that the presence of varying boundary constraints or forcing factors may lead to hysteretic behavior in saltwater intrusion, showing dependence of the saline wedge on historic conditions. Therefore, the dynamic behavior of SWI may depend on both the present and past forcing conditions. To this aim different transient simulations supported by evidences deduced from a physical model are carried out to assess the presence of the hysteretic effects in the SWI phenomenon and to evaluate its influence in the management of the coastal aquifers for both the rational exploitation and the corrected management of water resources. About 70% of the world's population dwells in coastal zones. Therefore the optimal exploitation of fresh groundwater and the control of seawater intrusion are the challenges of the present day and future water supply engineers and managers. The existence of hysteretic effects further challenges the modelling of wedge saltwater intrusion and indicates that past forcing conditions should be considered in the interpretation of SWI measurements and predictions.

Temporal variability of the Circumpolar Deep Water inflow onto the Ross Sea continental shelf

NASA Astrophysics Data System (ADS)

Castagno, Pasquale; Falco, Pierpaolo; Dinniman, Michael S.; Spezie, Giancarlo; Budillon, Giorgio

2017-02-01

The intrusion of Circumpolar Deep Water (CDW) is the primary source of heat, salt and nutrients onto Antarctica's continental shelves and plays a major role in the shelf physical and biological processes. Different studies have analyzed the processes responsible for the transport of CDW across the Ross Sea shelf break, but until now, there are no continuous observations that investigate the timing of the intrusions. Also, few works have focused on the effect of the tides that control these intrusions. In the Ross Sea, the CDW intrudes onto the shelf in several locations, but mostly along the troughs. We use hydrographic observations and a mooring placed on the outer shelf in the middle of the Drygalski Trough in order to characterize the spatial and temporal variability of CDW inflow onto the shelf. Our data span from 2004 to the beginning of 2014. In the Drygalski Trough, the CDW enters as a 150 m thick layer between 250 and 400 m, and moves upward towards the south. At the mooring location, about 50 km from the shelf break, two main CDW cores can be observed: one on the east side of the trough spreading along the west slope of Mawson Bank from about 200 m to the bottom and the other one in the central-west side from 200 m to about 350 m depth. A signature of this lighter and relatively warm water is detected by the instruments on the mooring at bottom of the Drygalski Trough. High frequency periodic CDW intrusion at the bottom of the trough is related to the diurnal and spring/neap tidal cycles. At lower frequency, a seasonal variability of the CDW intrusion is noticed. A strong inflow of CDW is observed every year at the end of December, while the CDW inflow is at its seasonal minimum during the beginning of the austral fall. In addition an interannual variability is also evident. A change of the CDW intrusion before and after 2010 is observed.

Linking precious metal enrichment and halogen cycling in mafic magmatic systems: insights from the Rum layered intrusion, NW Scotland

NASA Astrophysics Data System (ADS)

Kelly, A. P.; O'Driscoll, B.; Clay, P. L.; Burgess, R.

2017-12-01

Layered intrusions host the world's largest known concentrations of the platinum-group elements (PGE). Emphasis has been attached to the role of halogen-bearing fluids in concentrating the precious metals, but whether this occurs at the magmatic stage, or via subsequent metasomatism, is actively debated. One obstacle to progress has been the analytical difficulty of measuring low abundances of the halogens in the cumulate products of layered intrusions. To elucidate the importance of the halogens in facilitating PGE-mineralisation, as well as fingerprint halogen provenance and assess the importance of halogen cycling in mafic magma systems more generally, a suite of samples encompassing different stages of activity of the Palaeogene Rum layered intrusion was investigated. Halogen abundances were measured by neutron irradiation noble gas mass spectrometric analysis, permitting the detection of relatively low (ppm-ppb) abundances of Cl, Br and I in mg-sized samples. The samples include PGE-enriched chromite seams, various cumulates (e.g., peridotites), picrites (approximating the Rum parental magma), and pegmatites representing volatile-rich melts that circulated the intrusion at a late-stage in its solidification history. The new data reveal that PGE-bearing chromite seams contain relatively low Cl concentrations (2-3 ppm), with high molar ratios of Br/Cl and I/Cl (0.005 and 0.009, respectively). The picrites and cumulates have Br/Cl and I/Cl ratios close to sub-continental lithospheric mantle values of approximately 0.0013 and 0.00002, respectively, and thus likely reflect the Rum magma source region. A positive correlation between Cl and Br signifies comparable partitioning behaviour in all samples. However, I is more variable, displaying a positive correlation with Cl for more primitive samples (e.g. picrite and peridotite), and seemingly decoupling from Br and Cl in chromite seams and pegmatites. The relative enrichment of I over Cl in the chromite seams points to the local involvement of an organic-rich sedimentary assimilant and potentially represents an important trigger for PGE-mineralisation. Similarly high I/Cl signatures in some of the late-stage pegmatites suggest that fluids with this distinctive composition circulated the cooling Rum intrusion for a protracted period of time.

Verifying the secure setup of Unix client/servers and detection of network intrusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feingold, R.; Bruestle, H.R.; Bartoletti, T.

1995-07-01

This paper describes our technical approach to developing and delivering Unix host- and network-based security products to meet the increasing challenges in information security. Today`s global ``Infosphere`` presents us with a networked environment that knows no geographical, national, or temporal boundaries, and no ownership, laws, or identity cards. This seamless aggregation of computers, networks, databases, applications, and the like store, transmit, and process information. This information is now recognized as an asset to governments, corporations, and individuals alike. This information must be protected from misuse. The Security Profile Inspector (SPI) performs static analyses of Unix-based clients and servers to checkmore » on their security configuration. SPI`s broad range of security tests and flexible usage options support the needs of novice and expert system administrators alike. SPI`s use within the Department of Energy and Department of Defense has resulted in more secure systems, less vulnerable to hostile intentions. Host-based information protection techniques and tools must also be supported by network-based capabilities. Our experience shows that a weak link in a network of clients and servers presents itself sooner or later, and can be more readily identified by dynamic intrusion detection techniques and tools. The Network Intrusion Detector (NID) is one such tool. NID is designed to monitor and analyze activity on an Ethernet broadcast Local Area Network segment and produce transcripts of suspicious user connections. NID`s retrospective and real-time modes have proven invaluable to security officers faced with ongoing attacks to their systems and networks.« less

Identification of Tropical-Extratropical Interactions and Extreme Precipitation Events in the Middle East Based On Potential Vorticity and Moisture Transport

NASA Astrophysics Data System (ADS)

de Vries, A. J.; Ouwersloot, H. G.; Feldstein, S. B.; Riemer, M.; El Kenawy, A. M.; McCabe, M. F.; Lelieveld, J.

2018-01-01

Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability, and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.

Tectonic evolution of the Troodos Ophiolite within the Tethyan Framework

NASA Astrophysics Data System (ADS)

Dilek, Yildirim; Thy, Peter; Moores, Eldridge M.; Ramsden, Todd W.

1990-08-01

A new tectonic model reconciles conflicting structural and geochemical evidence for the origin of the Troodos ophiolite, a well-preserved remnant of Neotethyan oceanic crust. Grabens and normal faults within the sheeted dike complex and the extrusive sequence of the Troodos ophiolite resemble those of oceanic spreading centers. Diverse intrusive and tectonic contact relationships between the sheeted dike complex and the underlying plutonic sequence indicate multiple and episodic intrusion of magma and along- and across-strike variation in volcanic and tectonic activity during development of oceanic crust. Coupled with the existence of the Arakapas transform fault to the south, these structural and intrusive relationships suggest origin at an intersection between a spreading center and a transform fault. The arclike chemistry of sheeted dikes and related extrusive rocks and the inferred highly depleted and hydrous nature of the mantle source of the late stage intrusive and extrusive rocks argue, however, for generation of part of the ophiolite within a subduction zone environment. Regional reconstructions suggest that the Mesozoic Neotethys may have evolved as a marginal basin both to the Afro-Arabian continent and the Paleotethyan ocean over an active or recently active south dipping subduction zone. The Troodos ophiolite and other eastern Mediterranean ophiolites, whose magma compositions were affected by the subducted Paleotethyan slab, may have formed along east-west trending spreading centers separated by north-south trending transform faults within this marginal basin. A rapid change in relative plate motion in late Cretaceous time between Eurasia and Afro-Arabia created a regional compressive regime that may have resulted in plate boundary reorganizations within the Neotethyan realm and in initiation of north dipping subduction zone(s) beneath the Troodos and other ophiolites in the region. The apparent forearc setting of the Troodos ophiolite is a consequence of this intraoceanic displacement after its formation and thus is unrelated to its generation.

Episodic growth of a Late Cretaceous and Paleogene intrusive complex of pegmatitic leucogranite, Ruby Mountains core complex, Nevada, USA

USGS Publications Warehouse

Howard, Keith A.; Wooden, J.L.; Barnes, C.G.; Premo, W.R.; Snoke, A.W.; Lee, S.-Y.

2011-01-01

Gneissic pegmatitic leucogranite forms a dominant component (>600 km3) of the midcrustal infrastructure of the Ruby Mountains–East Humboldt Range core complex (Nevada, USA), and was assembled and modified episodically into a batholithic volume by myriad small intrusions from ca. 92 to 29 Ma. This injection complex consists of deformed sheets and other bodies emplaced syntectonically into a stratigraphic framework of marble, calc-silicate rocks, quartzite, schist, and other granitoids. Bodies of pegmatitic granite coalesce around host-rock remnants, which preserve relict or ghost stratigraphy, thrusts, and fold nappes. Intrusion inflated but did not disrupt the host-rock structure. The pegmatitic granite increases proportionally downward from structurally high positions to the bottoms of 1-km-deep canyons where it constitutes 95%–100% of the rock. Zircon and monazite dated by U-Pb (sensitive high-resolution ion microprobe, SHRIMP) for this rock type cluster diffusely at ages near 92, 82(?), 69, 38, and 29 Ma, and indicate successive or rejuvenated igneous crystallization multiple times over long periods of the Late Cretaceous and the Paleogene. Initial partial melting of unexposed pelites may have generated granite forerunners, which were remobilized several times in partial melting events. Sources for the pegmatitic granite differed isotopically from sources of similar-aged interleaved equigranular granites. Dominant Late Cretaceous and fewer Paleogene ages recorded from some pegmatitic granite samples, and Paleogene-only ages from the two structurally deepest samples, together with varying zircon trace element contents, suggest several disparate ages of final emplacement or remobilization of various small bodies. Folded sills that merge with dikes that cut the same folds suggest that there may have been in situ partial remobilization. The pegmatitic granite intrusions represent prolonged and recurrent generation, assembly, and partial melting modification of a batholithic volume even while the regional tectonic environment varied dramatically from contractile thickening to extension and mafic underplating.

AIDE - Advanced Intrusion Detection Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Cathy L.

2013-04-28

Would you like to know when someone has dropped an undesirable executable binary on our system? What about something less malicious such as a software installation by a user? What about the user who decides to install a newer version of mod_perl or PHP on your web server without letting you know beforehand? Or even something as simple as when an undocumented config file change is made by another member of the admin group? Do you even want to know about all the changes that happen on a daily basis on your server? The purpose of an intrusion detection systemmore » (IDS) is to detect unauthorized, possibly malicious activity. The purpose of a host-based IDS, or file integrity checker, is check for unauthorized changes to key system files, binaries, libraries, and directories on the system. AIDE is an Open Source file and directory integrity checker. AIDE will let you know when a file or directory has been added, deleted, modified. It is included with the Red Hat Enterprise 6. It is available for other Linux distros. This is a case study describing the process of configuring AIDE on an out of the box RHEL6 installation. Its goal is to illustrate the thinking and the process by which a useful AIDE configuration is built.« less

Non-contact arrhythmia assessment in natural settings: a step toward preventive cardiac care

NASA Astrophysics Data System (ADS)

Amelard, Robert; Hughson, Richard L.; Clausi, David A.; Wong, Alexander

2017-02-01

Cardiovascular disease is a major contributor to US morbidity. Taking preventive action can greatly reduce or eliminate the impact on quality of life. However, many issues often go undetected until the patient presents a physical symptom. Non-intrusive continuous cardiovascular monitoring systems may make detecting and monitoring abnormalities earlier feasible. One candidate system is photoplethysmographic imaging (PPGI), which is able to assess arterial blood pulse characteristics in one or multiple individuals remotely from a distance. In this case study, we showed that PPGI can be used to detect cardiac arrhythmia that would otherwise require contact-based monitoring techniques. Using a novel system, coded hemodynamic imaging (CHI), strong temporal blood pulse waveform signals were extracted at a distance of 1.5 m from the participant using 850-1000 nm diffuse illumination for deep tissue penetration. Data were recorded at a sampling rate of 60 Hz, providing a temporal resolution of 17 ms. The strong fidelity of the signal allowed for both temporal and spectral assessment of abnormal blood pulse waveforms, ultimately to detect the onset of abnormal cardiac events. Data from a participant with arrhythmia was analyzed and compared against normal blood pulse waveform data to validate CHI's ability to assess cardiac arrhythmia. Results indicate that CHI can be used as a non-intrusive continuous cardiac monitoring system.

A Non-Intrusive Pressure Sensor by Detecting Multiple Longitudinal Waves

PubMed Central

Zhou, Hongliang; Lin, Weibin; Ge, Xiaocheng; Zhou, Jian

2016-01-01

Pressure vessels are widely used in industrial fields, and some of them are safety-critical components in the system—for example, those which contain flammable or explosive material. Therefore, the pressure of these vessels becomes one of the critical measurements for operational management. In the paper, we introduce a new approach to the design of non-intrusive pressure sensors, based on ultrasonic waves. The model of this sensor is built based upon the travel-time change of the critically refracted longitudinal wave (LCR wave) and the reflected longitudinal waves with the pressure. To evaluate the model, experiments are carried out to compare the proposed model with other existing models. The results show that the proposed model can improve the accuracy compared to models based on a single wave. PMID:27527183

Flexible and Transparent User Authentication for Mobile Devices

NASA Astrophysics Data System (ADS)

Clarke, Nathan; Karatzouni, Sevasti; Furnell, Steven

The mobile device has become a ubiquitous technology that is capable of supporting an increasingly large array of services, applications and information. Given their increasing importance, it is imperative to ensure that such devices are not misused or abused. Unfortunately, a key enabling control to prevent this, user authentication, has not kept up with the advances in device technology. This paper presents the outcomes of a 2 year study that proposes the use of transparent and continuous biometric authentication of the user: providing more comprehensive identity verification; minimizing user inconvenience; and providing security throughout the period of use. A Non-Intrusive and Continuous Authentication (NICA) system is described that maintains a continuous measure of confidence in the identity of the user, removing access to sensitive services and information with low confidence levels and providing automatic access with higher confidence levels. An evaluation of the framework is undertaken from an end-user perspective via a trial involving 27 participants. Whilst the findings raise concerns over education, privacy and intrusiveness, overall 92% of users felt the system offered a more secure environment when compared to existing forms of authentication.

Understanding the Laminar Distribution of Tropospheric Ozone from Ground-Based, Airborne, Spaceborne, and Modeling Perspectives

NASA Technical Reports Server (NTRS)

Newchurch, Mike; Johnson, Matthew S.; Huang, Guanyu; Kuang, Shi; Wang, Lihua; Chance, Kelly; Liu, Xiong

2016-01-01

Laminar ozone structure is a ubiquitous feature of tropospheric-ozone distributions resulting from dynamic and chemical atmospheric processes. Understanding the characteristics of these ozone laminae and the mechanisms responsible for producing them is important to outline the transport pathways of trace gases and to quantify the impact of different sources on tropospheric background ozone. In this study, we present a new method to detect ozone laminae to understand their climatological characteristics of occurrence frequency in terms of thickness and altitude. We employ both ground-based and airborne ozone lidar measurements and other synergistic observations and modeling to investigate the sources and mechanisms such as biomass burning transport, stratospheric intrusion, lightning-generated NOx, and nocturnal low-level jets that are responsible for depleted or enhanced tropospheric ozone layers. Spaceborne (e.g., OMI (Ozone Monitoring Instrument), TROPOMI (Tropospheric Monitoring Instrument), TEMPO (Tropospheric Emissions: Monitoring of Pollution)) measurements of these laminae will observe greater horizontal extent and lower vertical resolution than balloon-borne or lidar measurements will quantify. Using integrated ground-based, airborne, and spaceborne observations in a modeling framework affords insight into how to gain knowledge of both the vertical and horizontal evolution of these ubiquitous ozone laminae.

Evaluation of a Cyber Security System for Hospital Network.

PubMed

Faysel, Mohammad A

2015-01-01

Most of the cyber security systems use simulated data in evaluating their detection capabilities. The proposed cyber security system utilizes real hospital network connections. It uses a probabilistic data mining algorithm to detect anomalous events and takes appropriate response in real-time. On an evaluation using real-world hospital network data consisting of incoming network connections collected for a 24-hour period, the proposed system detected 15 unusual connections which were undetected by a commercial intrusion prevention system for the same network connections. Evaluation of the proposed system shows a potential to secure protected patient health information on a hospital network.

Impact of exogenous cortisol on the formation of intrusive memories in healthy women.

PubMed

Rombold, Felicitas; Wingenfeld, Katja; Renneberg, Babette; Schwarzkopf, Friederike; Hellmann-Regen, Julian; Otte, Christian; Roepke, Stefan

2016-12-01

Stress hormones such as cortisol are involved in modulating emotional memory. However, little is known about the influence of cortisol on the formation of intrusive memories after a traumatic event. The aim of this study was to examine whether cortisol levels during encoding and consolidation of an intrusion-inducing trauma film paradigm would influence subsequent intrusion formation. In an experimental, double-blind, placebo-controlled study a trauma film paradigm was used to induce intrusions in 60 healthy women. Participants received a single dose of either 20 mg hydrocortisone or placebo before watching a trauma film. Salivary cortisol and alpha-amylase as well as blood pressure were measured during the experiment. The consecutive number of intrusions, the vividness of intrusions, and the degree of distress evoked by the intrusions resulting from the trauma film were assessed throughout the following seven days. Hydrocortisone administration before the trauma film resulted in increased salivary cortisol levels but did not affect the consecutive number of intrusions, the vividness of intrusions, and the degree of distress evoked by the intrusions throughout the following week. These results indicate that pharmacologically increased cortisol levels during an experimental trauma film paradigm do not influence consecutive intrusive memories. Current data do not support a prominent role of exogenous cortisol on intrusive memories, at least in healthy young women after a relatively mild trauma equivalent. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dyke emplacement in a Quaternary active volcano: the exposed swarm of Monte Somma-Vesuvio (Naples, Italy)

NASA Astrophysics Data System (ADS)

Marinoni, L. B.

2003-04-01

The Monte Somma-Vesuvius is a famous active stratovolcano located on the Bay of Naples (Italy). Unexpectedly, the intrusive complex of this volcano is poorly known. This work focuses on the moderate-intensity dyke swarm that crops out along the caldera wall cut in the Monte Somma (MS) and its host rock. A detailed field survey of 101 individual intrusions consisted of the recording of about 20 parameters for each intrusion according to a standardised method. The intrusions were located in the framework of a new geological map drawn for the caldera wall at a scale 1:2000. The MS intrusions that crop out from 780 to 1055 m a.s.l., are mostly monogenetic steeply-dipping segmented dykes; inclined sheets are also present, generally dipping towards the outer periphery of the volcano. Apparent crosscut due to dyke segmentation is common; true intersections show ambiguous alternation of dyke strikes. Indicators of initial intrusive flow (opening stage of the dyke-hosting fracture) often differ in direction and sense from late-stage indicators. Frequently, dykes intruded sub-horizontally in an early stage and later sub-vertically. The peak extension for MS, computed according to a standardised method, is 81.7 m in the direction N90°, based on 96 exposed sheets. Very likely, most of MS sheets intruded within ~12 ka, giving a time-averaged minimum extension rate of ~7 mm a-1. On MS, the azimuth pattern and the azimuth of peak extension are different in the two portions in which the caldera wall can be divided, east and west of Canale dell'Arena. This difference may indicate that two fault systems affecting the basement underneath the volcano exert their influence on the feeding system. On the other hand, three main dyke sets (among which the set trending NE-SW is prevalent) exist on MS, and inclined sheets form a significant portion of the intrusions. In addition, the peak extension and the percentage extension are comparable quantitatively in the two different sections of the caldera. Moreover, the cumulative minimum extension (in direction N25°) corresponds to 75% of the maximum extension (in direction N90°). This value is similar to that computed for Etna (78%), where the influence of self-induced stresses on dyke emplacement is well-assessed. This may suggest that self-induced stresses constrained the emplacement of the MS sheet swarm. Therefore, interplay of the regional stress field from the basement, with the self-induced radial stress field may be envisaged for MS. The stratigraphic study along the caldera wall of MS, shows a long history of edifice instability that, together with structural data and with the apparent asymmetry of the volcano, provides clues to the possibility of past flank failures directed towards W-SW.

Enhanced Deployment Strategy for Role-based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

NASA Astrophysics Data System (ADS)

Gendreau, Audrey

Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing application had established the network traffic flow to the sink. The same scenario was repeated using a power-based IDS to compare it against the proposed model. To identify a clusterhead's ability to host monitoring agents after the temperature sensing application terminated, the deployed IDS utilized the communication history and other network factors in order to rank the nodes. Similarly, using the node's communication history, the deployed power-based IDS ranked nodes based on their remaining power. For each individual scenario, and after the IDS application was deployed, the temperature sensing application was run for a second time. This time, to monitor the temperature sensing agents as the data flowed towards the sink, the network traffic was rerouted through the new intrusion detection clusterheads. Consequently, if the clusterheads were shared, the re-routing step was not preformed. Experimental results in this research demonstrated the effectiveness of applying a robust deployment metric to improve upon the energy efficiency of a deployed application in a multi-application WSN. It was found that in the scenarios with the intrusion detection application that utilized the proposed model resulted in more remaining energy than in the scenarios that implemented the power-based IDS. The algorithm especially had a positive impact on the small, dense, and more homogeneous networks. This finding was reinforced by the smaller percentage of new clusterheads that was selected. Essentially, the energy cost of the route to the sink was reduced because the network traffic was rerouted through fewer new clusterheads. Additionally, it was found that the intrusion detection topology that used the proposed approach formed smaller and more connected sets of clusterheads than the power-based IDS. As a consequence, this proposed approach essentially achieved the research objective for enhancing energy use in a multi-application WSN.

Co-Simulation Platform For Characterizing Cyber Attacks in Cyber Physical Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadi, Mohammad A. H.; Ali, Mohammad Hassan; Dasgupta, Dipankar

Smart grid is a complex cyber physical system containing a numerous and variety of sources, devices, controllers and loads. Communication/Information infrastructure is the backbone of the smart grid system where different grid components are connected with each other through this structure. Therefore, the drawbacks of the information technology related issues are also becoming a part of the smart grid. Further, smart grid is also vulnerable to the grid related disturbances. For such a dynamic system, disturbance and intrusion detection is a paramount issue. This paper presents a Simulink and OPNET based co-simulated test bed to carry out a cyber-intrusion inmore » a cyber-network for modern power systems and smart grid. The effect of the cyber intrusion on the physical power system is also presented. The IEEE 30 bus power system model is used to demonstrate the effectiveness of the simulated testbed. The experiments were performed by disturbing the circuit breakers reclosing time through a cyber-attack in the cyber network. Different disturbance situations in the proposed test system are considered and the results indicate the effectiveness of the proposed co-simulated scheme.« less

The cyber security threat stops in the boardroom.

PubMed

Scully, Tim

The attitude that 'it won't happen to me' still prevails in the boardrooms of industry when senior executives consider the threat of targeted cyber intrusions. Not much has changed in the commercial world of cyber security over the past few years; hackers are not being challenged to find new ways to steal companies' intellectual property and confidential information. The consequences of even major security breaches seem not to be felt by the leaders of victim companies. Why is this so? Surely IT security practitioners are seeking new ways to detect and prevent targeted intrusions into companies' networks? Are the consequences of targeted intrusions so insignificant that the captains of industry tolerate them? Or do only others feel the pain of their failure? This paper initially explores the failure of cyber security in industry and contends that, while industry leaders should not be alone in accepting responsibility for this failure, they must take the initiative to make life harder for cyber threat actors. They cannot wait for government leadership on policy, strategy or coordination. The paper then suggests some measures that a CEO can adopt to build a new corporate approach to cyber security.

Topical Review: Integrating Findings on Direct Observation of Family Communication in Studies Comparing Pediatric Chronic Illness and Typically Developing Samples.

PubMed

Murphy, Lexa K; Murray, Caitlin B; Compas, Bruce E

2017-01-01

To review research on observed family communication in families with children with chronic illnesses compared with families with healthy, typically developing children, and to integrate findings utilizing a unifying family communication framework. Topical review of studies that have directly observed family communication in pediatric populations and included a typically developing comparison group. Initial findings from 14 studies with diverse approaches to quantifying observed family communication suggest that families with children with chronic illnesses may demonstrate lower levels of warm and structured communication and higher levels of hostile/intrusive and withdrawn communication compared with families with healthy, typically developing children. An integrative framework of family communication may be used in future studies that examine the occurrence, correlates, and mechanisms of family communication in pediatric populations.

Intrusion-based reasoning and depression: cross-sectional and prospective relationships.

PubMed

Berle, David; Moulds, Michelle L

2014-01-01

Intrusion-based reasoning refers to the tendency to form interpretations about oneself or a situation based on the occurrence of a negative intrusive autobiographical memory. Intrusion-based reasoning characterises post-traumatic stress disorder, but has not yet been investigated in depression. We report two studies that aimed to investigate this. In Study 1 both high (n = 42) and low (n = 28) dysphoric participants demonstrated intrusion-based reasoning. High-dysphoric individuals engaged in self-referent intrusion-based reasoning to a greater extent than did low-dysphoric participants. In Study 2 there were no significant differences in intrusion-based reasoning between currently depressed (n = 27) and non-depressed (n = 51) participants, and intrusion-based reasoning did not predict depressive symptoms at 6-month follow-up. Interestingly, previously (n = 26) but not currently (n = 27) depressed participants engaged in intrusion-based reasoning to a greater extent than never-depressed participants (n = 25), indicating the possibility that intrusion-based reasoning may serve as a "scar" from previous episodes. The implications of these findings are discussed.

Effects of intrusions on grades and contents of gold and other metals in volcanogenic massive sulfide deposits

USGS Publications Warehouse

Singer, Donald A.; Berger, Vladimir; Mosier, Dan L.

2011-01-01

The reason some VMS deposits contain more gold or other metals than others might be due to the influence of intrusions. A new approach examining this possibility is based on examining the information about many VMS deposits to test statistically if those with associated intrusions have significantly different grades or amounts of metals. A set of 632 VMS deposits with reported grades, tonnages, and information about the observed presence or absence of subvolcanic or plutonic intrusive bodies emplaced at or after VMS mineralization is statistically analyzed.Deposits with syn-mineralization or post-mineralization intrusions nearby have higher tonnages than deposits without reported intrusions, but the differences are not statistically significant. When both kinds of intrusions are reported, VMS deposit sizes are significantly higher than in the deposits without any intrusions. Gold, silver, zinc, lead, and copper average grades are not significantly different in the VMS deposits with nearby intrusions compared to deposits without regardless of relative age of intrusive. Only zinc and copper contents are significantly higher in VMS deposits with both kinds of intrusive reported. These differences in overall metal content are due to significantly larger deposit sizes of VMS deposits where both intrusive kinds are observed and reported, rather than any difference in metal grades.

Retrospective evaluation of complete-arch fixed partial dentures connecting teeth and implant abutments in patients with normal and reduced periodontal support.

PubMed

Cordaro, Luca; Ercoli, Carlo; Rossini, Carlo; Torsello, Ferruccio; Feng, Changyong

2005-10-01

The clinical outcome of complete-arch fixed prostheses supported by implants and natural tooth abutments in patients with normal or reduced periodontal support has been reported by few studies, with controversial results. The purpose of this study was to report on the implant success rate, prosthetic complications, and the occurrence of tooth intrusion, when complete-arch fixed prostheses, supported by a combination of implants and teeth, were fabricated for patients with normal and reduced periodontal support. Nineteen patients with residual teeth that served as abutments were consecutively treated with combined tooth- and implant-supported complete-arch fixed prostheses and were retrospectively evaluated after a period varying from 24 to 94 months. Nine patients showed reduced periodontal support as a result of periodontal disease and treatment (RPS group), and 10 patients had normal periodontal support of the abutment teeth (more than 2/3 of periodontal support [NPS group]). Ninety implants and 72 tooth abutments were used to support 19 fixed partial dentures. Screw- and cement-retained metal-ceramic and metal-resin prostheses were fabricated with rigid and nonrigid connectors. Implant survival and success rates, occurrence of caries and tooth intrusion, and prosthetic complications were recorded. The number of teeth, implants, prosthetic units, fixed partial dentures, and nonrigid connectors were compared with a t test to assess differences between the 2 groups, while data for the occurrence of intrusions and prosthetic complications were compared with the Fisher exact test (alpha=.05). One of the 90 implants was lost (99% survival rate) over 24 to 94 months, while 3 implants showed more than 2 mm of crestal bone loss (96% success rate) over the same period. No caries were detected, but 5.6% (4/72) of the abutment teeth exhibited intrusion. Intrusion of abutment teeth was noted in 3 patients who had normal periodontal support (13% of teeth in NPS group) of the abutment teeth and was associated with nonrigid connectors. No intrusion of teeth was noted in the patients exhibiting reduced periodontal support regardless of the type of connector or when a rigid connector was used for either group. The number of intruded teeth was significantly greater in patients with intact periodontal support (P=.03). Complete-arch fixed prosthesis supported by implant and tooth abutments may be associated with intrusion of teeth with intact periodontal support when nonrigid connectors are used to join the implant- and tooth-supported sections of the prostheses. However, fixed partial dentures supported by implants and teeth with reduced periodontal support were not associated with tooth intrusion, regardless of the type of connectors used.

Simulating spatial adaption of groundwater pumping on seawater intrusion in coastal regions

NASA Astrophysics Data System (ADS)

Grundmann, Jens; Ladwig, Robert; Schütze, Niels; Walther, Marc

2016-04-01

Coastal aquifer systems are used intensively to meet the growing demands for water in those regions. They are especially at risk for the intrusion of seawater due to aquifer overpumping, limited groundwater replenishment and unsustainable groundwater management which in turn also impacts the social and economical development of coastal regions. One example is the Al-Batinah coastal plain in northern Oman where irrigated agriculture is practiced by lots of small scaled farms in different distances from the sea, each of them pumping their water from coastal aquifer. Due to continuous overpumping and progressing saltwater intrusion farms near the coast had to close since water for irrigation got too saline. For investigating appropriate management options numerical density dependent groundwater modelling is required which should also portray the adaption of groundwater abstraction schemes on the water quality. For addressing this challenge a moving inner boundary condition is implemented in the numerical density dependent groundwater model which adjusts the locations for groundwater abstraction according to the position of the seawater intrusion front controlled by thresholds of relative chloride concentration. The adaption process is repeated for each management cycle within transient model simulations and allows for considering feedbacks with the consumers e.g. the agriculture by moving agricultural farms more inland or towards the sea if more fertile soils at the coast could be recovered. For finding optimal water management strategies efficiently, the behaviour of the numerical groundwater model for different extraction and replenishment scenarios is approximated by an artificial neural network using a novel approach for state space surrogate model development. Afterwards the derived surrogate is coupled with an agriculture module within a simulation based water management optimisation framework to achieve optimal cropping pattern and water abstraction schemes regarding multiple objectives like aquifer sustainability and profitable agriculture. Results obtained for the above mentioned region show that the surrogate model has a very good interpolation capability i.e. it is able to reproduce unknown states obtained by numerical model simulations within the range of its training data. Furthermore, the importance of portraying the adaptive behaviour of farmers on water quality is underlined to develop management scenarios more realistically. However, results of a stop pumping scenario show that it is not possible to push back an advanced seawater intrusion in a time period of 200 years. Therefore, combinations of technical and adaptive measures are required.

The ages and tectonic setting of the Faja Eruptiva de la Puna Oriental, Ordovician, NW Argentina

NASA Astrophysics Data System (ADS)

Bahlburg, Heinrich; Berndt, Jasper; Gerdes, Axel

2016-07-01

The Ordovician Faja Eruptiva de la Puna Oriental is a magmatic, predominantly intrusive belt in the Puna of northwestern Argentina with a N-S extension of ca. 400 km. Scarce isotope geochemical ages and biostratigraphic data on some of the folded Faja Eruptiva country rocks assign the magmatism either to the Lower and lower Middle Ordovician, or to the latest Ordovician. Interpretations of origin and tectonic framework of the Faja Eruptiva are controversial and vary between arc, back-arc and collisional-orogenic settings. We present high-resolution La-ICP-MS U-Pb age and Hf isotope data on zircons from 10 plutonic samples covering the magmatic belt along a length of 200 km in the northern Argentinian Puna. The xenocrystic and magmatic zircon age data have a wide spread between 2700 Ma and 440 Ma. Concordia and weighted mean age data document protracted magmatism in two phases between 480 and 460 Ma, and between 453 and 444 Ma, and constrain the time of the last intrusions at 444 ± 3 Ma and at 445 ± 2 Ma thus defining this last and main phase of intrusion at 444 Ma. εHf(t) values define a main vertical trend centered at 500 Ma with εHf(t) values between + 3 and - 16 indicating significant mixing of juvenile early Paleozoic melts with Paleoproterozoic crustal components. A second trend is formed by zircons with ages between 1.1 Ga and c. 500 Ma and predominantly positive εHf values between + 8 and - 3 and originates in juvenile mantle compositions between 1.6 and 1.1 Ga. The spread of the zircon and Hf data document that the Faja Eruptiva intrusives have experienced large-scale contamination by the hosting crustal basement. It follows that the basement of the Puna is formed either by the upper Proterozoic-lower Cambrian Puncoviscana Formation as an erosional product of the Proterozoic orogenic belts of SW Amazonia or that the Puna including its Puncoviscana basement is underlain by a crust shaped by these orogenies. The main intrusive event at 444 Ma has been linked to the Oclóyic orogeny in the Late Ordovician. The plutons intruded very likely in a sinistral strike-slip regime after the main folding phase of the Oclóyic orogeny had deformed the Ordovician sedimentary country rocks.

10 CFR 63.322 - Human intrusion scenario.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 2 2010-01-01 2010-01-01 false Human intrusion scenario. 63.322 Section 63.322 Energy... REPOSITORY AT YUCCA MOUNTAIN, NEVADA Postclosure Public Health and Environmental Standards Human Intrusion Standard § 63.322 Human intrusion scenario. For the purposes of the analysis of human intrusion, DOE must...

An Historical Analysis of Factors Contributing to the Emergence of the Intrusion Detection Discipline and its Role in Information Assurance

DTIC Science & Technology

2005-03-01

computing equipment, the idea of computer security has also become embedded in our society. Ever since the Michelangelo virus of 1992, when...Bibliography TheWorldwide Michelangelo Virus Scare of 1992. Retrieved February 2, 2004 from http://www.vmyths.com/fas/fas_inc/inc1.cfm Allen, J

DOE Office of Scientific and Technical Information (OSTI.GOV)

Troy Hiltbrand; Daniel Jones

As we look at the cyber security ecosystem, are we planning to fight the battle as we did yesterday, with firewalls and intrusion detection systems (IDS), or are we sensing a change in how security is evolving and planning accordingly? With the technology enablement and possible financial benefits of cloud computing, the traditional tools for establishing and maintaining our cyber security ecosystems are being dramatically altered.

Characterization of Extremely Lightweight Intrusion Detection (ELIDe) Power Utilization by Varying N-gram and Hash Length

DTIC Science & Technology

2015-09-01

changing the weight file used without redeploying the application. 2.1 Mobile Device We used the same Sprint-brand Galaxy S3 smart phone. The... Galaxy S3 line of smart phones varied in its technical specifications depending on the carrier. For reference, the Sprint-brand Galaxy S3 has the

10 CFR 73.67 - Licensee fixed site and in-transit requirements for the physical protection of special nuclear...

Code of Federal Regulations, 2010 CFR

2010-01-01

... detection and surveillance of unauthorized penetration or activities, (3) Monitor with an intrusion alarm or... acknowledges the specified mode of transport, (iii) Check the integrity of the container and locks or seals... material of moderate strategic significance shall: (i) Check the integrity of the containers and seals upon...

10 CFR 73.67 - Licensee fixed site and in-transit requirements for the physical protection of special nuclear...

Code of Federal Regulations, 2013 CFR

2013-01-01

... detection and surveillance of unauthorized penetration or activities, (3) Monitor with an intrusion alarm or... acknowledges the specified mode of transport, (iii) Check the integrity of the container and locks or seals... material of moderate strategic significance shall: (i) Check the integrity of the containers and seals upon...

10 CFR 73.67 - Licensee fixed site and in-transit requirements for the physical protection of special nuclear...

Code of Federal Regulations, 2014 CFR

2014-01-01

... detection and surveillance of unauthorized penetration or activities, (3) Monitor with an intrusion alarm or... acknowledges the specified mode of transport, (iii) Check the integrity of the container and locks or seals... material of moderate strategic significance shall: (i) Check the integrity of the containers and seals upon...

10 CFR 73.67 - Licensee fixed site and in-transit requirements for the physical protection of special nuclear...

Code of Federal Regulations, 2012 CFR

2012-01-01

... detection and surveillance of unauthorized penetration or activities, (3) Monitor with an intrusion alarm or... acknowledges the specified mode of transport, (iii) Check the integrity of the container and locks or seals... material of moderate strategic significance shall: (i) Check the integrity of the containers and seals upon...

10 CFR 73.67 - Licensee fixed site and in-transit requirements for the physical protection of special nuclear...

Code of Federal Regulations, 2011 CFR

2011-01-01

... detection and surveillance of unauthorized penetration or activities, (3) Monitor with an intrusion alarm or... acknowledges the specified mode of transport, (iii) Check the integrity of the container and locks or seals... material of moderate strategic significance shall: (i) Check the integrity of the containers and seals upon...

The Worry List: What They Are and How to Deal with Them

ERIC Educational Resources Information Center

Technology & Learning, 2008

2008-01-01

In this article, four directors discuss the security challenges that keep them worried and what they do about it. Dwayne Alton describes how his school district, IT School District of Lee County, Fort Meyers, Florida, collaborated with Cisco and installed an intrusion detection system which alerts IT staff when someone creates their own access…

An Experimental Exploration of the Impact of Sensor-Level Packet Loss on Network Intrusion Detection

DTIC Science & Technology

2015-07-01

Our observation of the graph reveals that this is most likely a nonlinear relationship resembling a sigmoid function (see Fig. 10). Spiess and...2014. 16. Usleep - sleep some number of microseconds. In: Chapter 3 of the Linux Pro- grammerś Manual; Raleigh (NC): Red Hat, Inc.; 2014. 17. Spiess

Rapid dike intrusion into Sakurajima volcano on August 15, 2015, as detected by multi-parameter ground deformation observations

NASA Astrophysics Data System (ADS)

Hotta, Kohei; Iguchi, Masato; Tameguri, Takeshi

2016-04-01

We present observations of ground deformation at Sakurajima in August 2015 and model the deformation using a combination of GNSS, tilt and strain data in order to interpret a rapid deformation event on August 15, 2015. The pattern of horizontal displacement during the period from August 14 to 16, 2015, shows a WNW-ESE extension, which suggests the opening of a dike. Using a genetic algorithm, we obtained the position, dip, strike length, width and opening of a dislocation source based on the combined data. A nearly vertical dike with a NNE-SSW strike was found at a depth of 1.0 km below sea level beneath the Showa crater. The length and width are 2.3 and 0.6 km, respectively, and a dike opening of 1.97 m yields a volume increase of 2.7 × 106 m3. 887 volcano-tectonic (VT) earthquakes beside the dike suggest that the rapid opening of the dike caused an accumulation of strain in the surrounding rocks, and the VT earthquakes were generated to release this strain. Half of the total amount of deformation was concentrated between 10:27 and 11:54 on August 15. It is estimated that the magma intrusion rate was 1 × 106 m3/h during this period. This is 200 times larger than the magma intrusion rate prior to one of the biggest eruptions at the summit crater of Minami-dake on July 24, 2012, and 2200 times larger than the average magma intrusion rate during the period from October 2011 to March 2012. The previous Mogi-type ground deformation is considered to be a process of magma accumulation in preexisting spherical reservoirs. Conversely, the August 2015 event was a dike intrusion and occurred in a different location to the preexisting reservoirs. The direction of the opening of the dike coincides with the T-axes and direction of faults creating a graben structure.

Model selection for anomaly detection

NASA Astrophysics Data System (ADS)

Burnaev, E.; Erofeev, P.; Smolyakov, D.

2015-12-01

Anomaly detection based on one-class classification algorithms is broadly used in many applied domains like image processing (e.g. detection of whether a patient is "cancerous" or "healthy" from mammography image), network intrusion detection, etc. Performance of an anomaly detection algorithm crucially depends on a kernel, used to measure similarity in a feature space. The standard approaches (e.g. cross-validation) for kernel selection, used in two-class classification problems, can not be used directly due to the specific nature of a data (absence of a second, abnormal, class data). In this paper we generalize several kernel selection methods from binary-class case to the case of one-class classification and perform extensive comparison of these approaches using both synthetic and real-world data.

Layered intrusions of the Duluth Complex, Minnesota, USA

USGS Publications Warehouse

Miller, J.D.; Ripley, E.M.; ,

1996-01-01

The Duluth Complex and associated subvolcanic intrusions comprise a large (5000 km2) intrusive complex in northeastern Minnesota that was emplaced into comagmatic volcanics during the development of the 1.1 Ga Midcontinent rift in North America. In addition to anorthositic and felsic intrusions, the Duluth Complex is composed of many individual mafic layered intrusions of tholeiitic affinity. The cumulate stratigraphies and cryptic variations of six of the better exposed and better studied intrusions are described here to demonstrate the variability in their cumulus mineral paragenesis.

Simultaneous lidar observations of the water vapor and ozone signatures of a stratospheric intrusion during the MOHAVE-2009 campaign

NASA Astrophysics Data System (ADS)

Leblanc, T.; McDermid, I. S.; Pérot, K.

2010-12-01

Ozone and water vapor signatures of a stratospheric intrusion were simultaneously observed by the Jet Propulsion Laboratory lidars located at Table Mountain Facility, California (TMF, 34.4N, 117.7W) during the Measurements of Humidity in the Atmosphere and Validation Experiments (MOHAVE-2009) campaign in October 2009. These observations are placed in the context of the meridional displacement and folding of the tropopause, and resulting contrast in the properties of the air masses sampled by lidar. The lidar observations are supported by model data, specifically potential vorticity fields advected by the high-resolution transport model MIMOSA, and by 10-day backward isentropic trajectories. The ozone and water vapor anomalies measured by lidar were largely anti-correlated, and consistent with the assumption of a wet and ozone-poor subtropical upper troposphere, and a dry and ozone-rich extra-tropical lowermost stratosphere. However, it is shown that this anti-correlation relation collapsed just after the stratospheric intrusion event of October 20, suggesting mixed air embedded along the subtropical jet stream and sampled by lidar during its displacement south of TMF (tropopause fold). The ozone-PV expected positive correlation relation held strongly throughout the measurement period, including when a lower polar stratospheric filament passed over TMF just after the stratospheric intrusion. The numerous highly-correlated signatures observed during this event demonstrate the strong capability of the water vapor and ozone lidars at TMF, and provide new confidence in the future detection by lidar of long-term variability of water vapor and ozone in the Upper Troposphere-Lower Stratosphere (UTLS).

Why seawater intrusion has not yet occurred in the Kaluvelli-Pondicherry basin, Tamil Nadu, India

NASA Astrophysics Data System (ADS)

Vincent, Aude; Violette, Sophie

2017-09-01

Worldwide, coastal aquifers are threatened by seawater intrusion. The threat is greatest when aquifers are overexploited or when recharge is low due to a semi-arid or arid climate. The Kaluvelli-Pondicherry sedimentary basin in Tamil Nadu (India) presents both these characteristics. Groundwater levels in the Vanur aquifer can reach 50 m below sea level at less than 20 km inland. This groundwater depletion is due to an exponential increase in extraction for irrigation over 35 years. No seawater intrusion has yet been detected, but a sulphate-rich mineralization is observed, the result of upward vertical leakage from the underlying Ramanathapuram aquifer. To characterize the mechanisms involved, and to facilitate effective water management, hydrogeological numerical modelling of this multi-layered system has been conducted. Existing and acquired geological and hydrodynamic data have been applied to a quasi-3D hydrogeological model, NEWSAM. Recharge had been previously quantified through the inter-comparison of hydrological models, based on climatological and surface-flow field measurements. Sensitivity tests on parameters and boundary conditions associated with the sea were performed. The resulting water balances for each aquifer led to hypotheses of (1) an offshore fresh groundwater stock, and (2) a reversal and increase of the upward leakage from the Ramanathapuram aquifer, thus corroborating the hypothesis proposed to explain geochemical results of the previous study, and denying a seawater intrusion. Palaeo-climate review supports the existence of favourable hydro-climatological conditions to replenish an offshore groundwater stock of the Vanur aquifer in the past. The extent of this fresh groundwater stock was calculated using the Kooi and Groen method.

[An Extraction and Recognition Method of the Distributed Optical Fiber Vibration Signal Based on EMD-AWPP and HOSA-SVM Algorithm].

PubMed

Zhang, Yanjun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong

2016-02-01

Given that the traditional signal processing methods can not effectively distinguish the different vibration intrusion signal, a feature extraction and recognition method of the vibration information is proposed based on EMD-AWPP and HOSA-SVM, using for high precision signal recognition of distributed fiber optic intrusion detection system. When dealing with different types of vibration, the method firstly utilizes the adaptive wavelet processing algorithm based on empirical mode decomposition effect to reduce the abnormal value influence of sensing signal and improve the accuracy of signal feature extraction. Not only the low frequency part of the signal is decomposed, but also the high frequency part the details of the signal disposed better by time-frequency localization process. Secondly, it uses the bispectrum and bicoherence spectrum to accurately extract the feature vector which contains different types of intrusion vibration. Finally, based on the BPNN reference model, the recognition parameters of SVM after the implementation of the particle swarm optimization can distinguish signals of different intrusion vibration, which endows the identification model stronger adaptive and self-learning ability. It overcomes the shortcomings, such as easy to fall into local optimum. The simulation experiment results showed that this new method can effectively extract the feature vector of sensing information, eliminate the influence of random noise and reduce the effects of outliers for different types of invasion source. The predicted category identifies with the output category and the accurate rate of vibration identification can reach above 95%. So it is better than BPNN recognition algorithm and improves the accuracy of the information analysis effectively.

Reducing depressive intrusions via a computerized cognitive bias modification of appraisals task: developing a cognitive vaccine.

PubMed

Lang, Tamara J; Moulds, Michelle L; Holmes, Emily A

2009-02-01

A feature of depression is the distressing experience of intrusive, negative memories. The maladaptive appraisals of such intrusions have been associated with symptom persistence. This study aimed to experimentally manipulate appraisals about depressive intrusions via a novel computerized cognitive bias modification (CBM) of appraisals paradigm, and to test the impact on depressive intrusion frequency for a standardized event (a depressive film). Forty-eight participants were randomly assigned to either a session of positive or negative CBM. Participants then watched a depressing film (including scenes of bereavement and bullying) and subsequently monitored the occurrence of depressive intrusions related to the film in a diary for one week. At one-week follow-up, participants completed additional measures of intrusions--the Impact of Event Scale (IES) and an intrusion provocation task. As predicted, compared to the negative condition, participants who underwent positive CBM showed a more positive appraisal bias. Further, one week later, positive CBM participants reported fewer intrusions of the film and had lower IES scores. Our findings demonstrate that it is possible to manipulate maladaptive appraisals about depressive intrusions via a computerized CBM task. Further, this effect transfers to reducing intrusive symptomatology related to a standardized event (a depressive film) over one week, suggesting novel clinical implications.

A Four–Component Model of Age–Related Memory Change

PubMed Central

Healey, M. Karl; Kahana, Michael J.

2015-01-01

We develop a novel, computationally explicit, theory of age–related memory change within the framework of the context maintenance and retrieval (CMR2) model of memory search. We introduce a set of benchmark findings from the free recall and recognition tasks that includes aspects of memory performance that show both age-related stability and decline. We test aging theories by lesioning the corresponding mechanisms in a model fit to younger adult free recall data. When effects are considered in isolation, many theories provide an adequate account, but when all effects are considered simultaneously, the existing theories fail. We develop a novel theory by fitting the full model (i.e., allowing all parameters to vary) to individual participants and comparing the distributions of parameter values for older and younger adults. This theory implicates four components: 1) the ability to sustain attention across an encoding episode, 2) the ability to retrieve contextual representations for use as retrieval cues, 3) the ability to monitor retrievals and reject intrusions, and 4) the level of noise in retrieval competitions. We extend CMR2 to simulate a recognition memory task using the same mechanisms the free recall model uses to reject intrusions. Without fitting any additional parameters, the four–component theory that accounts for age differences in free recall predicts the magnitude of age differences in recognition memory accuracy. Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. Thus we provide a four–component theory of a complex pattern of age differences across two key laboratory tasks. PMID:26501233

Kinetic processes for plastic deformation of olivine in the Poyi ultramafic intrusion, NW China: Insights from the textural analysis of a 1700 m fully cored succession

NASA Astrophysics Data System (ADS)

Yao, Zhuo-sen; Qin, Ke-zhang; Xue, Sheng-chao

2017-07-01

The ubiquitous presence of undulose extinction and subgrain boundaries in olivine crystals is commonly perceived as originating in the mantle, however these plastic deformation features are also well developed in the Poyi ultramafic intrusion, NW China. In this case, olivine was deformed through kinetic processes in a crustal magma chamber, rather than by deformation processes in the upper mantle. Moreover, accumulation and textural coarsening were critical to the characteristics of crystal size distributions (CSDs) of olivines in the Poyi intrusion. The axial deformational compaction of crystal mush was revealed by virtue of other quantitative textural analyses (e.g., spatial distribution patter, alignment factor and aspect ratio). Additionally, based on the contrast of density between crystal matrix and interstitial melt, adequate stress was generated by the km-scale crystal framework in Poyi body ( 2-11 MPa) which triggered the distortion of grain-lattice in olivine. The deformation mechanisms of olivine primarily are dislocation creep and dislocation-accommodated grain boundary sliding (DisGBS), while diffusion creep is subsidiary. This study has revealed various kinetic processes in a magmatic system by first demonstrating the genetic relationship between mineral deformation and axial compaction of crystal mush while highlighting the uncertainty of employing the deformation features of olivine in peridotite xenoliths as an indicator for a mantle origin. In contrast to the olivine populations of xenocrysts that underwent fragmentation during ascent, the deformed primitive olivines in compaction exhibit a distinct shortage of small grains, which is conducive to delimiting these two types of deformed grains.

Appraisal and control of sexual and non-sexual intrusive thoughts in university students.

PubMed

Clark, D A; Purdon, C; Byers, E S

2000-05-01

This study examined differences in the appraisal and thought control strategies associated with the perceived control of unwanted sexual and non-sexual intrusive thoughts. Eleven appraisal dimensions, subjective physiological arousal and 10 thought control strategies were measured in 171 university students who were administered the Revised Obsessive Intrusions Inventory-Sex Version, a self-report measure of unwanted intrusive thoughts. Thought-action fusion (TAF) likelihood was a significant unique predictor of the perceived controllability of respondents' most upsetting sexual and non-sexual intrusive thought. Moreover greater subjective physiological arousal was a significant predictor of reduced control over sexual intrusions, whereas worry that one might act on an intrusive thought and greater effort to control the intrusion were significant unique predictors of the control of non-sexual intrusive thoughts. Various thought control strategies were more often used in response to non-sexual than sexual cognitions. The results are discussed in terms of the differential role of various appraisal processes in the control of unwanted sexual and non-sexual thoughts.

Time, space, and composition relations among northern Nevada intrusive rocks and their metallogenic implications

USGS Publications Warehouse

duBray, E.A.

2007-01-01

Importantly, modal composition, age, and geochemical characteristics of intrusions associated with large mineral deposits along the trends, are indistinguishable from non-mineralized intrusions in northern Nevada and thus do not identify intrusions associated with significant deposits. Moreover, intrusion age and composition show little correlation with mineral-deposit type, abundance, and size. Given the lack of diagnostic characteristics for intrusions associated with deposits, it is uncertain whether age, modal composition, and geochemical data can identify intrusions associated with mineral deposits. These findings suggest that associations between northern Nevada intrusions and mineral deposits reflect superimposition of many geologic factors, none of which was solely responsible for mineral-deposit formation. These factors might include intrusion size, efficiency of fluid and metal extraction from magma, prevailing redox and sulfidation conditions, or derivation of metals and ligands from host rocks and groundwater. The abundance and diversity of mineral deposits in northern Nevada may partly reflect geochemical inheritance, for example, along the mineral trends rather than the influence of petrologically unique magma or associated fluids.

Petrogenesis of the Ni-Cu-PGE sulfide-bearing Tamarack Intrusive Complex, Midcontinent Rift System, Minnesota

NASA Astrophysics Data System (ADS)

Taranovic, Valentina; Ripley, Edward M.; Li, Chusi; Rossell, Dean

2015-01-01

The Tamarack Intrusive Complex (TIC, 1105.6 ± 1.2 Ma) in NE Minnesota, was emplaced during the early stages of the development of the Midcontinent Rift System (MRS, "Early Stage": 1110-1106 Ma). Country rocks of the TIC are those of the Paleoproterozoic Thomson Formation, part of the Animikie Group including sulfide-bearing metasedimentary black shale. The magmatic system is composed of at least two principal mafic-ultramafic intrusive sequences: the sulfide-barren Bowl Intrusion in the south and the "dike" area intrusions in the north which host Ni-Cu-Platinum Group Elements (PGE) mineralization with up to 2.33% Ni, 1.24% Cu, 0.34 g/t Pt, 0.23 g/t Pd and 0.18 g/t Au. Two distinct intrusive units in the "dike" area are the CGO (coarse-grained olivine-bearing) Intrusion, a sub-vertical dike-like body, and the overlying sub-horizontal FGO (fine-grained olivine-bearing) Intrusion. Both intrusions comprise peridotite, feldspathic peridotite, feldspathic pyroxenite, melatroctolite and melagabbro. Massive sulfides are volumetrically minor and mainly occur as lenses emplaced into the country rocks associated with both intrusions. Semi-massive (net-textured) sulfides are distributed at the core of the CGO Intrusion, surrounded by a halo of the disseminated sulfides. Disseminated sulfides also occur in lenses along the base of the FGO Intrusion. Olivine compositions in the CGO Intrusion are between Fo89 and Fo82 and in the FGO Intrusion from Fo84 to Fo82. TIC intrusions have more primitive olivine compositions than that of olivine in the sheet-like intrusions in the Duluth Complex (below Fo70), as well as olivine from the smaller, conduit-related, Eagle and East Eagle Intrusions in Northern Michigan (Fo86 to Fo75). The FeO/MgO ratios of the CGO and FGO Intrusion parental magmas, inferred from olivine compositions, are similar to those of picritic basalts erupted during the early stages of the MRS formation. Trace element ratios differ slightly from other intrusions in the MRS, and are indicative of significant crustal contamination. Differences in textures, whole-rock and mineral compositions, and sulfide distribution are consistent with the emplacement of at least two distinct sulfide saturated magmatic pulses. Ni-enrichment in the TIC indicates that sulfide saturation was attained prior to the sequestration of major proportions of Ni by olivine, possibly at a deeper chamber in the magmatic system. The addition of crustal S from the Thomson Formation sulfidic country rocks is thought to have been the principal process which drove the early attainment of sulfide saturation in the magmas. The CGO Intrusion carried the greater abundance of sulfide liquid, but both the CGO and FGO intrusive sequences represent the accumulation of dense silicate minerals and sulfide liquid in a conduit system. The genetic processes that were operative in the formation of Ni-Cu-PGE mineralization in the Tamarack Intrusive Complex appear to be typical of conduit-style magmatic sulfide deposits associated with large continental basaltic provinces.

Stuck in the spin cycle: Avoidance and intrusions following breast cancer diagnosis.

PubMed

Bauer, Margaret R; Wiley, Joshua F; Weihs, Karen L; Stanton, Annette L

2017-09-01

Theories and research regarding cognitive and emotional processing during the experience of profound stressors suggest that the presence of intrusive thoughts and feelings predicts greater use of avoidance and that the use of avoidance paradoxically predicts more intrusions. However, empirical investigations of their purported bidirectional relationship are limited. This study presents a longitudinal investigation of the reciprocal relationship between intrusions and avoidance coping over a 6-month period in the year following breast cancer diagnosis. Breast cancer patients (N = 460) completed measures of cancer-related intrusions and avoidance at study entry, 3 months, and 6 months later (i.e., an average of 2, 5, and 8 months after diagnosis, respectively). Cross-lagged panel analyses revealed that intrusive thoughts, feelings, and images at study entry predicted greater avoidance 3 months later, and avoidance coping at study entry predicted intrusions 3 months later, controlling for the stability of intrusions and avoidance as well as time since diagnosis. Findings were not statistically significant for avoidance predicting intrusions, or vice versa, between the 3-month and the 6-month assessment period, during which they declined. These findings provide empirical support for the theoretical contention that avoidance and intrusive thoughts and emotions reciprocally influence one another following stressful events. Additionally, in the months shortly after breast cancer diagnosis, intrusions and avoidance are positively related. However, the relationships attenuate over time, which could indicate resolved cognitive and emotional processing of the cancer experience. Statement of contribution What is already known on this subject? Following stressful life events, individuals often experience intrusive thoughts and feelings related to the event and they report avoidance of such reminders. Many studies demonstrate that greater intrusions predict more subsequent use of avoidance coping, and other studies show that greater use of avoidance predicts more intrusions. Their reciprocal relation has not been examined, however. What does this study add? This is the first examination of the concurrent, reciprocal influence of intrusions and avoidance. Findings suggest that accounting for the bidirectional influence of avoidance and intrusions best estimates hypothesized models. Higher intrusions and avoidance predicted each other for the first 3 months after study entry, but the relationship diminished 6 months after study entry, perhaps due to productive mental processing of the stress of breast cancer diagnosis and treatment. © 2017 The British Psychological Society.

[Analysis of intrusion errors in free recall].

PubMed

Diesfeldt, H F A

2017-06-01

Extra-list intrusion errors during five trials of the eight-word list-learning task of the Amsterdam Dementia Screening Test (ADST) were investigated in 823 consecutive psychogeriatric patients (87.1% suffering from major neurocognitive disorder). Almost half of the participants (45.9%) produced one or more intrusion errors on the verbal recall test. Correct responses were lower when subjects made intrusion errors, but learning slopes did not differ between subjects who committed intrusion errors and those who did not so. Bivariate regression analyses revealed that participants who committed intrusion errors were more deficient on measures of eight-word recognition memory, delayed visual recognition and tests of executive control (the Behavioral Dyscontrol Scale and the ADST-Graphical Sequences as measures of response inhibition). Using hierarchical multiple regression, only free recall and delayed visual recognition retained an independent effect in the association with intrusion errors, such that deficient scores on tests of episodic memory were sufficient to explain the occurrence of intrusion errors. Measures of inhibitory control did not add significantly to the explanation of intrusion errors in free recall, which makes insufficient strength of memory traces rather than a primary deficit in inhibition the preferred account for intrusion errors in free recall.

An energy ratio feature extraction method for optical fiber vibration signal

NASA Astrophysics Data System (ADS)

Sheng, Zhiyong; Zhang, Xinyan; Wang, Yanping; Hou, Weiming; Yang, Dan

2018-03-01

The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.

Integrated Remote Sensing Modalities for Classification at a Legacy Test Site

NASA Astrophysics Data System (ADS)

Lee, D. J.; Anderson, D.; Craven, J.

2016-12-01

Detecting, locating, and characterizing suspected underground nuclear test sites is of interest to the worldwide nonproliferation monitoring community. Remote sensing provides both cultural and surface geological information over a large search area in a non-intrusive manner. We have characterized a legacy nuclear test site at the Nevada National Security Site (NNSS) using an aerial system based on RGB imagery, light detection and ranging, and hyperspectral imaging. We integrate these different remote sensing modalities to perform pattern recognition and classification tasks on the test site. These tasks include detecting cultural artifacts and exotic materials. We evaluate if the integration of different remote sensing modalities improves classification performance.

Statistical Model Applied to NetFlow for Network Intrusion Detection

NASA Astrophysics Data System (ADS)

Proto, André; Alexandre, Leandro A.; Batista, Maira L.; Oliveira, Isabela L.; Cansian, Adriano M.

The computers and network services became presence guaranteed in several places. These characteristics resulted in the growth of illicit events and therefore the computers and networks security has become an essential point in any computing environment. Many methodologies were created to identify these events; however, with increasing of users and services on the Internet, many difficulties are found in trying to monitor a large network environment. This paper proposes a methodology for events detection in large-scale networks. The proposal approaches the anomaly detection using the NetFlow protocol, statistical methods and monitoring the environment in a best time for the application.

Stratigraphic framework of upper Paleozoic rocks, southeastern Sangre de Cristo Mountains, New Mexico

USGS Publications Warehouse

Baltz, E.H.; Myers, D.A.

1999-01-01

The Sangre de Cristo Mountains of south-central Colorado and north-central New Mexico are the physiographic expression of a southerly trending Cenozoic structural uplift that plunges gently south to die out in the Great Plains south of Santa Fe and Las Vegas, New Mexico. The uplift is bounded on the west by Neogene downfaulted and downwarped basins of the Rio Grande depression and, on the east, by broad Laramide basins that have sharply folded western limbs. The uplift was modified in Neogene time by local igneous-intrusive doming and normal faulting related to the Rio Grande rift.

Sensitivity analysis of some critical factors affecting simulated intrusion volumes during a low pressure transient event in a full-scale water distribution system.

PubMed

Ebacher, G; Besner, M C; Clément, B; Prévost, M

2012-09-01

Intrusion events caused by transient low pressures may result in the contamination of a water distribution system (DS). This work aims at estimating the range of potential intrusion volumes that could result from a real downsurge event caused by a momentary pump shutdown. A model calibrated with transient low pressure recordings was used to simulate total intrusion volumes through leakage orifices and submerged air vacuum valves (AVVs). Four critical factors influencing intrusion volumes were varied: the external head of (untreated) water on leakage orifices, the external head of (untreated) water on submerged air vacuum valves, the leakage rate, and the diameter of AVVs' outlet orifice (represented by a multiplicative factor). Leakage orifices' head and AVVs' orifice head levels were assessed through fieldwork. Two sets of runs were generated as part of two statistically designed experiments. A first set of 81 runs was based on a complete factorial design in which each factor was varied over 3 levels. A second set of 40 runs was based on a latin hypercube design, better suited for experimental runs on a computer model. The simulations were conducted using commercially available transient analysis software. Responses, measured by total intrusion volumes, ranged from 10 to 366 L. A second degree polynomial was used to analyze the total intrusion volumes. Sensitivity analyses of both designs revealed that the relationship between the total intrusion volume and the four contributing factors is not monotonic, with the AVVs' orifice head being the most influential factor. When intrusion through both pathways occurs concurrently, interactions between the intrusion flows through leakage orifices and submerged AVVs influence intrusion volumes. When only intrusion through leakage orifices is considered, the total intrusion volume is more largely influenced by the leakage rate than by the leakage orifices' head. The latter mainly impacts the extent of the area affected by intrusion. Copyright © 2012 Elsevier Ltd. All rights reserved.

X-Ray Backscatter Imaging for Aerospace Applications

NASA Astrophysics Data System (ADS)

Shedlock, Daniel; Edwards, Talion; Toh, Chin

2011-06-01

Scatter x-ray imaging (SXI) is a real time, digital, x-ray backscatter imaging technique that allows radiographs to be taken from one side of an object. This x-ray backscatter imaging technique offers many advantages over conventional transmission radiography that include single-sided access and extremely low radiation fields compared to conventional open source industrial radiography. Examples of some applications include the detection of corrosion, foreign object debris, water intrusion, cracking, impact damage and leak detection in a variety of material such as aluminum, composites, honeycomb structures, and titanium.

Intrusion of Magmatic Bodies Into the Continental Crust: 3-D Numerical Models

NASA Astrophysics Data System (ADS)

Gorczyk, Weronika; Vogt, Katharina

2018-03-01

Magma intrusion is a major material transfer process in the Earth's continental crust. Yet the mechanical behavior of the intruding magma and its host are a matter of debate. In this study we present a series of numerical thermomechanical simulations on magma emplacement in 3-D. Our results demonstrate the response of the continental crust to magma intrusion. We observe change in intrusion geometries between dikes, cone sheets, sills, plutons, ponds, funnels, finger-shaped and stock-like intrusions, and injection time. The rheology and temperature of the host are the main controlling factors in the transition between these different modes of intrusion. Viscous deformation in the warm and deep crust favors host rock displacement and plutons at the crust-mantle boundary forming deep-seated plutons or magma ponds in the lower to middle crust. Brittle deformation in the cool and shallow crust induces cone-shaped fractures in the host rock and enables emplacement of finger- or stock-like intrusions at shallow or intermediate depth. Here the passage of magmatic and hydrothermal fluids from the intrusion through the fracture pattern may result in the formation of ore deposits. A combination of viscous and brittle deformation forms funnel-shaped intrusions in the middle crust. Intrusion of low-density magma may more over result in T-shaped intrusions in cross section with magma sheets at the surface.

Swept shock/boundary-layer interactions: Scaling laws, flowfield structure, and experimental methods

NASA Technical Reports Server (NTRS)

Settles, Gary S.

1993-01-01

A general review is given of several decades of research on the scaling laws and flowfield structures of swept shock wave/turbulent boundary layer interactions. Attention is further restricted to the experimental study and physical understanding of the steady-state aspects of these flows. The interaction produced by a sharp, upright fin mounted on a flat plate is taken as an archetype. An overall framework of quasiconical symmetry describing such interactions is first developed. Boundary-layer separation, the interaction footprint, Mach number scaling, and Reynolds number scaling are then considered, followed by a discussion of the quasiconical similarity of interactions produced by geometrically-dissimilar shock generators. The detailed structure of these interaction flowfields is next reviewed, and is illustrated by both qualitative visualizations and quantitative flow images in the quasiconical framework. Finally, the experimental techniques used to investigate such flows are reviewed, with emphasis on modern non-intrusive optical flow diagnostics.

Phobias of attachment-related inner states in the psychotherapy of adult survivors of childhood complex trauma.

PubMed

Liotti, Giovanni

2013-11-01

The clinical case described in this article illustrates the value of taking into account the dynamics of disorganized attachment in the assessment of attachment-related phobias (phobia of attachment and phobia of attachment loss) during the psychotherapy of chronically traumatized patients. These seemingly opposite phobias typically coexist in the same patient, appear as phobias of both inner states (affect phobias) and relational experiences, and are linked to dissociated representations of self-with-other. Theory and research on attachment disorganization provide a clinician-friendly conceptual framework for capturing both the intrapsychic (e.g., intrusive and nonintegrated mental states) and the relational (e.g., dramatic unsolvable dilemmas in interpersonal exchanges) aspects of the attachment-related phobias. The therapeutic strategy and the key interventions that logically follow from a case formulation based on this conceptual framework are examined. © 2013 Wiley Periodicals, Inc.

Evaluation of Hanford Single-Shell Waste Tanks Suspected of Water Intrusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feero, Amie J.; Washenfelder, Dennis J.; Johnson, Jeremy M.

2013-11-14

Intrusions evaluations for twelve single-shell tanks were completed in 2013. The evaluations consisted of remote visual inspections, data analysis, and calculations of estimated intrusion rates. The observation of an intrusion or the preponderance of evidence confirmed that six of the twelve tanks evaluated had intrusions. These tanks were tanks 241-A-103, BX-101, BX-103, BX-110, BY-102, and SX-106.

Cup-shaped Intrusions, Morphology and Emplacement Mechanism Investigate Through Analogue Modelling

NASA Astrophysics Data System (ADS)

Mathieu, L.; van Wyk de Vries, B.

2007-12-01

We investigate the morphology of large-scale shallow-depth magma intrusions and sub-volcanic complexes with analogue models. Intrusions of analogue magma are done in a granular material that can contain a ductile layer. The model surface is flat to model the formation of plutonic intrusions and it is overlain by a cone when modelling late sub-volcanic complexes. For flat-top models, we obtain cup-shaped intrusions fed by dykes. Cup-shaped intrusions are inverted-cone like bodies. They are different from saucer-shaped intrusions as they possess neither a well developed sill-base, nor an outer rim. However, like saucers, cups are shallow depth intrusions that dome the country rocks. They initiate from an advancing dyke and first develop an inverted-cone like morphology. Then, the central thickness increases and thrusts form at the edge of the domed country rocks. At this stage, the intrusions progressively involve toward a lopolith shape. By using analogue magma of various viscosities we have been able to constrain key relationships: higher intrusion viscosity causes deeper initiation and the deeper they initiate, the larger is the intrusion diameter. A natural example of such intrusion might by the circles of volcanoes like the Azufre-Lastaria (Peru) that might be overlain be a large-scale cup-shaped intrusion. When adding a cone at the surface of the model and, sometimes, a thin ductile layer in the substratum, the morphology of cup-shaped intrusions vary. Note that the ductile layer of our models is not thick enough to induce the gravitational spreading of the cone. Generally, cup-shaped intrusions are asymmetric in cross section and elliptical in plan view. Their formation creates extension structures in the cone (croissant-shaped rift, straight rift or normal fault) and thrusts in some sectors below the cone. Both types of structures are bordered by strike-slip faults. Cups and saucers share many similarities, but differ probably in the fact that saucers are partially sills that are guided by stratigraphic horizons. However, the basic formation mechanisms may be the same and saucers could be regarded as a special form of cup.

Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System (PAIDS)

DTIC Science & Technology

2009-03-01

viii 3.2.3 Sub7 ...from TaskInfo in Excel Format. 3.2.3 Sub7 Also known as SubSeven, this is one of the best known, most widely distributed backdoor programs on the...engineering the spread of viruses, worms, backdoors and other malware. The Sub7 Trojan establishes a server on the victim computer that

2007 Beyond SBIR Phase II: Bringing Technology Edge to the Warfighter

DTIC Science & Technology

2007-08-23

Systems Trade-Off Analysis and Optimization Verification and Validation On-Board Diagnostics and Self - healing Security and Anti-Tampering Rapid...verification; Safety and reliability analysis of flight and mission critical systems On-Board Diagnostics and Self - Healing Model-based monitoring and... self - healing On-board diagnostics and self - healing ; Autonomic computing; Network intrusion detection and prevention Anti-Tampering and Trust