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.

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.

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

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

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.

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...

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.

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.

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.

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).

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.

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

Research on IPv6 intrusion detection system Snort-based

NASA Astrophysics Data System (ADS)

Shen, Zihao; Wang, Hui

2010-07-01

This paper introduces the common intrusion detection technologies, discusses the work flow of Snort intrusion detection system, and analyzes IPv6 data packet encapsulation and protocol decoding technology. We propose the expanding Snort architecture to support IPv6 intrusion detection in accordance with CIDF standard combined with protocol analysis technology and pattern matching technology, and present its composition. The research indicates that the expanding Snort system can effectively detect various intrusion attacks; it is high in detection efficiency and detection accuracy and reduces false alarm and omission report, which effectively solves the problem of IPv6 intrusion detection.

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

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 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.

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

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

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.

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.

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…

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.

Hybrid Intrusion Forecasting Framework for Early Warning System

NASA Astrophysics Data System (ADS)

Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

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.

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.

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.

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.

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.

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 ...

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...

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.

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.

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

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.

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.

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

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.

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.

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.

An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

PubMed Central

Butun, Ismail; Ra, In-Ho; Sankar, Ravi

2015-01-01

In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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...

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

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.

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

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

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...

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

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.

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

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

A survey of artificial immune system based intrusion detection.

PubMed

Yang, Hua; Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

2014-01-01

In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

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

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.

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.

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.

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.

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.

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.

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…

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.

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...

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.

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

[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.

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.

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

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.

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%.

Method for detecting moment connection fracture using high-frequency transients in recorded accelerations

USGS Publications Warehouse

Rodgers, J.E.; Elebi, M.

2011-01-01

The 1994 Northridge earthquake caused brittle fractures in steel moment frame building connections, despite causing little visible building damage in most cases. Future strong earthquakes are likely to cause similar damage to the many un-retrofitted pre-Northridge buildings in the western US and elsewhere. Without obvious permanent building deformation, costly intrusive inspections are currently the only way to determine if major fracture damage that compromises building safety has occurred. Building instrumentation has the potential to provide engineers and owners with timely information on fracture occurrence. Structural dynamics theory predicts and scale model experiments have demonstrated that sudden, large changes in structure properties caused by moment connection fractures will cause transient dynamic response. A method is proposed for detecting the building-wide level of connection fracture damage, based on observing high-frequency, fracture-induced transient dynamic responses in strong motion accelerograms. High-frequency transients are short (<1 s), sudden-onset waveforms with frequency content above 25 Hz that are visually apparent in recorded accelerations. Strong motion data and damage information from intrusive inspections collected from 24 sparsely instrumented buildings following the 1994 Northridge earthquake are used to evaluate the proposed method. The method's overall success rate for this data set is 67%, but this rate varies significantly with damage level. The method performs reasonably well in detecting significant fracture damage and in identifying cases with no damage, but fails in cases with few fractures. Combining the method with other damage indicators and removing records with excessive noise improves the ability to detect the level of damage. ?? 2010 Elsevier B.V. All rights reserved.

A Survey of Artificial Immune System Based Intrusion Detection

PubMed Central

Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

2014-01-01

In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted. PMID:24790549

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

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.

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.

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…

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

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

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

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.

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 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

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.

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.

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

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

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

Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

PubMed

Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

2017-01-01

Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

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

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

Multilayer Statistical Intrusion Detection in Wireless Networks

NASA Astrophysics Data System (ADS)

Hamdi, Mohamed; Meddeb-Makhlouf, Amel; Boudriga, Noureddine

2008-12-01

The rapid proliferation of mobile applications and services has introduced new vulnerabilities that do not exist in fixed wired networks. Traditional security mechanisms, such as access control and encryption, turn out to be inefficient in modern wireless networks. Given the shortcomings of the protection mechanisms, an important research focuses in intrusion detection systems (IDSs). This paper proposes a multilayer statistical intrusion detection framework for wireless networks. The architecture is adequate to wireless networks because the underlying detection models rely on radio parameters and traffic models. Accurate correlation between radio and traffic anomalies allows enhancing the efficiency of the IDS. A radio signal fingerprinting technique based on the maximal overlap discrete wavelet transform (MODWT) is developed. Moreover, a geometric clustering algorithm is presented. Depending on the characteristics of the fingerprinting technique, the clustering algorithm permits to control the false positive and false negative rates. Finally, simulation experiments have been carried out to validate the proposed IDS.

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

The effects of an anchovy (stolephorus insularis) substrate application on the level of fluor intrusion on Sprague Dawley rat teeth (in vivo)

NASA Astrophysics Data System (ADS)

Sakinah, N. R.; Gunawan, H. A.; Puspitawati, R.

2017-08-01

Fluoride intrusion is one of the efficacy parameters of fluoridation. Anchovy (Stolephorus insularis), which contains a high fluoride concentration in the CaF2compound, can be used as a fluoridative agent which is affordable and easily obtained. The aim of this study is to prove the effectiveness of the application of an anchovy substrate (Stolephorus insularis), either by a feeding method or a topical method, for tooth fluoridation based on the depth of fluoride intrusion on the enamel. An in vivo experimental laboratory method was used. The subjects were 14 Sprague Dawley rats divided into five groups. The groups included a baseline control, a feeding negative control, a topical negative control, an anchovy feeding method, and a topical solution anchovy method. After 15 days of treatment, the teeth were cut transversely with a 0.5 mm thickness then processed to test for fluoride intrusion using fluorescence microscopy. There was increased fluor intrusion on the enamel of the experimental groups compared to the negative control groups (p<0.05).Fluoride intrusion using the topical fluoride method is higher than with the feeding method (p <0.05). Thus, the application of an anchovy substrate, either by chewing or smearing, increases fluoride intrusion on the enamel.

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.

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

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET.

PubMed

N Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

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.

Method and apparatus for off-gas composition sensing

DOEpatents

Ottesen, David Keith; Allendorf, Sarah Williams; Hubbard, Gary Lee; Rosenberg, David Ezechiel

1999-01-01

An apparatus and method for non-intrusive collection of off-gas data in a steelmaking furnace includes structure and steps for transmitting a laser beam through the off-gas produced by a steelmaking furnace, for controlling the transmitting to repeatedly scan the laser beam through a plurality of wavelengths in its tuning range, and for detecting the laser beam transmitted through the off-gas and converting the detected laser beam to an electrical signal. The electrical signal is processed to determine characteristics of the off-gas that are used to analyze and/or control the steelmaking process.

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.

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.

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

A hybrid approach for efficient anomaly detection using metaheuristic methods

PubMed Central

Ghanem, Tamer F.; Elkilani, Wail S.; Abdul-kader, Hatem M.

2014-01-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms. PMID:26199752

A hybrid approach for efficient anomaly detection using metaheuristic methods.

PubMed

Ghanem, Tamer F; Elkilani, Wail S; Abdul-Kader, Hatem M

2015-07-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

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.

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET

PubMed Central

N. Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks. PMID:27285146

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

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.

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.

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.

Monitoring CO2 sequestration into deep saline aquifer and associated salt intrusion using coupled multiphase flow modeling and time-lapse electrical resistivity tomography

NASA Astrophysics Data System (ADS)

Lu, C.; Zhang, C.; Huang, H.; Johnson, T.

2012-12-01

Geological sequestration of carbon dioxide (CO2) into the subsurface has been considered as one solution to reduce greenhouse emission to the atmosphere. Successful sequestration process requires efficient and adequate monitoring of injected fluids as they migrate into the aquifer to evaluate flow path, leakage, and geochemical interactions between CO2 and geologic media. In this synthetic field scale study, we have integrated 3D multiphase flow modeling code PFLOTRAN with 3D time-laps electrical resistivity tomography (ERT) to gain insight into the supercritical (SC) CO2 plumes movement in the deep saline aquifer and associated brine intrusion into shallower fresh water aquifer. A parallel ERT forward and inverse modeling package was introduced, and related algorithms are briefly described. The capabilities and limitations of ERT in monitoring CO2 migration are assessed by comparing the results from PFLOTRAN simulations with the ERT inversion results. In general, our study shows the ERT inversion results compare well with PFLOTRAN with reasonable discrepancies, indicating that the ERT can capture the actual CO2 plume dynamics and brine intrusion. Detailed comparisons on the location, size and volume of CO2 plume show the ERT method underestimated area review and overestimated total plume volume in the predictions of SC CO2 movements. These comparisons also show the ERT method constantly overestimate salt intrusion area and underestimated total solute amount in the predictions of brine filtration. Our study shows that together with other geochemical and geophysical methods, ERT is a potentially useful monitoring tool in detecting the SC CO2 and formation fluid migrations.

Improving Control System Cyber-State Awareness using Known Secure Sensor Measurements

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

Ondrej Linda; Milos Manic; Miles McQueen

Abstract—This paper presents design and simulation of a low cost and low false alarm rate method for improved cyber-state awareness of critical control systems - the Known Secure Sensor Measurements (KSSM) method. The KSSM concept relies on physical measurements to detect malicious falsification of the control systems state. The KSSM method can be incrementally integrated with already installed control systems for enhanced resilience. This paper reviews the previously developed theoretical KSSM concept and then describes a simulation of the KSSM system. A simulated control system network is integrated with the KSSM components. The effectiveness of detection of various intrusion scenariosmore » is demonstrated on several control system network topologies.« 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

A Quantitative Experimental Study of the Effectiveness of Systems to Identify Network Attackers

ERIC Educational Resources Information Center

Handorf, C. Russell

2016-01-01

This study analyzed the meta-data collected from a honeypot that was run by the Federal Bureau of Investigation for a period of 5 years. This analysis compared the use of existing industry methods and tools, such as Intrusion Detection System alerts, network traffic flow and system log traffic, within the Open Source Security Information Manager…

Improved security monitoring method for network bordary

NASA Astrophysics Data System (ADS)

Gao, Liting; Wang, Lixia; Wang, Zhenyan; Qi, Aihua

2013-03-01

This paper proposes a network bordary security monitoring system based on PKI. The design uses multiple safe technologies, analysis deeply the association between network data flow and system log, it can detect the intrusion activities and position invasion source accurately in time. The experiment result shows that it can reduce the rate of false alarm or missing alarm of the security incident effectively.

Non-intrusive torque measurement for rotating shafts using optical sensing of zebra-tapes

NASA Astrophysics Data System (ADS)

Zappalá, D.; Bezziccheri, M.; Crabtree, C. J.; Paone, N.

2018-06-01

Non-intrusive, reliable and precise torque measurement is critical to dynamic performance monitoring, control and condition monitoring of rotating mechanical systems. This paper presents a novel, contactless torque measurement system consisting of two shaft-mounted zebra tapes and two optical sensors mounted on stationary rigid supports. Unlike conventional torque measurement methods, the proposed system does not require costly embedded sensors or shaft-mounted electronics. Moreover, its non-intrusive nature, adaptable design, simple installation and low cost make it suitable for a large variety of advanced engineering applications. Torque measurement is achieved by estimating the shaft twist angle through analysis of zebra tape pulse train time shifts. This paper presents and compares two signal processing methods for torque measurement: rising edge detection and cross-correlation. The performance of the proposed system has been proven experimentally under both static and variable conditions and both processing approaches show good agreement with reference measurements from an in-line, invasive torque transducer. Measurement uncertainty has been estimated according to the ISO GUM (Guide to the expression of uncertainty in measurement). Type A analysis of experimental data has provided an expanded uncertainty relative to the system full-scale torque of  ±0.30% and  ±0.86% for the rising edge and cross-correlation approaches, respectively. Statistical simulations performed by the Monte Carlo method have provided, in the worst case, an expanded uncertainty of  ±1.19%.

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.

Time-resolved broadband cavity-enhanced absorption spectroscopy for chemical kinetics.

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

Sheps, Leonid; Chandler, David W.

Experimental measurements of elementary reaction rate coefficients and product branching ratios are essential to our understanding of many fundamentally important processes in Combustion Chemistry. However, such measurements are often impossible because of a lack of adequate detection techniques. Some of the largest gaps in our knowledge concern some of the most important radical species, because their short lifetimes and low steady-state concentrations make them particularly difficult to detect. To address this challenge, we propose a novel general detection method for gas-phase chemical kinetics: time-resolved broadband cavity-enhanced absorption spectroscopy (TR-BB-CEAS). This all-optical, non-intrusive, multiplexed method enables sensitive direct probing of transientmore » reaction intermediates in a simple, inexpensive, and robust experimental package.« less

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.

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

Alternative Methods for Assessing Contaminant Transport from the Vadose Zone to Indoor Air

NASA Astrophysics Data System (ADS)

Baylor, K. J.; Lee, A.; Reddy, P.; Plate, M.

2010-12-01

Vapor intrusion, which is the transport of contaminant vapors from groundwater and the vadose zone to indoor air, has emerged as a significant human health risk near hazardous waste sites. Volatile organic compounds (VOCs) such as trichloroethylene (TCE) and tetrachloroethylene (PCE) can volatilize from groundwater and from residual sources in the vadose zone and enter homes and commercial buildings through cracks in the slab, plumbing conduits, or other preferential pathways. Assessment of the vapor intrusion pathway typically requires collection of groundwater, soil gas, and indoor air samples, a process which can be expensive and time-consuming. We evaluated three alternative vapor intrusion assessment methods, including 1) use of radon as a surrogate for vapor intrusion, 2) use of pressure differential measurements between indoor/outdoor and indoor/subslab to assess the potential for vapor intrusion, and 3) use of passive, longer-duration sorbent methods to measure indoor air VOC concentrations. The primary test site, located approximately 30 miles south of San Francisco, was selected due to the presence of TCE (10 - 300 ug/L) in shallow groundwater (5 to 10 feet bgs). At this test site, we found that radon was not a suitable surrogate to asses vapor intrusion and that pressure differential measurements are challenging to implement and equipment-intensive. More significantly, we found that the passive, longer-duration sorbent methods are easy to deploy and compared well quantitatively with standard indoor air sampling methods. The sorbent technique is less than half the cost of typical indoor air methods, and also provides a longer duration sample, typically 3 to 14 days rather than 8 to 24 hours for standard methods. The passive sorbent methods can be a reliable, cost-effective, and easy way to sample for TCE, PCE and other VOCs as part of a vapor intrusion investigation.

Mellin Transform-Based Correction Method for Linear Scale Inconsistency of Intrusion Events Identification in OFPS

NASA Astrophysics Data System (ADS)

Wang, Baocheng; Qu, Dandan; Tian, Qing; Pang, Liping

2018-05-01

For the problem that the linear scale of intrusion signals in the optical fiber pre-warning system (OFPS) is inconsistent, this paper presents a method to correct the scale. Firstly, the intrusion signals are intercepted, and an aggregate of the segments with equal length is obtained. Then, the Mellin transform (MT) is applied to convert them into the same scale. The spectral characteristics are obtained by the Fourier transform. Finally, we adopt back-propagation (BP) neural network to identify intrusion types, which takes the spectral characteristics as input. We carried out the field experiments and collected the optical fiber intrusion signals which contain the picking signal, shoveling signal, and running signal. The experimental results show that the proposed algorithm can effectively improve the recognition accuracy of the intrusion signals.

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

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.

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.

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 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.

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.

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.

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.

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.

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

Intrusion Prevention and Detection in Grid Computing - The ALICE Case

NASA Astrophysics Data System (ADS)

Gomez, Andres; Lara, Camilo; Kebschull, Udo

2015-12-01

Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machine Learning approach. We plan to implement the proposed framework as a software prototype that will be tested as a component of the ALICE Grid middleware.

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.

Architecture for an artificial immune system.

PubMed

Hofmeyr, S A; Forrest, S

2000-01-01

An artificial immune system (ARTIS) is described which incorporates many properties of natural immune systems, including diversity, distributed computation, error tolerance, dynamic learning and adaptation, and self-monitoring. ARTIS is a general framework for a distributed adaptive system and could, in principle, be applied to many domains. In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS. LISYS is described and shown to be effective at detecting intrusions, while maintaining low false positive rates. Finally, similarities and differences between ARTIS and Holland's classifier systems are discussed.

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.

Quality metrics for sensor images

NASA Technical Reports Server (NTRS)

Ahumada, AL

1993-01-01

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.

Study project of intrusive rocks: States of Espirito Santo and Rio de Janeiro, south and east of Minas Gerais and southeast of the state of Sao Paulo. [Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Dossantos, A. R.; DOSANJOS; Barbos, M. P.; Veneziani, P.

1981-01-01

The feasibility of mapping intrusive rocks in polycyclic and polymetamorphic areas using the logic method for photointerpretation of LANDSAT and radar imagery was investigated. The resolution, scale and spectral characteristics of the imagery were considered. Spectral characteristics of the intrusive rock units mapped using image 100 were investigated. It was determined that identification of acidic and basic intrusive bodies and determination of their relationships with principal structural directions using the logic method was feasible. Tectonic compartments were subdivided into units according to their predominant lithographic types, ignoring stratigraphy. The principal directions of various foliations, faults, megafolds, and fractural systems were defined. Delineation of the boundaries of intrusive bodies mapped using the spectral characteristics of Image 100 imagery ws determined to be more accurate than visual analysis. A 1:500,000 scale map of intrusions in the areas studied was generated.

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

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.

A hybrid method for protection against threats to a network infrastructure for an electronic warfare management system

NASA Astrophysics Data System (ADS)

Byłak, Michał; RóŻański, Grzegorz

2017-04-01

The article presents the concept of ensuring the security of network information infrastructure for the management of Electronic Warfare (EW) systems. The concept takes into account the reactive and proactive tools against threats. An overview of the methods used to support the safety of IT networks and information sources about threats is presented. Integration of mechanisms that allow for effective intrusion detection and rapid response to threats in a network has been proposed. The architecture of the research environment is also presented.

An efficient multi-objective optimization method for water quality sensor placement within water distribution systems considering contamination probability variations.

PubMed

He, Guilin; Zhang, Tuqiao; Zheng, Feifei; Zhang, Qingzhou

2018-06-20

Water quality security within water distribution systems (WDSs) has been an important issue due to their inherent vulnerability associated with contamination intrusion. This motivates intensive studies to identify optimal water quality sensor placement (WQSP) strategies, aimed to timely/effectively detect (un)intentional intrusion events. However, these available WQSP optimization methods have consistently presumed that each WDS node has an equal contamination probability. While being simple in implementation, this assumption may do not conform to the fact that the nodal contamination probability may be significantly regionally varied owing to variations in population density and user properties. Furthermore, the low computational efficiency is another important factor that has seriously hampered the practical applications of the currently available WQSP optimization approaches. To address these two issues, this paper proposes an efficient multi-objective WQSP optimization method to explicitly account for contamination probability variations. Four different contamination probability functions (CPFs) are proposed to represent the potential variations of nodal contamination probabilities within the WDS. Two real-world WDSs are used to demonstrate the utility of the proposed method. Results show that WQSP strategies can be significantly affected by the choice of the CPF. For example, when the proposed method is applied to the large case study with the CPF accounting for user properties, the event detection probabilities of the resultant solutions are approximately 65%, while these values are around 25% for the traditional approach, and such design solutions are achieved approximately 10,000 times faster than the traditional method. This paper provides an alternative method to identify optimal WQSP solutions for the WDS, and also builds knowledge regarding the impacts of different CPFs on sensor deployments. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

ASSESSMENT OF VAPOR INTRUSION USING INDOOR AND SUB-SLAB AIR SAMPLING

EPA Science Inventory

The objective of this investigation was to develop a method for evaluating vapor intrusion using indoor and sub-slab air measurement and at the same time directly assist EPA’s New England Regional Office in evaluating vapor intrusion in 15 homes and one business near the former R...

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.

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.

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.

10 CFR 963.16 - Postclosure suitability evaluation method.

Code of Federal Regulations, 2010 CFR

2010-01-01

... radionuclide concentrations in the case where there is no human intrusion into the repository. DOE will model... where there is a human intrusion as specified by 10 CFR 63.322. DOE will model the performance of the... criteria in § 963.17. If required by applicable NRC regulations regarding a human intrusion standard, § 63...

Method and apparatus for identification of hazards along an intended travel route

NASA Technical Reports Server (NTRS)

Kronfeld, Kevin M. (Inventor); Lapis, Mary Beth (Inventor); Walling, Karen L. (Inventor); Chackalackal, Mathew S. (Inventor)

2003-01-01

Targets proximate to a travel route plan were evaluated to determine hazardousness. Projected geometric representation of a vehicle determines intrusion of hazardous targets along travel route plan. Geometric representation of hazardous targets projected along motion vector to determine intrusion upon travel route plan. Intrusion assessment presented on user display.

Intrusive Thoughts and Young Children's Knowledge about Thinking following a Natural Disaster

ERIC Educational Resources Information Center

Sprung, Manuel; Harris, Paul L.

2010-01-01

Background: "Hurricane Katrina" devastated the Mississippi Gulf Coast in August 2005. Intrusive re-experiencing is a common posttraumatic stress symptom. However, young children with limited introspection skills might have difficulties identifying their intrusive thoughts. Method: A sample of 165 5- to 9-year-old children were surveyed about their…

Probabilistic monitoring in intrusion detection module for energy efficiency in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

De Rango, Floriano; Lupia, Andrea

2016-05-01

MANETs allow mobile nodes communicating to each other using the wireless medium. A key aspect of these kind of networks is the security, because their setup is done without an infrastructure, so external nodes could interfere in the communication. Mobile nodes could be compromised, misbehaving during the multi-hop transmission of data, or they could have a selfish behavior to save energy, which is another important constraint in MANETs. The detection of these behaviors need a framework that takes into account the latest interactions among nodes, so malicious or selfish nodes could be detected also if their behavior is changed over time. The monitoring activity increases the energy consumption, so our proposal takes into account this issue reducing the energy required by the monitoring system, keeping the effectiveness of the intrusion detection system. The results show an improvement in the saved energy, improving the detection performance too.

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.

Biosensors for termite control

NASA Astrophysics Data System (ADS)

Farkhanda, M.

2013-12-01

Termites are major urban pests in Pakistan and cause damage to wooden structures and buildings. Termite management has two parts: prevention and control. The most difficult part of termite control is termite detection as most of them are subterranean in Pakistan and have tunneling habit.Throughout the world, chemical termiticides are going to be replaced by baits, microwave and sensor technology. Termite species are distinct biologically and have specific foraging behaviors. Termite Detection Radar, Moisture meter and Remote Thermal Sensor with Laser are available throughout the world. These can detect termites underground and use fewer chemicals than traditional methods. For wooden buildings, a termite sensor and an intrusion detection system for detecting termites are designed. A pair of electrodes is disposed inside the container. A pair of terminals is connected to these electrodes, these extend outside the container. Termites are detected by a change of conductivity between the electrodes, when termites are detected a warning device generates a warning signal. In Pakistan, there is dire need to develop such biosensoring devices locally, then apply control methods that would save money and protect the environment.

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

Prospects for Evidence -Based Software Assurance: Models and Analysis

DTIC Science & Technology

2015-09-01

virtual machine is much lighter than the workstation. The virtual machine doesn’t need to run anti- virus , firewalls, intrusion preven- tion systems...34] Maiorca, D., Corona , I., and Giacinto, G. Looking at the bag is not enough to find the bomb: An evasion of structural methods for malicious PDF...CCS ’13, ACM, pp. 119–130. [35] Maiorca, D., Giacinto, G., and Corona , I. A pattern recognition system for malicious PDF files detection. In

Preliminary experiments on surface flow visualization in the cryogenic wind tunnel by use of condensing or freezing gases

NASA Technical Reports Server (NTRS)

Goodyer, M. J.

1988-01-01

Cryogenic wind tunnel users must have available surface flow visualization techniques to satisfy a variety of needs. While the ideal from an aerodynamic stand would be non-intrusive, until an economical technique is developed there will be occasions when the user will be prepared to resort to an intrusive method. One such method is proposed, followed by preliminary evaluation experiments carried out in environments representative of the cryogenic nitrogen tunnel. The technique uses substances which are gases at normal temperature and pressure but liquid or solid at cryogenic temperatures. These are deposited on the model in localized regions, the patterns of the deposits and their subsequent melting or evaporation revealing details of the surface flow. The gases were chosen because of the likelihood that they will not permanently contaminate the model or tunnel. Twenty-four gases were identified as possibly suitable and four of these were tested from which it was concluded that surface flow direction can be shown by the method. Other flow details might also be detectable. The cryogenic wind tunnel used was insulated on the outside and did not show signs of contamination.

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.

Feature Selection Using Information Gain for Improved Structural-Based Alert Correlation

PubMed Central

Siraj, Maheyzah Md; Zainal, Anazida; Elshoush, Huwaida Tagelsir; Elhaj, Fatin

2016-01-01

Grouping and clustering alerts for intrusion detection based on the similarity of features is referred to as structurally base alert correlation and can discover a list of attack steps. Previous researchers selected different features and data sources manually based on their knowledge and experience, which lead to the less accurate identification of attack steps and inconsistent performance of clustering accuracy. Furthermore, the existing alert correlation systems deal with a huge amount of data that contains null values, incomplete information, and irrelevant features causing the analysis of the alerts to be tedious, time-consuming and error-prone. Therefore, this paper focuses on selecting accurate and significant features of alerts that are appropriate to represent the attack steps, thus, enhancing the structural-based alert correlation model. A two-tier feature selection method is proposed to obtain the significant features. The first tier aims at ranking the subset of features based on high information gain entropy in decreasing order. The‏ second tier extends additional features with a better discriminative ability than the initially ranked features. Performance analysis results show the significance of the selected features in terms of the clustering accuracy using 2000 DARPA intrusion detection scenario-specific dataset. PMID:27893821

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.

A progress report on UNICOS misuse detection at Los Alamos

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

Thompson, J.L.; Jackson, K.A.; Stallings, C.A.

An effective method for detecting computer misuse is the automatic monitoring and analysis of on-line user activity. During the past year, Los Alamos enhanced its Network Anomaly Detection and Intrusion Reporter (NADIR) to include analysis of user activity on Los Alamos` UNICOS Crays. In near real-time, NADIR compares user activity to historical profiles and tests activity against expert rules. The expert rules express Los Alamos` security policy and define improper or suspicious behavior. NADIR reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations. This paper describes the implementation to date of the UNICOS component ofmore » NADIR, along with the operational experiences and future plans for the system.« less

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...

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.

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.

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.

Framework flexibility of ZIF-8 under liquid intrusion: discovering time-dependent mechanical response and structural relaxation.

PubMed

Sun, Yueting; Li, Yibing; Tan, Jin-Chong

2018-04-18

The structural flexibility of a topical zeolitic imidazolate framework with sodalite topology, termed ZIF-8, has been elucidated through liquid intrusion under moderate pressures (i.e. tens of MPa). By tracking the evolution of water intrusion pressure under cyclic conditions, we interrogate the role of the gate-opening mechanism controlling the size variation of the pore channels of ZIF-8. Interestingly, we demonstrate that its channel deformation is recoverable through structural relaxation over time, hence revealing the viscoelastic mechanical response in ZIF-8. We propose a simple approach employing a glycerol-water solution mixture, which can significantly enhance the sensitivity of intrusion pressure for the detection of structural deformation in ZIF-8. By leveraging the time-dependent gate-opening phenomenon in ZIF-8, we achieved a notable improvement (50%) in energy dissipation during multicycle mechanical deformation experiments.

Simple, Efficient, and Rapid Methods to Determine the Potential for Vapor Intrusion into the Home: Temporal Trends, Vapor Intrusion Forecasting, Sampling Strategies, and Contaminant Migration Routes

EPA Science Inventory

Current practice for evaluating the vapor intrusion pathway involves a multiple line of evidence approach based on direct measurements of volatile organic compound (VOC) concentrations in groundwater, external soil gas, subslab soil gas, and/or indoor air. No single line of evide...

Enforcing positivity in intrusive PC-UQ methods for reactive ODE systems

DOE PAGES

Najm, Habib N.; Valorani, Mauro

2014-04-12

We explore the relation between the development of a non-negligible probability of negative states and the instability of numerical integration of the intrusive Galerkin ordinary differential equation system describing uncertain chemical ignition. To prevent this instability without resorting to either multi-element local polynomial chaos (PC) methods or increasing the order of the PC representation in time, we propose a procedure aimed at modifying the amplitude of the PC modes to bring the probability of negative state values below a user-defined threshold. This modification can be effectively described as a filtering procedure of the spectral PC coefficients, which is applied on-the-flymore » during the numerical integration when the current value of the probability of negative states exceeds the prescribed threshold. We demonstrate the filtering procedure using a simple model of an ignition process in a batch reactor. This is carried out by comparing different observables and error measures as obtained by non-intrusive Monte Carlo and Gauss-quadrature integration and the filtered intrusive procedure. Lastly, the filtering procedure has been shown to effectively stabilize divergent intrusive solutions, and also to improve the accuracy of stable intrusive solutions which are close to the stability limits.« less

Geophysical characterization of saltwater intrusion in a coastal aquifer: The case of Martil-Alila plain (North Morocco)

NASA Astrophysics Data System (ADS)

Himi, Mahjoub; Tapias, Josefiina; Benabdelouahab, Sara; Salhi, Adil; Rivero, Luis; Elgettafi, Mohamed; El Mandour, Abdenabi; Stitou, Jamal; Casas, Albert

2017-02-01

Several factors can affect the quantity and the quality of groundwater resources, but in coastal aquifers seawater intrusion is often the most significant issue regarding freshwater supply. Further, saltwater intrusion is a worldwide issue because about seventy percent of the world's population lives in coastal regions. Generally, fresh groundwater not affected by saltwater intrusion is characterized by low salinity and therefore low electrical conductivity (EC) values. Consequently, high values of EC in groundwater along the coastline are usually associated to seawater intrusion. This effect is amplified if the coastal aquifer is overexploited with a subsequent gradual displacement of the freshwater-saltwater interface towards the continent. Delineation of marine intrusion in coastal aquifers has traditionally relied upon observation wells and collection of water samples. This approach may miss important hydrologic features related to saltwater intrusion in areas where access is difficult and where wells are widely spaced. Consequently, the scarcity of sampling points and sometimes their total absence makes the number of data available limited and most of the time not representative for mapping the spatial and temporal variability of groundwater salinity. In this study, we use a series of geophysical methods for characterizing the aquifer geometry and the extension of saltwater intrusion in the Martil-Alila coastal region (Morocco) as a complement to geological and hydrogeochemical data. For this reason, we carried out three geophysical surveys: Gravity, Electrical Resistivity and Frequency Domain Electromagnetic. The geometry of the basin has been determined from the interpretation of a detailed gravity survey. Electrical resistivity models derived from vertical electrical soundings allowed to characterize the vertical and the lateral extensions of aquifer formations. Finally, frequency domain electromagnetic methods allowed delineating the extension of the saltwater intrusion.

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.

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

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.

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.

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.

Sleep Deprivation Attack Detection in Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Bhattasali, Tapalina; Chaki, Rituparna; Sanyal, Sugata

2012-02-01

Deployment of sensor network in hostile environment makes it mainly vulnerable to battery drainage attacks because it is impossible to recharge or replace the battery power of sensor nodes. Among different types of security threats, low power sensor nodes are immensely affected by the attacks which cause random drainage of the energy level of sensors, leading to death of the nodes. The most dangerous type of attack in this category is sleep deprivation, where target of the intruder is to maximize the power consumption of sensor nodes, so that their lifetime is minimized. Most of the existing works on sleep deprivation attack detection involve a lot of overhead, leading to poor throughput. The need of the day is to design a model for detecting intrusions accurately in an energy efficient manner. This paper proposes a hierarchical framework based on distributed collaborative mechanism for detecting sleep deprivation torture in wireless sensor network efficiently. Proposed model uses anomaly detection technique in two steps to reduce the probability of false intrusion.

Volumetric Measurement of Root Resorption following Molar Mini-Screw Implant Intrusion Using Cone Beam Computed Tomography

PubMed Central

Li, Wen; Chen, Fei; Zhang, Feng; Ding, Wanghui; Ye, Qingsong; Shi, Jiejun; Fu, Baiping

2013-01-01

Objective Molar intrusion by mini-screw implantation can cause different degrees of root resorption. However, most methods (2-D and 3-D) used for evaluating root resorption have focused on the root length without considering 3-D resorption. The purpose of this study was to volumetrically evaluate root resorption using cone beam computed tomography(CBCT) after mini-screw implant intrusion. Materials and Methods 1. The volumes of 32 teeth were measured using CBCT and laser scanning to verify the accuracy of CBCT. 2. Twelve overerupted molars from adult patients were investigated in this study. After mini-screw implants were inserted into the buccal and palatal alveolar bones, 150 g of force was applied to the mini-screw implants on each side to intrude the molars. CBCT images of all patients were taken immediately prior to intrusion and after intrusion. The volumes of the roots were calculated using the Mimics software program. The differences between the pre-intrusion and post-intrusion root volumes were statistically evaluated with a paired-samples t-test. In addition, the losses of the roots were statistically compared with each other using one-way analysis of variance at the P<0.05 level. Results No statistically significant volume differences were observed between the physical (laser scanning) and CBCT measurements (P>0.05). The overerupted molars were significantly intruded (P<0.05), and the average intrusion was 3.30±1.60 mm. The differences between the pre-intrusion and post-intrusion root volumes were statistically significant for all of the roots investigated (P<0.05). The roots were sorted by volume loss in descending order as follows: mesiobuccal, palatal, and distobuccal. Statistical significance was achieved among the three roots. The average total resorption for each tooth was 58.39±1.54 mm3. Conclusion Volume measurement using CBCT was able to effectively evaluate root resorption caused by mini-screw intrusion. The highest volume loss was observed in the mesiobuccal root among the three roots of the investigated first molar teeth. PMID:23585866

A study on efficient detection of network-based IP spoofing DDoS and malware-infected Systems.

PubMed

Seo, Jung Woo; Lee, Sang Jin

2016-01-01

Large-scale network environments require effective detection and response methods against DDoS attacks. Depending on the advancement of IT infrastructure such as the server or network equipment, DDoS attack traffic arising from a few malware-infected systems capable of crippling the organization's internal network has become a significant threat. This study calculates the frequency of network-based packet attributes and analyzes the anomalies of the attributes in order to detect IP-spoofed DDoS attacks. Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. Detection accuracy and performance of the collected real-time traffic on a core network is analyzed thru the use of the proposed algorithm, and a prototype was developed to evaluate the performance of the algorithm. As a result, DDoS attacks on the internal network were detected in real-time and whether or not IP addresses were spoofed was confirmed. Detecting hosts infected by malware in real-time allowed the execution of intrusion responses before stoppage of the internal network caused by large-scale attack traffic.

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

Vapor Intrusion Assessment and Mitigation 2012

DTIC Science & Technology

2012-03-26

1 Geosyntec 0 consultants Vapor Intrusion Assessment and Mitigation 2012 Robert Ettinger, M.S., P.E., Todd McAiary, M.Sc., P.Eng., P.G...REPORT DATE 26 MAR 2012 2. REPORT TYPE 3. DATES COVERED 00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Vapor Intrusion Assessment and...Updates • Typical Assessment Approaches and Common Challenges • Methods to Distinguish Background Sources (McHugh) • Significance • Compound

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...

Occurrence and attempted mitigation of carbon dioxide in a home constructed on reclaimed coal-mine spoil, Pike County, Indiana

USGS Publications Warehouse

Robinson, Bret A.

2010-01-01

In recent years carbon dioxide intrusion has become recognized as a potentially serious health threat where homes are constructed on or near reclaimed surface coal mines. When carbon dioxide invades the living space of a home, it can collect near the floor, displace the oxygen there, and produce an oxygen-deficient environment. In this investigation, several lines of inquiry were pursued to determine the environmental factors that most influence carbon dioxide intrusion at a Pike County, Ind., home where this phenomenon is known to occur. It was found that carbon dioxide intrusion events at the home are most closely tied to rapid drops in barometric pressure and rainfall. Other researchers have shown that windy conditions and periods of cold weather also can contribute to soil-gas intrusion to structures. From this, a conceptual model was developed to illustrate the influence of these four meteorological conditions. Additionally, three mitigation methods-block-wall depressurization, block-wall and sub-slab depressurization, and block-wall and sub-slab pressurization-were applied successively to the study-site home, and environmental data were collected to evaluate the effectiveness of each mitigation method. In each case, it was found that these methods did not ensure a safe environment when meteorological conditions were favorable for carbon dioxide intrusion.

Ex-situ gas diffusion layer intrusion effect determination of polymer electrolyte membrane fuel cell flow fields

NASA Astrophysics Data System (ADS)

Haase, S.; Rauber, M.

2015-09-01

In automotive PEM fuel cell systems, one of the most important targets is to reduce the parasitic power of balance of plant components, e.g. the air supply. This can be achieved for example by decreasing air stoichiometry. However, this could lead to bad flow sharing in the fuel cell stack. Therefore the fluid distribution in the flow field has to be evaluated, understood and optimized. This work evaluates the effect of GDL intrusion on the pressure drop via ex-situ determination of GDL intrusion using CFD simulation. The intruded GDL geometries, evaluated by an optical microscope with 200 times enlargement, are transferred to pressure drop behaviors by a numerical CFD model. These results are compared to the results of the differential pressure method of mapping the pressure distribution, described in [43]. The intrusion of the GDL leads to homogeneous flow distribution up to clamping pressures of 2.5 MPa. The inhomogeneous intrusion, induced by cracked fibers that extend into the channel, dominates the flow at higher clamping pressures and leads to the exponential increase in pressure drop in the differential pressure method. For clamping pressures used in typical fuel cell applications, the results of both methods show homogeneous flow through the channels.

Tree Sampling as a Method to Assess Vapor Intrusion Potential at a Site Characterized by VOC-Contaminated Groundwater and Soil.

PubMed

Wilson, Jordan L; Limmer, Matthew A; Samaranayake, V A; Schumacher, John G; Burken, Joel G

2017-09-19

Vapor intrusion (VI) by volatile organic compounds (VOCs) in the built environment presents a threat to human health. Traditional VI assessments are often time-, cost-, and labor-intensive; whereas traditional subsurface methods sample a relatively small volume in the subsurface and are difficult to collect within and near structures. Trees could provide a similar subsurface sample where roots act as the "sampler' and are already onsite. Regression models were developed to assess the relation between PCE concentrations in over 500 tree-core samples with PCE concentrations in over 50 groundwater and 1000 soil samples collected from a tetrachloroethylene- (PCE-) contaminated Superfund site and analyzed using gas chromatography. Results indicate that in planta concentrations are significantly and positively related to PCE concentrations in groundwater samples collected at depths less than 20 m (adjusted R 2 values greater than 0.80) and in soil samples (adjusted R 2 values greater than 0.90). Results indicate that a 30 cm diameter tree characterizes soil concentrations at depths less than 6 m over an area of 700-1600 m 2 , the volume of a typical basement. These findings indicate that tree sampling may be an appropriate method to detect contamination at shallow depths at sites with VI.

Tree sampling as a method to assess vapor intrusion potential at a site characterized by VOC-contaminated groundwater and soil

USGS Publications Warehouse

Wilson, Jordan L.; Limmer, Matthew A.; Samaranayake, V. A.; Schumacher, John G.; Burken, Joel G.

2017-01-01

Vapor intrusion (VI) by volatile organic compounds (VOCs) in the built environment presents a threat to human health. Traditional VI assessments are often time-, cost-, and labor-intensive; whereas traditional subsurface methods sample a relatively small volume in the subsurface and are difficult to collect within and near structures. Trees could provide a similar subsurface sample where roots act as the “sampler’ and are already onsite. Regression models were developed to assess the relation between PCE concentrations in over 500 tree-core samples with PCE concentrations in over 50 groundwater and 1000 soil samples collected from a tetrachloroethylene- (PCE-) contaminated Superfund site and analyzed using gas chromatography. Results indicate that in planta concentrations are significantly and positively related to PCE concentrations in groundwater samples collected at depths less than 20 m (adjusted R2 values greater than 0.80) and in soil samples (adjusted R2 values greater than 0.90). Results indicate that a 30 cm diameter tree characterizes soil concentrations at depths less than 6 m over an area of 700–1600 m2, the volume of a typical basement. These findings indicate that tree sampling may be an appropriate method to detect contamination at shallow depths at sites with VI.

Toddler Inhibited Temperament, Maternal Cortisol Reactivity and Embarrassment, and Intrusive Parenting

PubMed Central

Kiel, Elizabeth J.; Buss, Kristin A.

2013-01-01

The relevance of parenting behavior to toddlers’ development necessitates a better understanding of the influences on parents during parent-child interactions. Toddlers’ inhibited temperament may relate to parenting behaviors, such as intrusiveness, that predict outcomes later in childhood. The conditions under which inhibited temperament relates to intrusiveness, however, remain understudied. A multi-method approach would acknowledge that several levels of processes determine mothers’ experiences during situations in which they witness their toddlers interacting with novelty. As such, the current study examined maternal cortisol reactivity and embarrassment about shyness as moderators of the relation between toddlers’ inhibited temperament and maternal intrusive behavior. Participants included 92 24-month-olds toddlers and their mothers. Toddlers’ inhibited temperament and maternal intrusiveness were measured observationally in the laboratory. Mothers supplied saliva samples at the beginning of the laboratory visit and 20 minutes after observation. Maternal cortisol reactivity interacted with inhibited temperament in relation to intrusive behavior, such that mothers with higher levels of cortisol reactivity were observed to be more intrusive with more highly inhibited toddlers. Embarrassment related to intrusive behavior as a main effect. These results highlight the importance of considering child characteristics and psychobiological processes in relation to parenting behavior. PMID:23750532

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

Diagnosis of femtosecond plasma filament by channeling microwaves along the filament

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

Alshershby, Mostafa; Ren, Yu; Qin, Jiang

2013-05-20

We introduce a simple, fast, and non-intrusive experimental method to obtain the basic parameters of femtosecond laser-generated plasma filament. The method is based on the channeling of microwaves along both a plasma filament and a well-defined conducting wire. By comparing the detected microwaves that propagate along the plasma filament and a copper wire with known conductivity and spatial dimension, the basic parameters of the plasma filament can be easily obtained. As a result of the possibility of channeling microwave radiation along the plasma filament, we were then able to obtain the plasma density distribution along the filament length.

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.

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.

Maxillary molar intrusion with micro-implant anchorage (MIA).

PubMed

Park, Hyo-Sang; Jang, Bong-Kyu; Kyung, Hee-Moon

2005-11-01

Intrusion of the maxillary molars is difficult to accomplish using traditional methods of anchorage. To describe methods of maxillary molar intrusion with the aid of micro-implants. Micro-implants provide stable intra-oral anchorage and enable the maxillary molars to be intruded without the usual side effects. Three adult patients are presented showing how micro-implants can be used to intrude the maxillary molars. In the first patient micro-implants were placed in the alveolar process between the second premolar and first molar, in the second patient micro-implants were placed in the palatal alveolar process between the first and second molars, and in the third patient a micro-implant was placed in the palate paramedially. A transpalatal bar was used to prevent bucco- or linguoversion of the molars during intrusion. The maxillary molars can be intruded with intra-oral anchorage derived from microscrew implants.

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.

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.

Quantitation by Portable Gas Chromatography: Mass Spectrometry of VOCs Associated with Vapor Intrusion

PubMed Central

Fair, Justin D.; Bailey, William F.; Felty, Robert A.; Gifford, Amy E.; Shultes, Benjamin; Volles, Leslie H.

2010-01-01

Development of a robust reliable technique that permits for the rapid quantitation of volatile organic chemicals is an important first step to remediation associated with vapor intrusion. This paper describes the development of an analytical method that allows for the rapid and precise identification and quantitation of halogenated and nonhalogenated contaminants commonly found within the ppbv level at sites where vapor intrusion is a concern. PMID:20885969

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

Automatic Fatigue Detection of Drivers through Yawning Analysis

NASA Astrophysics Data System (ADS)

Azim, Tayyaba; Jaffar, M. Arfan; Ramzan, M.; Mirza, Anwar M.

This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The focus of the paper is on how to detect yawning which is an important cue for determining driver's fatigue. Initially, the face is located through Viola-Jones face detection method in a video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. The degree of mouth openness is extracted on the basis of mouth features, to determine driver's yawning state. If the yawning state of the driver persists for several consecutive frames, the system concludes that the driver is non-vigilant due to fatigue and is thus warned through an alarm. The system reinitializes when occlusion or misdetection occurs. Experiments were carried out using real data, recorded in day and night lighting conditions, and with users belonging to different race and gender.

Detection of periods of food intake using Support Vector Machines.

PubMed

Lopez-Meyer, Paulo; Schuckers, Stephanie; Makeyev, Oleksandr; Sazonov, Edward

2010-01-01

Studies of obesity and eating disorders need objective tools of Monitoring of Ingestive Behavior (MIB) that can detect and characterize food intake. In this paper we describe detection of food intake by a Support Vector Machine classifier trained on time history of chews and swallows. The training was performed on data collected from 18 subjects in 72 experiments involving eating and other activities (for example, talking). The highest accuracy of detecting food intake (94%) was achieved in configuration where both chews and swallows were used as predictors. Using only swallowing as a predictor resulted in 80% accuracy. Experimental results suggest that these two predictors may be used for differentiation between periods of resting and food intake with a resolution of 30 seconds. Proposed methods may be utilized for development of an accurate, inexpensive, and non-intrusive methodology to objectively monitor food intake in free living conditions.

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.

Study of Threat Scenario Reconstruction based on Multiple Correlation

NASA Astrophysics Data System (ADS)

Yuan, Xuejun; Du, Jing; Qin, Futong; Zhou, Yunyan

2017-10-01

The emergence of intrusion detection technology has solved many network attack problems, ensuring the safety of computer systems. However, because of the isolated output alarm information, large amount of data, and mixed events, it is difficult for the managers to understand the deep logic relationship between the alarm information, thus they cannot deduce the attacker’s true intentions. This paper presents a method of online threat scene reconstruction to handle the alarm information, which reconstructs of the threat scene. For testing, the standard data set is used.

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.

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.

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.

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…

Stress Induced in the Periodontal Ligament under Orthodontic Loading (Part I): A Finite Element Method Study Using Linear Analysis

PubMed Central

Hemanth, M; deoli, Shilpi; Raghuveer, H P; Rani, M S; Hegde, Chatura; Vedavathi, B

2015-01-01

Background: Orthodontic tooth movement is a complex procedure that occurs due to various biomechanical changes in the periodontium. Optimal orthodontic forces yield maximum tooth movement whereas if the forces fall beyond the optimal threshold it can cause deleterious effects. Among various types of tooth movements intrusion and lingual root torque are associated with causing root resoprtion, especially with the incisors. Therefore in this study, the stress patterns in the periodontal ligament (PDL) were evaluated with intrusion and lingual root torque using finite element method (FEM). Materials and Methods: A three-dimensional (3D) FEM model of the maxillary incisors was generated using SOLIDWORKS modeling software. Stresses in the PDL were evaluated with intrusive and lingual root torque movements by a 3D FEM using ANSYS software using linear stress analysis. Results: It was observed that with the application of intrusive load compressive stresses were distributed at the apex whereas tensile stress was seen at the cervical margin. With the application of lingual root torque maximum compressive stress was distributed at the apex and tensile stress was distributed throughout the PDL. Conclusion: For intrusive and lingual root torque movements stress values over the PDL was within the range of optimal stress value as proposed by Lee, with a given force system by Proffit as optimum forces for orthodontic tooth movement using linear properties. PMID:26464555

A novel CUSUM-based approach for event detection in smart metering

NASA Astrophysics Data System (ADS)

Zhu, Zhicheng; Zhang, Shuai; Wei, Zhiqiang; Yin, Bo; Huang, Xianqing

2018-03-01

Non-intrusive load monitoring (NILM) plays such a significant role in raising consumer awareness on household electricity use to reduce overall energy consumption in the society. With regard to monitoring low power load, many researchers have introduced CUSUM into the NILM system, since the traditional event detection method is not as effective as expected. Due to the fact that the original CUSUM faces limitations given the small shift is below threshold, we therefore improve the test statistic which allows permissible deviation to gradually rise as the data size increases. This paper proposes a novel event detection and corresponding criterion that could be used in NILM systems to recognize transient states and to help the labelling task. Its performance has been tested in a real scenario where eight different appliances are connected to main line of electric power.

Characterization of electrical appliances in transient state

NASA Astrophysics Data System (ADS)

Wójcik, Augustyn; Winiecki, Wiesław

2017-08-01

The article contains the study about electrical appliance characterization on the basis of power grid signals. To represent devices, parameters of current and voltage signals recorded during transient states are used. In this paper only transients occurring as a result of switching on devices are considered. The way of data acquisition performed in specialized measurement setup developed for electricity load monitoring is described. The paper presents the method of transients detection and the method of appliance parameters calculation. Using the set of acquired measurement data and appropriate software the set of parameters for several household appliances operating in different operating conditions was processed. Usefulness of appliances characterization in Non-Intrusive Appliance Load Monitoring System (NIALMS) with the use of proposed method is discussed focusing on obtained results.

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

Beaver, Justin M; Borges, Raymond Charles; Buckner, Mark A

Critical infrastructure Supervisory Control and Data Acquisition (SCADA) systems were designed to operate on closed, proprietary networks where a malicious insider posed the greatest threat potential. The centralization of control and the movement towards open systems and standards has improved the efficiency of industrial control, but has also exposed legacy SCADA systems to security threats that they were not designed to mitigate. This work explores the viability of machine learning methods in detecting the new threat scenarios of command and data injection. Similar to network intrusion detection systems in the cyber security domain, the command and control communications in amore » critical infrastructure setting are monitored, and vetted against examples of benign and malicious command traffic, in order to identify potential attack events. Multiple learning methods are evaluated using a dataset of Remote Terminal Unit communications, which included both normal operations and instances of command and data injection attack scenarios.« 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

Non-Intrusive, Time-Resolved Hall Thruster Near-Field Electron Temperature Measurements

DTIC Science & Technology

2011-08-01

With the growing interest in Hall thruster technology, comes the need to fully characterize the plasma dynamics that determine performance. Of...instabilities characteristic of Hall thruster behavior, time resolved techniques must be developed. This study presents a non-intrusive method of

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

UQTk Version 3.0.3 User Manual

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

Sargsyan, Khachik; Safta, Cosmin; Chowdhary, Kamaljit Singh

2017-05-01

The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.0.3 offers intrusive and non-intrusive methods for propagating input uncertainties through computational models, tools for sen- sitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters from experimental data. This manual discusses the download and installation process for UQTk, provides pointers to the UQ methods used in the toolkit, and describes some of the examples provided with the toolkit.

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.

A machine learning evaluation of an artificial immune system.

PubMed

Glickman, Matthew; Balthrop, Justin; Forrest, Stephanie

2005-01-01

ARTIS is an artificial immune system framework which contains several adaptive mechanisms. LISYS is a version of ARTIS specialized for the problem of network intrusion detection. The adaptive mechanisms of LISYS are characterized in terms of their machine-learning counterparts, and a series of experiments is described, each of which isolates a different mechanism of LISYS and studies its contribution to the system's overall performance. The experiments were conducted on a new data set, which is more recent and realistic than earlier data sets. The network intrusion detection problem is challenging because it requires one-class learning in an on-line setting with concept drift. The experiments confirm earlier experimental results with LISYS, and they study in detail how LISYS achieves success on the new data set.

Depression and Related Problems in University Students

ERIC Educational Resources Information Center

Field, Tiffany; Diego, Miguel; Pelaez, Martha; Deeds, Osvelia; Delgado, Jeannette

2012-01-01

Method: Depression and related problems were studied in a sample of 283 university students. Results: The students with high depression scores also had high scores on anxiety, intrusive thoughts, controlling intrusive thoughts and sleep disturbances scales. A stepwise regression suggested that those problems contributed to a significant proportion…

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.

Vulnerability of water distribution systems to pathogen intrusion: how effective is a disinfectant residual?

PubMed

Propato, Marco; Uber, James G

2004-07-01

Can the spread of infectious disease through water distribution systems be halted by a disinfectant residual? This question is overdue for an answer. Regulatory agencies and water utilities have long been concerned about accidental intrusions of pathogens into distribution system pipelines (i.e., cross-connections) and are increasingly concerned about deliberate pathogen contamination. Here, a simulation framework is developed and used to assess the vulnerability of a water system to microbiological contamination. The risk of delivering contaminated water to consumers is quantified by a network water quality model that includes disinfectant decay and disinfection kinetics. The framework is applied to two example networks under a worst-case deliberate intrusion scenario. Results show that the risk of consumer exposure is affected by the residual maintenance strategy employed. The common regulation that demands a "detectable" disinfectant residual may not provide effective consumer protection against microbial contamination. A chloramine residual, instead of free chlorine, may significantly weaken this final barrier against pathogen intrusions. Moreover, the addition of a booster station at storage tanks may improve consumer protection without requiring excessive disinfectant.

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.

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

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.

METHOD AND LOCATION OF GROUND WATER SAMPLING: IMPACT ON ATTENUATION FACTORS FOR ASSESSING IMPACT ON VAPOR INTRUSION

EPA Science Inventory

The Draft EPA Subsurface Vapor Intrusion Guidance Document was established to "address the incremental increases in exposures and risks from subsurface contaminants that my be intruding into indoor air". The document utilizes attenuation factors based on indoor air/soil gas or i...

A Markov game theoretic data fusion approach for cyber situational awareness

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Cruz, Jose B., Jr.; Haynes, Leonard; Kruger, Martin; Blasch, Erik

2007-04-01

This paper proposes an innovative data-fusion/ data-mining game theoretic situation awareness and impact assessment approach for cyber network defense. Alerts generated by Intrusion Detection Sensors (IDSs) or Intrusion Prevention Sensors (IPSs) are fed into the data refinement (Level 0) and object assessment (L1) data fusion components. High-level situation/threat assessment (L2/L3) data fusion based on Markov game model and Hierarchical Entity Aggregation (HEA) are proposed to refine the primitive prediction generated by adaptive feature/pattern recognition and capture new unknown features. A Markov (Stochastic) game method is used to estimate the belief of each possible cyber attack pattern. Game theory captures the nature of cyber conflicts: determination of the attacking-force strategies is tightly coupled to determination of the defense-force strategies and vice versa. Also, Markov game theory deals with uncertainty and incompleteness of available information. A software tool is developed to demonstrate the performance of the high level information fusion for cyber network defense situation and a simulation example shows the enhanced understating of cyber-network defense.

Salp distribution and grazing in a saline intrusion off NW Spain

NASA Astrophysics Data System (ADS)

Huskin, Iñaki; Elices, Ma. José; Anadón, Ricardo

2003-07-01

Salp distribution and grazing were studied along three transects (19 stations) and a Lagrangian phase (7 stations) off Galician coast (NW Spain) in November 1999 during GIGOVI 99 cruise. A poleward saline intrusion was detected at the shelf-break, reaching salinity values above 35.90 u.p.s. at 100-m depth. The salp community was dominated by Salpa fusiformis, although Cyclosalpa bakeri, Thalia democratica and Iasis zonaria were also found in the study area. Total salp abundance ranged from 4 to 4500 ind m -2, representing biomass values between 0.2 and 2750 mg C m -2. Maximum densities were located in the frontal area separating the saline body from coastal waters. S. fusiformis pigment ingestion was estimated using the gut fluorescence method. Gut contents were linearly related to salp body size. Total pigment ingestion ranged from 0.001 to 15 mg Chl- a m -2 d -1, with maximum values at the coastal edge of the saline body. Estimated ingestion translates into an average daily grazing impact of 7% of chlorophyll standing stock, ranging from <1% to 77%.

A Non-Intrusive Algorithm for Sensitivity Analysis of Chaotic Flow Simulations

NASA Technical Reports Server (NTRS)

Blonigan, Patrick J.; Wang, Qiqi; Nielsen, Eric J.; Diskin, Boris

2017-01-01

We demonstrate a novel algorithm for computing the sensitivity of statistics in chaotic flow simulations to parameter perturbations. The algorithm is non-intrusive but requires exposing an interface. Based on the principle of shadowing in dynamical systems, this algorithm is designed to reduce the effect of the sampling error in computing sensitivity of statistics in chaotic simulations. We compare the effectiveness of this method to that of the conventional finite difference method.

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

Jackson, K.A.; Neuman, M.C.; Simmonds, D.D.

An effective method for detecting computer misuse is the automatic monitoring and analysis of on-line user activity. This activity is reflected in the system audit record, in the system vulnerability posture, and in other evidence found through active testing of the system. During the last several years we have implemented an automatic misuse detection system at Los Alamos. This is the Network Anomaly Detection and Intrusion Reporter (NADIR). We are currently expanding NADIR to include processing of the Cray UNICOS operating system. This new component is called the UNICOS Realtime NADIR, or UNICORN. UNICORN summarizes user activity and system configurationmore » in statistical profiles. It compares these profiles to expert rules that define security policy and improper or suspicious behavior. It reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations. The first phase of UNICORN development is nearing completion, and will be operational in late 1994.« less

Towards Reliable Evaluation of Anomaly-Based Intrusion Detection Performance

NASA Technical Reports Server (NTRS)

Viswanathan, Arun

2012-01-01

This report describes the results of research into the effects of environment-induced noise on the evaluation process for anomaly detectors in the cyber security domain. This research was conducted during a 10-week summer internship program from the 19th of August, 2012 to the 23rd of August, 2012 at the Jet Propulsion Laboratory in Pasadena, California. The research performed lies within the larger context of the Los Angeles Department of Water and Power (LADWP) Smart Grid cyber security project, a Department of Energy (DoE) funded effort involving the Jet Propulsion Laboratory, California Institute of Technology and the University of Southern California/ Information Sciences Institute. The results of the present effort constitute an important contribution towards building more rigorous evaluation paradigms for anomaly-based intrusion detectors in complex cyber physical systems such as the Smart Grid. Anomaly detection is a key strategy for cyber intrusion detection and operates by identifying deviations from profiles of nominal behavior and are thus conceptually appealing for detecting "novel" attacks. Evaluating the performance of such a detector requires assessing: (a) how well it captures the model of nominal behavior, and (b) how well it detects attacks (deviations from normality). Current evaluation methods produce results that give insufficient insight into the operation of a detector, inevitably resulting in a significantly poor characterization of a detectors performance. In this work, we first describe a preliminary taxonomy of key evaluation constructs that are necessary for establishing rigor in the evaluation regime of an anomaly detector. We then focus on clarifying the impact of the operational environment on the manifestation of attacks in monitored data. We show how dynamic and evolving environments can introduce high variability into the data stream perturbing detector performance. Prior research has focused on understanding the impact of this variability in training data for anomaly detectors, but has ignored variability in the attack signal that will necessarily affect the evaluation results for such detectors. We posit that current evaluation strategies implicitly assume that attacks always manifest in a stable manner; we show that this assumption is wrong. We describe a simple experiment to demonstrate the effects of environmental noise on the manifestation of attacks in data and introduce the notion of attack manifestation stability. Finally, we argue that conclusions about detector performance will be unreliable and incomplete if the stability of attack manifestation is not accounted for in the evaluation strategy.

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.

Investigating subsidence at volcanoes in northern California using InSAR

NASA Astrophysics Data System (ADS)

Parker, A. L.; Biggs, J.; Annen, C.; Lu, Z.

2013-12-01

Both Medicine Lake Volcano (MLV) and Lassen Volcanic Center (LVC), northern CA, show signs of subsidence at rates of ~1 cm/yr. Leveling and campaign GPS measurements show that MLV has subsided at a constant rate for over 50 years, making the geodetic history of this volcano unique in both its duration and continuity. Here, we summarise and build upon the existing geodetic records at MLV and LVC, using interferometric synthetic aperture radar (InSAR) to extend the time-series of deformation measurements to 2011. We also use the improved spatial resolution of InSAR measurements to investigate causes of long-term subsidence, providing new insight into magmatic storage conditions at MLV and the timescales of deformation due to cooling and crystallization. A large InSAR dataset has been acquired for the volcanoes of northern CA, but application of the data has been limited by extensive noise and incoherence. We analyse multiple datasets from MLV and LVC and, with the use of multi-temporal InSAR analysis methods (noise-based stacking, π-RATE and StaMPS), demonstrate how InSAR may be used more successfully as a monitoring tool in this region. By comparing InSAR results for MLV to past geodetic studies, we demonstrate that subsidence is on going at ~1 cm/yr with no detectable change in rate. We find that the best fitting source geometry to InSAR data is a sill approximated by a horizontal penny-shaped crack, with radius 2 km and depth 11 km, undergoing volume loss at a rate of -0.0022 km3/yr. We discuss possible source mechanisms of long-term subsidence, investigating volume loss due to cooling and crystallization of an intrusion. We calculate the temperature, melt fraction and volume loss of an intrusion over time using petrological information and a numerical thermal model of heat loss by conduction. The geometry of the intrusion is based upon the depth and radius of the penny-shaped crack model. We run simulations for a range of thicknesses between that of a single intrusion (~50 m) and that of the larger column of intrusive material thought to exist beneath the edifice (~7000 m). Using constraints from the geodetic record, we identify a range of sills with volumes < 10 km3 that can account for the deformation recorded at MLV. We use these models to discuss the timing of intrusion and forecast the total duration of cooling. These processes are also significant at LVC and other Cascade volcanoes, where hydrothermal activity is likely to be driven by heat from magmatic intrusions and the exsolution of volatiles that occurs during cooling and crystallization.

Research on Abnormal Detection Based on Improved Combination of K - means and SVDD

NASA Astrophysics Data System (ADS)

Hao, Xiaohong; Zhang, Xiaofeng

2018-01-01

In order to improve the efficiency of network intrusion detection and reduce the false alarm rate, this paper proposes an anomaly detection algorithm based on improved K-means and SVDD. The algorithm first uses the improved K-means algorithm to cluster the training samples of each class, so that each class is independent and compact in class; Then, according to the training samples, the SVDD algorithm is used to construct the minimum superspheres. The subordinate relationship of the samples is determined by calculating the distance of the minimum superspheres constructed by SVDD. If the test sample is less than the center of the hypersphere, the test sample belongs to this class, otherwise it does not belong to this class, after several comparisons, the final test of the effective detection of the test sample.In this paper, we use KDD CUP99 data set to simulate the proposed anomaly detection algorithm. The results show that the algorithm has high detection rate and low false alarm rate, which is an effective network security protection method.

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.

ASSESSMENT OF VAPOR INTRUSION IN HOMES NEAR THE RAYMARK SUPERFUND SITE USING BASEMENT AND SUB-SLAB AIR SAMPLES

EPA Science Inventory

This report describes the results of an investigation conducted to assist EPA’s New England Regional Office in evaluating vapor intrusion at 15 homes and one commercial building near the Raymark Superfund Site in Stratford, Connecticut. Methods were developed to sample sub-slab ...

Orthodontic intrusion of maxillary incisors: a 3D finite element method study

PubMed Central

Saga, Armando Yukio; Maruo, Hiroshi; Argenta, Marco André; Maruo, Ivan Toshio; Tanaka, Orlando Motohiro

2016-01-01

Objective: In orthodontic treatment, intrusion movement of maxillary incisors is often necessary. Therefore, the objective of this investigation is to evaluate the initial distribution patterns and magnitude of compressive stress in the periodontal ligament (PDL) in a simulation of orthodontic intrusion of maxillary incisors, considering the points of force application. Methods: Anatomic 3D models reconstructed from cone-beam computed tomography scans were used to simulate maxillary incisors intrusion loading. The points of force application selected were: centered between central incisors brackets (LOAD 1); bilaterally between the brackets of central and lateral incisors (LOAD 2); bilaterally distal to the brackets of lateral incisors (LOAD 3); bilaterally 7 mm distal to the center of brackets of lateral incisors (LOAD 4). Results and Conclusions: Stress concentrated at the PDL apex region, irrespective of the point of orthodontic force application. The four load models showed distinct contour plots and compressive stress values over the midsagittal reference line. The contour plots of central and lateral incisors were not similar in the same load model. LOAD 3 resulted in more balanced compressive stress distribution. PMID:27007765

Effects of Sleep after Experimental Trauma on Intrusive Emotional Memories

PubMed Central

Kleim, Birgit; Wysokowsky, Julia; Schmid, Nuria; Seifritz, Erich; Rasch, Björn

2016-01-01

Study Objectives: To investigate sleep's effect in the immediate aftermath of experiencing an analog trauma in the laboratory on reducing intrusive emotional memory formation. Methods: Sixty-five healthy women were exposed to an experimental laboratory trauma. They viewed a neutral and a trauma film in the laboratory and were randomly allocated to either a group that slept following film viewing or a group that remained awake. Sleep was recorded with electroencephalogram in a subgroup of participants in the sleep group. All participants recorded intrusive memories in the week following the film. Results: The sleep group experienced fewer and less distressing intrusive trauma memories compared to the wake group. These effects were particularly evident toward the end of the week. Duration spent in stage N2 as opposed to light N1 sleep, a higher number of fast parietal sleep spindles and a lower rapid eye movement sleep density predicted intrusion frequency. Conclusions: Our results have clinical implications and set the ground for early-intervention sleep studies following trauma and prevention of chronic posttrauma disorders. Citation: Kleim B, Wysokowsky J, Schmid N, Seifritz E, Rasch B. Effects of sleep after experimental trauma on intrusive emotional memories. SLEEP 2016;39(12):2125–2132. PMID:27748249

Partial Discharge Monitoring on Metal-Enclosed Switchgear with Distributed Non-Contact Sensors.

PubMed

Zhang, Chongxing; Dong, Ming; Ren, Ming; Huang, Wenguang; Zhou, Jierui; Gao, Xuze; Albarracín, Ricardo

2018-02-11

Metal-enclosed switchgear, which are widely used in the distribution of electrical energy, play an important role in power distribution networks. Their safe operation is directly related to the reliability of power system as well as the power quality on the consumer side. Partial discharge detection is an effective way to identify potential faults and can be utilized for insulation diagnosis of metal-enclosed switchgear. The transient earth voltage method, an effective non-intrusive method, has substantial engineering application value for estimating the insulation condition of switchgear. However, the practical application effectiveness of TEV detection is not satisfactory because of the lack of a TEV detection application method, i.e., a method with sufficient technical cognition and analysis. This paper proposes an innovative online PD detection system and a corresponding application strategy based on an intelligent feedback distributed TEV wireless sensor network, consisting of sensing, communication, and diagnosis layers. In the proposed system, the TEV signal or status data are wirelessly transmitted to the terminal following low-energy signal preprocessing and acquisition by TEV sensors. Then, a central server analyzes the correlation of the uploaded data and gives a fault warning level according to the quantity, trend, parallel analysis, and phase resolved partial discharge pattern recognition. In this way, a TEV detection system and strategy with distributed acquisition, unitized fault warning, and centralized diagnosis is realized. The proposed system has positive significance for reducing the fault rate of medium voltage switchgear and improving its operation and maintenance level.

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.

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

Donnelly, H.; Fullwood, R.; Glancy, J.

This is the second volume of a two volume report on the VISA method for evaluating safeguards at fixed-site facilities. This volume contains appendices that support the description of the VISA concept and the initial working version of the method, VISA-1, presented in Volume I. The information is separated into four appendices, each describing details of one of the four analysis modules that comprise the analysis sections of the method. The first appendix discusses Path Analysis methodology, applies it to a Model Fuel Facility, and describes the computer codes that are being used. Introductory material on Path Analysis given inmore » Chapter 3.2.1 and Chapter 4.2.1 of Volume I. The second appendix deals with Detection Analysis, specifically the schemes used in VISA-1 for classifying adversaries and the methods proposed for evaluating individual detection mechanisms in order to build the data base required for detection analysis. Examples of evaluations on identity-access systems, SNM portal monitors, and intrusion devices are provided. The third appendix describes the Containment Analysis overt-segment path ranking, the Monte Carlo engagement model, the network simulation code, the delay mechanism data base, and the results of a sensitivity analysis. The last appendix presents general equations used in Interruption Analysis for combining covert-overt segments and compares them with equations given in Volume I, Chapter 3.« less

Design process and preliminary psychometric study of a video game to detect cognitive impairment in senior adults

PubMed Central

Perez-Rodriguez, Roberto; Facal, David; Fernandez-Iglesias, Manuel J.; Anido-Rifon, Luis; Mouriño-Garcia, Marcos

2017-01-01

Introduction Assessment of episodic memory has been traditionally used to evaluate potential cognitive impairments in senior adults. Typically, episodic memory evaluation is based on personal interviews and pen-and-paper tests. This article presents the design, development and a preliminary validation of a novel digital game to assess episodic memory intended to overcome the limitations of traditional methods, such as the cost of its administration, its intrusive character, the lack of early detection capabilities, the lack of ecological validity, the learning effect and the existence of confounding factors. Materials and Methods Our proposal is based on the gamification of the California Verbal Learning Test (CVLT) and it has been designed to comply with the psychometric characteristics of reliability and validity. Two qualitative focus groups and a first pilot experiment were carried out to validate the proposal. Results A more ecological, non-intrusive and better administrable tool to perform cognitive assessment was developed. Initial evidence from the focus groups and pilot experiment confirmed the developed game’s usability and offered promising results insofar its psychometric validity is concerned. Moreover, the potential of this game for the cognitive classification of senior adults was confirmed, and administration time is dramatically reduced with respect to pen-and-paper tests. Limitations Additional research is needed to improve the resolution of the game for the identification of specific cognitive impairments, as well as to achieve a complete validation of the psychometric properties of the digital game. Conclusion Initial evidence show that serious games can be used as an instrument to assess the cognitive status of senior adults, and even to predict the onset of mild cognitive impairments or Alzheimer’s disease. PMID:28674661

Stress Induced in the Periodontal Ligament under Orthodontic Loading (Part I): A Finite Element Method Study Using Linear Analysis.

PubMed

Hemanth, M; Deoli, Shilpi; Raghuveer, H P; Rani, M S; Hegde, Chatura; Vedavathi, B

2015-08-01

Orthodontic tooth movement is a complex procedure that occurs due to various biomechanical changes in the periodontium. Optimal orthodontic forces yield maximum tooth movement whereas if the forces fall beyond the optimal threshold it can cause deleterious effects. Among various types of tooth movements intrusion and lingual root torque are associated with causing root resoprtion, especially with the incisors. Therefore in this study, the stress patterns in the periodontal ligament (PDL) were evaluated with intrusion and lingual root torque using finite element method (FEM). A three-dimensional (3D) FEM model of the maxillary incisors was generated using SOLIDWORKS modeling software. Stresses in the PDL were evaluated with intrusive and lingual root torque movements by a 3D FEM using ANSYS software using linear stress analysis. It was observed that with the application of intrusive load compressive stresses were distributed at the apex whereas tensile stress was seen at the cervical margin. With the application of lingual root torque maximum compressive stress was distributed at the apex and tensile stress was distributed throughout the PDL. For intrusive and lingual root torque movements stress values over the PDL was within the range of optimal stress value as proposed by Lee, with a given force system by Proffit as optimum forces for orthodontic tooth movement using linear properties.

Integral Analysis of Field Work and Laboratory Electrical Resistivity Imaging for Saline Water Intrusion Prediction in Groundwater

NASA Astrophysics Data System (ADS)

Zawawi, M. H.; Zahar, M. F.; Hashim, M. M. M.; Hazreek, Z. A. M.; Zahari, N. M.; Kamaruddin, M. A.

2018-04-01

Saline water intrusion is a serious threat to the groundwater as many part of the world utilize groundwater as their main source of fresh water supply. The usage of high salinity level of water as drinking water can lead to a very serious health hazard towards human. Saline water intrusion is a process by which induced flow of seawater into freshwater aquifer along the coastal area. It might happen due to human action and/or by natural event. The climate change and rise up of sea level may speed up the saline water intrusion process. The conventional method for distinguishing and checking saltwater interference to groundwater along the coast aquifers is to gather and test the groundwater from series of observation wells (borehole) with an end goal to give the important information about the hydrochemistry data to conclude whether the water in the well are safe to consume or not. An integrated approach of field and laboratory electrical resistivity investigation is proposed for indicating the contact region between saline and fresh groundwater. It was found that correlation for both soilbox produced almost identical curvilinear trends for 2% increment of seawater tested using sand sample. This project contributes towards predicting the saline water intrusion to the groundwater by non-destructive test that can replaced the conventional method of groundwater monitoring using series of boreholes in the coastal area

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 ...

Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way

PubMed Central

López-Gil, Juan-Miguel; Virgili-Gomá, Jordi; Gil, Rosa; Guilera, Teresa; Batalla, Iolanda; Soler-González, Jorge; García, Roberto

2016-01-01

Technical advances, particularly the integration of wearable and embedded sensors, facilitate tracking of physiological responses in a less intrusive way. Currently, there are many devices that allow gathering biometric measurements from human beings, such as EEG Headsets or Health Bracelets. The massive data sets generated by tracking of EEG and physiology may be used, among other things, to infer knowledge about human moods and emotions. Apart from direct biometric signal measurement, eye tracking systems are nowadays capable of determining the point of gaze of the users when interacting in ICT environments, which provides an added value research on many different areas, such as psychology or marketing. We present a process in which devices for eye tracking, biometric, and EEG signal measurements are synchronously used for studying both basic and complex emotions. We selected the least intrusive devices for different signal data collection given the study requirements and cost constraints, so users would behave in the most natural way possible. On the one hand, we have been able to determine basic emotions participants were experiencing by means of valence and arousal. On the other hand, a complex emotion such as empathy has also been detected. To validate the usefulness of this approach, a study involving forty-four people has been carried out, where they were exposed to a series of affective stimuli while their EEG activity, biometric signals, and eye position were synchronously recorded to detect self-regulation. The hypothesis of the work was that people who self-regulated would show significantly different results when analyzing their EEG data. Participants were divided into two groups depending on whether Electro Dermal Activity (EDA) data indicated they self-regulated or not. The comparison of the results obtained using different machine learning algorithms for emotion recognition shows that using EEG activity alone as a predictor for self-regulation does not allow properly determining whether a person in self-regulation its emotions while watching affective stimuli. However, adequately combining different data sources in a synchronous way to detect emotions makes it possible to overcome the limitations of single detection methods. PMID:27594831

Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way.

PubMed

López-Gil, Juan-Miguel; Virgili-Gomá, Jordi; Gil, Rosa; García, Roberto

2016-01-01

Technical advances, particularly the integration of wearable and embedded sensors, facilitate tracking of physiological responses in a less intrusive way. Currently, there are many devices that allow gathering biometric measurements from human beings, such as EEG Headsets or Health Bracelets. The massive data sets generated by tracking of EEG and physiology may be used, among other things, to infer knowledge about human moods and emotions. Apart from direct biometric signal measurement, eye tracking systems are nowadays capable of determining the point of gaze of the users when interacting in ICT environments, which provides an added value research on many different areas, such as psychology or marketing. We present a process in which devices for eye tracking, biometric, and EEG signal measurements are synchronously used for studying both basic and complex emotions. We selected the least intrusive devices for different signal data collection given the study requirements and cost constraints, so users would behave in the most natural way possible. On the one hand, we have been able to determine basic emotions participants were experiencing by means of valence and arousal. On the other hand, a complex emotion such as empathy has also been detected. To validate the usefulness of this approach, a study involving forty-four people has been carried out, where they were exposed to a series of affective stimuli while their EEG activity, biometric signals, and eye position were synchronously recorded to detect self-regulation. The hypothesis of the work was that people who self-regulated would show significantly different results when analyzing their EEG data. Participants were divided into two groups depending on whether Electro Dermal Activity (EDA) data indicated they self-regulated or not. The comparison of the results obtained using different machine learning algorithms for emotion recognition shows that using EEG activity alone as a predictor for self-regulation does not allow properly determining whether a person in self-regulation its emotions while watching affective stimuli. However, adequately combining different data sources in a synchronous way to detect emotions makes it possible to overcome the limitations of single detection methods.

Experimental Design for the Evaluation of Detection Techniques of Hidden Corrosion Beneath the Thermal Protective System of the Space Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Kemmerer, Catherine C.; Jacoby, Joseph A.; Lomness, Janice K.; Hintze, Paul E.; Russell, Richard W.

2007-01-01

The detection of corrosion beneath Space Shuttle Orbiter thermal protective system is traditionally accomplished by removing the Reusable Surface Insulation tiles and performing a visual inspection of the aluminum substrate and corrosion protection system. This process is time consuming and has the potential to damage high cost tiles. To evaluate non-intrusive NDE methods, a Proof of Concept (PoC) experiment was designed and test panels were manufactured. The objective of the test plan was three-fold: establish the ability to detect corrosion hidden from view by tiles; determine the key factor affecting detectability; roughly quantify the detection threshold. The plan consisted of artificially inducing dimensionally controlled corrosion spots in two panels and rebonding tile over the spots to model the thermal protective system of the orbiter. The corrosion spot diameter ranged from 0.100" to 0.600" inches and the depth ranged from 0.003" to 0.020". One panel consisted of a complete factorial array of corrosion spots with and without tile coverage. The second panel consisted of randomized factorial points replicated and hidden by tile. Conventional methods such as ultrasonics, infrared, eddy current and microwave methods have shortcomings. Ultrasonics and IR cannot sufficiently penetrate the tiles, while eddy current and microwaves have inadequate resolution. As such, the panels were interrogated using Backscatter Radiography and Terahertz Imaging. The terahertz system successfully detected artificially induced corrosion spots under orbiter tile and functional testing is in-work in preparation for implementation.

Thermal Inspection of a Composite Fuselage Section Using a Fixed Eigenvector Principal Component Analysis Method

NASA Technical Reports Server (NTRS)

Zalameda, Joseph N.; Bolduc, Sean; Harman, Rebecca

2017-01-01

A composite fuselage aircraft forward section was inspected with flash thermography. The fuselage section is 24 feet long and approximately 8 feet in diameter. The structure is primarily configured with a composite sandwich structure of carbon fiber face sheets with a Nomex(Trademark) honeycomb core. The outer surface area was inspected. The thermal data consisted of 477 data sets totaling in size of over 227 Gigabytes. Principal component analysis (PCA) was used to process the data sets for substructure and defect detection. A fixed eigenvector approach using a global covariance matrix was used and compared to a varying eigenvector approach. The fixed eigenvector approach was demonstrated to be a practical analysis method for the detection and interpretation of various defects such as paint thickness variation, possible water intrusion damage, and delamination damage. In addition, inspection considerations are discussed including coordinate system layout, manipulation of the fuselage section, and the manual scanning technique used for full coverage.

"SmartMonitor"--an intelligent security system for the protection of individuals and small properties with the possibility of home automation.

PubMed

Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław

2014-06-05

"SmartMonitor" is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the "SmartMonitor" system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons.

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).

Volumetric measurement of root resorption following molar mini-screw implant intrusion using cone beam computed tomography.

PubMed

Li, Wen; Chen, Fei; Zhang, Feng; Ding, Wanghui; Ye, Qingsong; Shi, Jiejun; Fu, Baiping

2013-01-01

Molar intrusion by mini-screw implantation can cause different degrees of root resorption. However, most methods (2-D and 3-D) used for evaluating root resorption have focused on the root length without considering 3-D resorption. The purpose of this study was to volumetrically evaluate root resorption using cone beam computed tomography(CBCT) after mini-screw implant intrusion. 1. The volumes of 32 teeth were measured using CBCT and laser scanning to verify the accuracy of CBCT. 2. Twelve overerupted molars from adult patients were investigated in this study. After mini-screw implants were inserted into the buccal and palatal alveolar bones, 150 g of force was applied to the mini-screw implants on each side to intrude the molars. CBCT images of all patients were taken immediately prior to intrusion and after intrusion. The volumes of the roots were calculated using the Mimics software program. The differences between the pre-intrusion and post-intrusion root volumes were statistically evaluated with a paired-samples t-test. In addition, the losses of the roots were statistically compared with each other using one-way analysis of variance at the P<0.05 level. No statistically significant volume differences were observed between the physical (laser scanning) and CBCT measurements (P>0.05). The overerupted molars were significantly intruded (P<0.05), and the average intrusion was 3.30±1.60 mm. The differences between the pre-intrusion and post-intrusion root volumes were statistically significant for all of the roots investigated (P<0.05). The roots were sorted by volume loss in descending order as follows: mesiobuccal, palatal, and distobuccal. Statistical significance was achieved among the three roots. The average total resorption for each tooth was 58.39±1.54 mm(3). Volume measurement using CBCT was able to effectively evaluate root resorption caused by mini-screw intrusion. The highest volume loss was observed in the mesiobuccal root among the three roots of the investigated first molar teeth.

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...

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments.

PubMed

Jia, Yunjian; Zhou, Zhenyu; Chen, Fei; Duan, Peng; Guo, Zhen; Mumtaz, Shahid

2017-01-13

Tracking people's behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people's access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people's access behaviors can be correctly tracked within a one-second delay.

TReacLab: An object-oriented implementation of non-intrusive splitting methods to couple independent transport and geochemical software

NASA Astrophysics Data System (ADS)

Jara, Daniel; de Dreuzy, Jean-Raynald; Cochepin, Benoit

2017-12-01

Reactive transport modeling contributes to understand geophysical and geochemical processes in subsurface environments. Operator splitting methods have been proposed as non-intrusive coupling techniques that optimize the use of existing chemistry and transport codes. In this spirit, we propose a coupler relying on external geochemical and transport codes with appropriate operator segmentation that enables possible developments of additional splitting methods. We provide an object-oriented implementation in TReacLab developed in the MATLAB environment in a free open source frame with an accessible repository. TReacLab contains classical coupling methods, template interfaces and calling functions for two classical transport and reactive software (PHREEQC and COMSOL). It is tested on four classical benchmarks with homogeneous and heterogeneous reactions at equilibrium or kinetically-controlled. We show that full decoupling to the implementation level has a cost in terms of accuracy compared to more integrated and optimized codes. Use of non-intrusive implementations like TReacLab are still justified for coupling independent transport and chemical software at a minimal development effort but should be systematically and carefully assessed.

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments

PubMed Central

Jia, Yunjian; Zhou, Zhenyu; Chen, Fei; Duan, Peng; Guo, Zhen; Mumtaz, Shahid

2017-01-01

Tracking people’s behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people’s access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people’s access behaviors can be correctly tracked within a one-second delay. PMID:28098772

Estimating respiratory rate from FBG optical sensors by using signal quality measurement.

PubMed

Yongwei Zhu; Maniyeri, Jayachandran; Fook, Victor Foo Siang; Haihong Zhang

2015-08-01

Non-intrusiveness is one of the advantages of in-bed optical sensor device for monitoring vital signs, including heart rate and respiratory rate. Estimating respiratory rate reliably using such sensors, however, is challenging, due to body movement, signal variation according to different subjects or body positions, etc. This paper presents a method for reliable respiratory rate estimation for FBG optical sensors by introducing signal quality estimation. The method estimates the quality of the signal waveform by detecting regularly repetitive patterns using proposed spectrum and cepstrum analysis. Multiple window sizes are used to cater for a wide range of target respiratory rates. Furthermore, the readings of multiple sensors are fused to derive a final respiratory rate. Experiments with 12 subjects and 2 body positions were conducted using polysomnography belt signal as groundtruth. The results demonstrated the effectiveness of the method.

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

Characterization of pore structure in cement-based materials using pressurization-depressurization cycling mercury intrusion porosimetry (PDC-MIP)

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

Zhou Jian, E-mail: Jian.Zhou@tudelft.n; Ye Guang, E-mail: g.ye@tudelft.n; Magnel Laboratory for Concrete Research, Department of Structural Engineering, Ghent University, Technologiepark-Zwijnaarde 904 B-9052, Ghent

2010-07-15

Numerous mercury intrusion porosimetry (MIP) studies have been carried out to investigate the pore structure in cement-based materials. However, the standard MIP often results in an underestimation of large pores and an overestimation of small pores because of its intrinsic limitation. In this paper, an innovative MIP method is developed in order to provide a more accurate estimation of pore size distribution. The new MIP measurements are conducted following a unique mercury intrusion procedure, in which the applied pressure is increased from the minimum to the maximum by repeating pressurization-depressurization cycles instead of a continuous pressurization followed by a continuousmore » depressurization. Accordingly, this method is called pressurization-depressurization cycling MIP (PDC-MIP). By following the PDC-MIP testing sequence, the volumes of the throat pores and the corresponding ink-bottle pores can be determined at every pore size. These values are used to calculate pore size distribution by using the newly developed analysis method. This paper presents an application of PDC-MIP on the investigation of the pore size distribution in cement-based materials. The experimental results of PDC-MIP are compared with those measured by standard MIP. The PDC-MIP is further validated with the other experimental methods and numerical tool, including nitrogen sorption, backscanning electron (BSE) image analysis, Wood's metal intrusion porosimetry (WMIP) and the numerical simulation by the cement hydration model HYMOSTRUC3D.« 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.

On the Salt Water Intrusion into the Durusu Lake, Istanbul: A Joint Central Loop TEM And Multi-Electrode ERT Field Survey

NASA Astrophysics Data System (ADS)

Ardali, Ayça Sultan; Tezkan, Bülent; Gürer, Aysan

2018-02-01

Durusu Lake is the biggest and most important freshwater source supplying drinking water to the European side of Istanbul. In this study, electrical resistivity tomography (ERT) and transient electromagnetic (TEM) measurements were applied to detect a possible salt water intrusion into the lake and to delineate the subsurface structure in the north of Durusu Lake. The ERT and TEM measurements were carried out along six parallel profiles extending from the sea coast to the lake shore on the dune barrier. TEM data were interpreted using different 1-D inversion methods such as Occam, Marquardt, and laterally constrained inversion (LCI). ERT data were interpreted using 2-D inversion techniques. The inversion results of ERT and TEM data were shown as resistivity depth sections including topography. The sand layer spreading over the basin has a resistivity of 150-400 Ωm with a thickness of 5-10 m. The sandy layer with clay, silt, and gravel has a resistivity of 15-100 Ωm and a thickness of 10-40 m followed by a clay layer of a resistivity below 10 Ωm. When the inversion of these data is interpreted along with the hydrogeology of the area, it is concluded that the salt water intrusion along the dune barrier is not common and occurs at a particular area where the distance between lake and sea is very close. Using information from boreholes around the lake, it was verified that the common conductive region at depths of 30 m or more consists of clay layers and clay lenses.

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.

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.

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.

Indoor Air Contamination from Hazardous Waste Sites: Improving the Evidence Base for Decision-Making.

PubMed

Johnston, Jill; MacDonald Gibson, Jacqueline

2015-11-27

At hazardous waste sites, volatile chemicals can migrate through groundwater and soil into buildings, a process known as vapor intrusion. Due to increasing recognition of vapor intrusion as a potential indoor air pollution source, in 2015 the U.S. Environmental Protection Agency (EPA) released a new vapor intrusion guidance document. The guidance specifies two conditions for demonstrating that remediation is needed: (1) proof of a vapor intrusion pathway; and (2) evidence that human health risks exceed established thresholds (for example, one excess cancer among 10,000 exposed people). However, the guidance lacks details on methods for demonstrating these conditions. We review current evidence suggesting that monitoring and modeling approaches commonly employed at vapor intrusion sites do not adequately characterize long-term exposure and in many cases may underestimate risks. On the basis of this evidence, we recommend specific approaches to monitoring and modeling to account for these uncertainties. We propose a value of information approach to integrate the lines of evidence at a site and determine if more information is needed before deciding whether the two conditions specified in the vapor intrusion guidance are satisfied. To facilitate data collection and decision-making, we recommend a multi-directional community engagement strategy and consideration of environment justice concerns.

Indoor Air Contamination from Hazardous Waste Sites: Improving the Evidence Base for Decision-Making

PubMed Central

Johnston, Jill; MacDonald Gibson, Jacqueline

2015-01-01

At hazardous waste sites, volatile chemicals can migrate through groundwater and soil into buildings, a process known as vapor intrusion. Due to increasing recognition of vapor intrusion as a potential indoor air pollution source, in 2015 the U.S. Environmental Protection Agency (EPA) released a new vapor intrusion guidance document. The guidance specifies two conditions for demonstrating that remediation is needed: (1) proof of a vapor intrusion pathway; and (2) evidence that human health risks exceed established thresholds (for example, one excess cancer among 10,000 exposed people). However, the guidance lacks details on methods for demonstrating these conditions. We review current evidence suggesting that monitoring and modeling approaches commonly employed at vapor intrusion sites do not adequately characterize long-term exposure and in many cases may underestimate risks. On the basis of this evidence, we recommend specific approaches to monitoring and modeling to account for these uncertainties. We propose a value of information approach to integrate the lines of evidence at a site and determine if more information is needed before deciding whether the two conditions specified in the vapor intrusion guidance are satisfied. To facilitate data collection and decision-making, we recommend a multi-directional community engagement strategy and consideration of environment justice concerns. PMID:26633433

Intrusive images and voluntary memory for affective pictures: contextualization and dual-task interference.

PubMed

Krans, Julie; Langner, Oliver; Reinecke, Andrea; Pearson, David G

2013-12-01

The present study addressed the role of context information and dual-task interference during the encoding of negative pictures on intrusion development and voluntary recall. Healthy participants were shown negative pictures with or without context information. Pictures were either viewed alone or concurrently with a visuospatial or verbal task. Participants reported their intrusive images of the pictures in a diary. At follow-up, perceptual and contextual memory was tested. Participants in the context group reported more intrusive images and perceptual voluntary memory than participants in the no context group. No effects of the concurrent tasks were found on intrusive image frequency, but perceptual and contextual memory was affected according to the cognitive load of the task. The analogue method cannot be generalized to real-life trauma and the secondary tasks may differ in cognitive load. The findings challenge a dual memory model of PTSD but support an account in which retrieval strategy, rather than encoding processes, accounts for the experience of involuntary versus voluntary recall. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding Dysregulated Behaviors and Compulsions: An Extension of the Emotional Cascade Model and the Mediating Role of Intrusive Thoughts

PubMed Central

Jungmann, Stefanie M.; Vollmer, Noelle; Selby, Edward A.; Witthöft, Michael

2016-01-01

Objective: The Emotional Cascade Model (ECM) by Selby et al. (2008) proposes that people often engage in dysregulated behaviors to end extreme, aversive emotional states triggered by a self-perpetuating vicious cycle of (excessive) rumination, negative affect, and attempts to suppress negative thoughts. Method: Besides replicating the ECM, we introduced intrusions as a mediator between rumination and behavioral dysregulation and tested this extended ECM for compulsions as part of obsessive–compulsive disorders. A structural equation modeling approach was used to test this in a sample of N = 414, randomly recruited from the general population. Results: Intrusions were found to fully mediate the effect of rumination on a broad array of dysregulated behaviors and compulsions. This mediation endured when controlling for symptoms of depression. Conclusion: These findings support the idea that rumination fuels intrusions, which in turn foster dysregulated behaviors. Therefore, addressing rumination as well as intrusions may improve psychotherapeutic interventions for mental disorders characterized by dysregulated behaviors and/or extreme aversive emotional states. PMID:27445948

Seawater intrusion mapping using electrical resistivity tomography and hydrochemical data. An application in the coastal area of eastern Thermaikos Gulf, Greece.

PubMed

Kazakis, N; Pavlou, A; Vargemezis, G; Voudouris, K S; Soulios, G; Pliakas, F; Tsokas, G

2016-02-01

The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl(-) concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km(2)) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia-Epanomi and Aggelochori-Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

LANDSAT and radar mapping of intrusive rocks in SE-Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dossantos, A. R.; Dosanjos, C. E.; Moreira, J. C.; Barbosa, M. P.; Veneziani, P.

1982-01-01

The feasibility of intrusive rock mapping was investigated and criteria for regional geological mapping established at the scale of 1:500,00 in polycyclic and polymetamorphic areas using the logic method of photointerpretation of LANDSAT imagery and radar from the RADAMBRASIL project. The spectral behavior of intrusive rocks, was evaluated using the interactive multispectral image analysis system (Image-100). The region of Campos (city) in northern Rio de Janeiro State was selected as the study area and digital imagery processing and pattern recognition techniques were applied. Various maps at the 2:250,000 scale were obtained to evaluate the results of automatic data processing.

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 Security Framework for Online Distance Learning and Training.

ERIC Educational Resources Information Center

Furnell, S. M.; Onions, P. D.; Bleimann, U.; Gojny, U.; Knahl, M.; Roder, H. F.; Sanders, P. W.

1998-01-01

Presents a generic reference model for online distance learning and discusses security issues for each stage (enrollment, study, completion, termination, suspension). Discusses a security framework (authentication and accountability, access control, intrusion detection, network communications, nonrepudiation, learning resources provider…

Magnetic investigation and 2½ D gravity profile modelling across the Beattie magnetic anomaly in the southeastern Karoo Basin, South Africa

NASA Astrophysics Data System (ADS)

Baiyegunhi, Christopher; Gwavava, Oswald

2017-03-01

The southeastern Karoo Basin is considered to be one of the most prospective areas for shale gas exploration in South Africa. An interesting magnetic anomaly, the Beattie magnetic anomaly (BMA), and geologic intrusions are seen on the magnetic map. To date, the source of the BMA and interconnectivity of the igneous intrusions are not well understood. In this study, we investigate the interconnectivity of the igneous intrusions and possible location of the source of the BMA using gravity and magnetic methods. The gravity model results showed that igneous intrusions are interconnected at depth, which probably pose threat by increasing the risk of fracking the Karoo for shale gas exploration. The magnetic results revealed that the BMA becomes stronger with depth. The average depths to the top of the shallow and deep magnetic sources were estimated to be approximately 0.6 and 15 km, respectively.

Stochastic Optimization for an Analytical Model of Saltwater Intrusion in Coastal Aquifers

PubMed Central

Stratis, Paris N.; Karatzas, George P.; Papadopoulou, Elena P.; Zakynthinaki, Maria S.; Saridakis, Yiannis G.

2016-01-01

The present study implements a stochastic optimization technique to optimally manage freshwater pumping from coastal aquifers. Our simulations utilize the well-known sharp interface model for saltwater intrusion in coastal aquifers together with its known analytical solution. The objective is to maximize the total volume of freshwater pumped by the wells from the aquifer while, at the same time, protecting the aquifer from saltwater intrusion. In the direction of dealing with this problem in real time, the ALOPEX stochastic optimization method is used, to optimize the pumping rates of the wells, coupled with a penalty-based strategy that keeps the saltwater front at a safe distance from the wells. Several numerical optimization results, that simulate a known real aquifer case, are presented. The results explore the computational performance of the chosen stochastic optimization method as well as its abilities to manage freshwater pumping in real aquifer environments. PMID:27689362

A simple way to intrude overerupted upper second molars with miniscrews.

PubMed

Cao, Yang; Liu, Chufeng; Wang, Chunxian; Yang, Xiaoyu; Duan, Peijia; Xu, Chenrong

2013-12-01

Various methods of using skeletal anchorage for the intrusion of overerupted maxillary molars have been reported; however, it is difficult to intrude the overerupted upper second molars because of the low bone density in the region of the tuberosity. This article illustrates a new treatment method using partial fixed edgewise appliances and miniscrews to intrude the overerupted upper second molars. The miniscrews were applied to reinforce the anchorage of the upper first molar. The intrusive force was generated by the Ni-Ti wire. The clinical results showed a significant intrusion effect without root resorption or periodontal problems. This report demonstrates that the combination of partial conventional fixed appliances with miniscrews is a simple and effective treatment option to intrude overerupted upper second molars, especially in situations where miniscrews cannot be inserted directly next to the second molar. © 2013 by the American College of Prosthodontists.

An Excel Macro to Plot the HFE-Diagram to Identify Sea Water Intrusion Phases.

PubMed

Giménez-Forcada, Elena; Sánchez San Román, F Javier

2015-01-01

A hydrochemical facies evolution diagram (HFE-D) is a multirectangular diagram, which is a useful tool in the interpretation of sea water intrusion processes. This method note describes a simple method for generating an HFE-D plot using the spreadsheet software package, Microsoft Excel. The code was applied to groundwater from the alluvial coastal plain of Grosseto (Tuscany, Italy), which is characterized by a complex salinization process in which sea water mixes with sulfate or bicarbonate recharge water. © 2014, National GroundWater Association.

Ultrasonic Measurement of Aircraft Strut Hydraulic Fluid Level

NASA Technical Reports Server (NTRS)

Allison, Sidney G.

2002-01-01

An ultrasonic method is presented for non-intrusively measuring hydraulic fluid level in aircraft struts in the field quickly and easily without modifying the strut or aircraft. The technique interrogates the strut with ultrasonic waves generated and received by a removable ultrasonic transducer hand-held on the outside of the strut in a fashion that is in the presence or absence of hydraulic fluid inside the strut. This technique was successfully demonstrated on an A-6 aircraft strut on the carriage at the Aircraft Landing Dynamics Research Facility at NASA Langley Research Center. Conventional practice upon detection of strut problem symptoms is to remove aircraft from service for extensive maintenance to determine fluid level. No practical technique like the method presented herein for locating strut hydraulic fluid level is currently known to be used.

An analysis of security system for intrusion in Smartphone environment.

PubMed

Louk, Maya; Lim, Hyotaek; Lee, HoonJae

2014-01-01

There are many malware applications in Smartphone. Smartphone's users may become unaware if their data has been recorded and stolen by intruders via malware. Smartphone--whether for business or personal use--may not be protected from malwares. Thus, monitoring, detecting, tracking, and notification (MDTN) have become the main purpose of the writing of this paper. MDTN is meant to enable Smartphone to prevent and reduce the number of cybercrimes. The methods are shown to be effective in protecting Smartphone and isolating malware and sending warning in the form of notification to the user about the danger in progress. In particular, (a) MDTN process is possible and will be enabled for Smartphone environment. (b) The methods are shown to be an advanced security for private sensitive data of the Smartphone user.

An Analysis of Security System for Intrusion in Smartphone Environment

PubMed Central

Louk, Maya; Lim, Hyotaek; Lee, HoonJae

2014-01-01

There are many malware applications in Smartphone. Smartphone's users may become unaware if their data has been recorded and stolen by intruders via malware. Smartphone—whether for business or personal use—may not be protected from malwares. Thus, monitoring, detecting, tracking, and notification (MDTN) have become the main purpose of the writing of this paper. MDTN is meant to enable Smartphone to prevent and reduce the number of cybercrimes. The methods are shown to be effective in protecting Smartphone and isolating malware and sending warning in the form of notification to the user about the danger in progress. In particular, (a) MDTN process is possible and will be enabled for Smartphone environment. (b) The methods are shown to be an advanced security for private sensitive data of the Smartphone user. PMID:25165754

Development of a distributed polarization-OTDR to measure two vibrations with the same frequency

NASA Astrophysics Data System (ADS)

Pan, Yun; Wang, Feng; Wang, Xiangchuan; Zhang, Mingjiang; Zhou, Ling; Sun, Zhenqing; Zhang, Xuping

2015-08-01

A polarization optical time-domain reflectometer (POTDR) can distributedly measure the vibration of fiber by detecting the vibration induced polarization variation only with a polarization analyzer. It has great potential in the monitoring of the border intrusion, structural healthy, anti-stealing of pipeline and so on, because of its simple configuration, fast response speed and distributed measuring ability. However, it is difficult to distinguish two vibrations with the same frequency for POTDR because the signal induced by the first vibration would bury the other vibration induced signal. This paper proposes a simple method to resolve this problem in POTDR by analyzing the phase of the vibration induced signal. The effectiveness of this method in distinguishing two vibrations with the same frequency for POTDR is proved by simulation.

On the relation between crustal deformation and seismicity during the 2012-2014 magmatic intrusions in El Hierro island.

NASA Astrophysics Data System (ADS)

Domínguez Cerdeña, Itahiza; García-Cañada, Laura; Ángeles Benito Saz, María; Del Fresno, Carmen

2017-04-01

The last volcanic eruption in the Canary Islands took place in 2011 less than 2 km offshore El Hierro island, after 3 months of measuring surface deformation (up to 5 cm) and locating more than 10 000 earthquakes. In the two years following the end of the submarine eruption on 5 March 2012, six deep magmatic intrusions were recorded beneath the island. Despite the short time duration of these intrusions, these events have been more energetic that the 2011 pre-eruptive intrusive event but none of them ended in a new eruption. These post-eruptive reactivations are some of the few examples in the world of well monitored magmatic intrusions related with monogenetic volcanism. In order to understand these processes we have analyzed the geodetic and seismic data with different techniques. First, we did a joint hypocentral relocation of the six seismic swarms, including more than 6 300 events, to analyze the relative distribution of the earthquakes from different intrusions. The uncertainties of the earthquakes relocations was reduced to an average value of 300 m. New earthquakes' distribution shows the alignments of the different intrusions and a temporal migration of the events to larger depths. Moreover, we show the results of the ground deformation using GPS data from the network installed on the island (for each of the six intrusive events) and their inversion considering spherical models. In most of the intrusions the optimal source model was shallower and southern than the corresponding seismicity hypocenters. The intruded magma volume ranges from 0.02 to 0.13 km3. Finally, we also computed the b value from the Gutenberg Richter equation by means of a bootstrap method. The spatial and temporal evolution of the b value for the seismicity show a clear correlation with the temporal evolution of the crustal deformation. The six magma intrusions can be grouped, depending on their location, in three pairs each one associated with each of the three active rifts of El Hierro island. Although all intrusions show similar magma supply rate (60-90 m3/s) we found particular characteristic for each the three groups of intrusions, including the relation between seismic energy and deformation or the ratio between seismic and geodetic moment. We discuss the compatibility or not of these results with the possible triaxial nature of the origin of El Hierro island. As a conclusion, we have reviewed the historical seismic catalog and compared these post-eruptive intrusions with other possible magmatic intrusions in the Canary Islands. We found that a maximum of 50% of the volcanic unrests occurred in the Canary Islands in the last century ended in eruptions.

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

Determination of benzimidazole anthelmintics in milk and honey by monolithic fiber-based solid-phase microextraction combined with high-performance liquid chromatography-diode array detection.

PubMed

Zhang, Yong; Huang, Xiaojia; Yuan, Dongxing

2015-01-01

A porous poly(methacrylic acid-co-ethylene dimethacrylate) monolithic fiber (MEMF) for solid-phase microextraction (SPME) of five benzimidazole anthelmintics was prepared by in-situ polymerization. The effect of polymerization conditions on SPME of the target analytes was studied thoroughly. The physicochemical properties of the monolith were characterized by infrared spectroscopy, elemental analysis, scanning electron microscopy, and mercury intrusion porosimetry. Several conditions affecting the extraction efficiency were investigated and, under the optimized conditions, a simple and sensitive method for the determination of trace benzimidazoles residues in milk and honey was established by coupling MEMF-SPME with high-performance liquid chromatography-diode array detection (MEMF-SPME-HPLC-DAD). Under the optimum experimental conditions, the limits of detection (S/N = 3) of the method were 0.11-0.30 μg L(-1) for milk and 0.086-0.28 μg L(-1) for honey. Evaluation of intra-day and inter-day precision showed reproducibility was satisfactory-relative standard deviations (RSD) for both were <10 %. Finally, the method was successfully used for determination of benzimidazole residues in milk and honey. Recoveries obtained for determination of benzimidazole anthelmintics in spiked samples ranged from 72.3 to 121 %, with RSD always <11 %.

Innovative methods to reduce salt water intrusion in harbours

NASA Astrophysics Data System (ADS)

Groenenboom, J.; Uittenbogaard, R.; Hulsen, L.; van der Kaaij, T.; Kielen, N.

2017-12-01

The availability of fresh water in densely populated estuarine environments will in the future more often be threatened due to both human (e.g. channel deepening) and natural (sea-level rise, storm surges, extremely low river discharges) causes. Here, the salt water intrusion into the New Waterway, the main navigation channel of the port of Rotterdam, is used as a case study to elaborate on two innovative ways to mitigate the effects of salt water intrusion. The first method is based on the concept that vertical mixing of a salt wedge reduces its intrusion length. The idea is to equip a vessel with cranes that hold perforated tubes close to the bed alongside the vessel. By connecting compressors to the perforated tubes, a bubble screen with an adjustable vertical location can be created. Since the horizontal location of the bubble screens is not fixed, the vessel can sail in the vicinity of the moving salt wedge therewith increasing the effectiveness of the method. Another advantage of this intervention is that it can be deployed temporarily when the urgency for the prevention of salt water intrusion is high. The second method originates from the Port of Rotterdam Authority and is inspired by a small bypass that is present between two parallel channels (New Waterway and Caland Canal) connecting the North Sea to the Port of Rotterdam. Due to the different hydrodynamic characteristics of the hinterland of both channels, a difference in salinity and water level is present between both ends of the bypass. As a result, a lateral inflow of water into the New Waterway occurs at the same moment that the flood velocities transport saline water landwards. The lateral inflow of water into this channel has no momentum in the landward direction and therefore decreases the landward flow velocity and therewith the salt water intrusion. In addition, the inflow drives a vertical circulation that mixes the water column close to the bypass. Similar to the bubble screens mentioned above, this vertical mixing of the salt wedge reduces the landward directed salt transport. The flow through the bypass can be manipulated by changing the flow area or the number of bypasses. The effect on the currents and salt transport in the main channel depends on the bypass-configuration and can therefore be optimised (by e.g. a numerical study).

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...

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...

A new code for automatic detection and analysis of the lineament patterns for geophysical and geological purposes (ADALGEO)

NASA Astrophysics Data System (ADS)

Soto-Pinto, C.; Arellano-Baeza, A.; Sánchez, G.

2013-08-01

We present a new numerical method for automatic detection and analysis of changes in lineament patterns caused by seismic and volcanic activities. The method is implemented as a series of modules: (i) normalization of the image contrast, (ii) extraction of small linear features (stripes) through convolution of the part of the image in the vicinity of each pixel with a circular mask or through Canny algorithm, and (iii) posterior detection of main lineaments using the Hough transform. We demonstrate that our code reliably detects changes in the lineament patterns related to the stress evolution in the Earth's crust: specifically, a significant number of new lineaments appear approximately one month before an earthquake, while one month after the earthquake the lineament configuration returns to its initial state. Application of our software to the deformations caused by volcanic activity yields the opposite results: the number of lineaments decreases with the onset of microseismicity. This discrepancy can be explained assuming that the plate tectonic earthquakes are caused by the compression and accumulation of stress in the Earth's crust due to subduction of tectonic plates, whereas in the case of volcanic activity we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion and the resulting stretching of the surface.

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

An improved real time image detection system for elephant intrusion along the forest border areas.

PubMed

Sugumar, S J; Jayaparvathy, R

2014-01-01

Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

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.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

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...

Experimental saltwater intrusion in coastal aquifers using automated image analysis: Applications to homogeneous aquifers

NASA Astrophysics Data System (ADS)

Robinson, G.; Ahmed, Ashraf A.; Hamill, G. A.

2016-07-01

This paper presents the applications of a novel methodology to quantify saltwater intrusion parameters in laboratory-scale experiments. The methodology uses an automated image analysis procedure, minimising manual inputs and the subsequent systematic errors that can be introduced. This allowed the quantification of the width of the mixing zone which is difficult to measure in experimental methods that are based on visual observations. Glass beads of different grain sizes were tested for both steady-state and transient conditions. The transient results showed good correlation between experimental and numerical intrusion rates. The experimental intrusion rates revealed that the saltwater wedge reached a steady state condition sooner while receding than advancing. The hydrodynamics of the experimental mixing zone exhibited similar traits; a greater increase in the width of the mixing zone was observed in the receding saltwater wedge, which indicates faster fluid velocities and higher dispersion. The angle of intrusion analysis revealed the formation of a volume of diluted saltwater at the toe position when the saltwater wedge is prompted to recede. In addition, results of different physical repeats of the experiment produced an average coefficient of variation less than 0.18 of the measured toe length and width of the mixing zone.

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.

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.

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/

Semianalytical solutions for contaminant transport under variable velocity field in a coastal aquifer

NASA Astrophysics Data System (ADS)

Koohbor, Behshad; Fahs, Marwan; Ataie-Ashtiani, Behzad; Simmons, Craig T.; Younes, Anis

2018-05-01

Existing closed-form solutions of contaminant transport problems are limited by the mathematically convenient assumption of uniform flow. These solutions cannot be used to investigate contaminant transport in coastal aquifers where seawater intrusion induces a variable velocity field. An adaptation of the Fourier-Galerkin method is introduced to obtain semi-analytical solutions for contaminant transport in a confined coastal aquifer in which the saltwater wedge is in equilibrium with a freshwater discharge flow. Two scenarios dealing with contaminant leakage from the aquifer top surface and contaminant migration from a source at the landward boundary are considered. Robust implementation of the Fourier-Galerkin method is developed to efficiently solve the coupled flow, salt and contaminant transport equations. Various illustrative examples are generated and the semi-analytical solutions are compared against an in-house numerical code. The Fourier series are used to evaluate relevant metrics characterizing contaminant transport such as the discharge flux to the sea, amount of contaminant persisting in the groundwater and solute flux from the source. These metrics represent quantitative data for numerical code validation and are relevant to understand the effect of seawater intrusion on contaminant transport. It is observed that, for the surface contamination scenario, seawater intrusion limits the spread of the contaminant but intensifies the contaminant discharge to the sea. For the landward contamination scenario, moderate seawater intrusion affects only the spatial distribution of the contaminant plume while extreme seawater intrusion can increase the contaminant discharge to the sea. The developed semi-analytical solution presents an efficient tool for the verification of numerical models. It provides a clear interpretation of the contaminant transport processes in coastal aquifers subject to seawater intrusion. For practical usage in further studies, the full open source semi-analytical codes are made available at the website https://lhyges.unistra.fr/FAHS-Marwan.

New trends in logic synthesis for both digital designing and data processing

NASA Astrophysics Data System (ADS)

Borowik, Grzegorz; Łuba, Tadeusz; Poźniak, Krzysztof

2016-09-01

FPGA devices are equipped with memory-based structures. These memories act as very large logic cells where the number of inputs equals the number of address lines. At the same time, there is a huge demand in the market of Internet of Things for devices implementing virtual routers, intrusion detection systems, etc.; where such memories are crucial for realizing pattern matching circuits, IP address tables, and other. Unfortunately, existing CAD tools are not well suited to utilize capabilities that such large memory blocks offer due to the lack of appropriate synthesis procedures. This paper presents methods which are useful for memory-based implementations: minimization of the number of input variables and functional decomposition.

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

Suitability of optical, physical and chemical measurements for detection of changes in bacterial drinking water quality.

PubMed

Ikonen, Jenni; Pitkänen, Tarja; Miettinen, Ilkka T

2013-10-25

In this study, different optical, physical and chemical measurements were tested for their capacity to detect changes in water quality. The tests included UV-absorbance at 254 nm, absorbance at 420 nm, turbidity, particle counting, temperature, pH, electric conductivity (EC), free chlorine concentration and ATP concentration measurements. Special emphasis was given to investigating the potential for measurement tools to detect changes in bacterial concentrations in drinking water. Bacterial colony counts (CFU) and total bacterial cell counts (TBC) were used as reference methods for assessing the bacterial water quality. The study consists of a series of laboratory scale experiments: monitoring of regrowth of Pseudomonas fluorescens, estimation of the detection limits for optical measurements using Escherichia coli dilutions, verification of the relationships by analysing grab water samples from various distribution systems and utilisation of the measurements in the case of an accidentally contaminated distribution network. We found significant correlations between the tested measurements and the bacterial water quality. As the bacterial contamination of water often co-occurs with the intrusion of matrixes containing mainly non-bacterial components, the tested measurement tools can be considered to have the potential to rapidly detect any major changes in drinking water quality.

Suitability of Optical, Physical and Chemical Measurements for Detection of Changes in Bacterial Drinking Water Quality

PubMed Central

Ikonen, Jenni; Pitkänen, Tarja; Miettinen, Ilkka T.

2013-01-01

In this study, different optical, physical and chemical measurements were tested for their capacity to detect changes in water quality. The tests included UV-absorbance at 254 nm, absorbance at 420 nm, turbidity, particle counting, temperature, pH, electric conductivity (EC), free chlorine concentration and ATP concentration measurements. Special emphasis was given to investigating the potential for measurement tools to detect changes in bacterial concentrations in drinking water. Bacterial colony counts (CFU) and total bacterial cell counts (TBC) were used as reference methods for assessing the bacterial water quality. The study consists of a series of laboratory scale experiments: monitoring of regrowth of Pseudomonas fluorescens, estimation of the detection limits for optical measurements using Escherichia coli dilutions, verification of the relationships by analysing grab water samples from various distribution systems and utilisation of the measurements in the case of an accidentally contaminated distribution network. We found significant correlations between the tested measurements and the bacterial water quality. As the bacterial contamination of water often co-occurs with the intrusion of matrixes containing mainly non-bacterial components, the tested measurement tools can be considered to have the potential to rapidly detect any major changes in drinking water quality. PMID:24284353

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.

How significant is the slope of the sea-side boundary for modelling seawater intrusion in coastal aquifers?

NASA Astrophysics Data System (ADS)

Walther, Marc; Graf, Thomas; Kolditz, Olaf; Liedl, Rudolf; Post, Vincent

2017-08-01

Application of numerical models is a common method to assess groundwater resources. The versatility of these models allows consideration of different levels of complexity, but the accuracy of the outcomes hinges upon a proper description of the system behaviour. In seawater intrusion assessment, the implementation of the sea-side boundary condition is of particular importance. We evaluate the influence of the slope of the sea-side boundary on the simulation results of seawater intrusion in a freshwater aquifer by employing a series of slope variations together with a sensitivity analysis by varying additional sensitive parameters (freshwater inflow and longitudinal and transverse dispersivities). Model results reveal a multi-dimensional dependence of the investigated variables with an increasing relevance of the sea-side boundary slope for seawater intrusion (decrease of up to 32%), submarine groundwater discharge zone (reduction of up to 55%), and turnover times (increase of up to 730%) with increasing freshwater inflow or dispersivity values.

Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

NASA Astrophysics Data System (ADS)

Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

2018-04-01

To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

Doping-assisted low-pressure photoionization mass spectrometry for the real-time detection of lung cancer-related volatile organic compounds.

PubMed

Li, Zhen; Xu, Ce; Shu, Jinian; Yang, Bo; Zou, Yao

2017-04-01

Real-time detection of lung cancer-related volatile organic compounds (VOCs) is a promising, non-intrusive technique for lung cancer (LC) prescreening. In this study, a novel method was designed to enhance the detection selectivity and sensitivity of LC-related polar VOCs by dichloromethane (CH 2 Cl 2 ) doping-assisted low-pressure photoionization mass spectrometry (LPPI-MS). Compared with conventional LPPI-MS, CH 2 Cl 2 doping-assisted LPPI-MS boosted the peak intensities of n-propanol, n-pentanal, acetone, and butyl acetate in nitrogen specifically by 53, 18, 16, and 43 times, respectively. The signal intensities of their daughter ions were inhibited or reduced. At relative humidity (RH) of 20%, the sensitivities of n-propanol, n-pentanal, acetone, and butyl acetate detection ranged from 116 to 452 counts/ppbv with a detection time of 10s and R 2 >0.99 for the linear calibration curves. The method was also applicable under higher RH levels of 50% and 90%. Breath samples obtained from 10 volunteers and spiked samples were investigated. Eight-fold enhancements in the signal intensities of polar VOCs were observed in the normal and spiked samples. These preliminary results demonstrate the efficacy of the dichloromethane doping-assisted LPPI technique for the detection of LC-related polar VOCs. Further studies are indispensible to illustrating the detailed mechanism and applying the technique to breath diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance.

PubMed

Farkhatdinov, Ildar; Roehri, Nicolas; Burdet, Etienne

2017-09-26

Many wearable lower-limb robots for walking assistance have been developed in recent years. However, it remains unclear how they can be commanded in an intuitive and efficient way by their user. In particular, providing robotic assistance to neurologically impaired individuals in turning remains a significant challenge. The control should be safe to the users and their environment, yet yield sufficient performance and enable natural human-machine interaction. Here, we propose using the head and trunk anticipatory behaviour in order to detect the intention to turn in a natural, non-intrusive way, and use it for triggering turning movement in a robot for walking assistance. We therefore study head and trunk orientation during locomotion of healthy adults, and investigate upper body anticipatory behaviour during turning. The collected walking and turning kinematics data are clustered using the k-means algorithm and cross-validation tests and k-nearest neighbours method are used to evaluate the performance of turning detection during locomotion. Tests with seven subjects exhibited accurate turning detection. Head anticipated turning by more than 400-500 ms in average across all subjects. Overall, the proposed method detected turning 300 ms after its initiation and 1230 ms before the turning movement was completed. Using head anticipatory behaviour enabled to detect turning faster by about 100 ms, compared to turning detection using only pelvis orientation measurements. Finally, it was demonstrated that the proposed turning detection can improve the quality of human-robot interaction by improving the control accuracy and transparency.

Method and Apparatus for Measuring Fluid Flow

NASA Technical Reports Server (NTRS)

Arndt, G. Dickey (Inventor); Nguyen, Thanh X. (Inventor); Carl, James R. (Inventor)

1997-01-01

Method and apparatus for making measurements on fluids related to their complex permeability are disclosed. A microwave probe is provided for exposure to the fluids. The probe can be non-intrusive or can also be positioned at the location where measurements are to be made. The impedance of the probe is determined. in part. by the complex dielectric constant of the fluids at the probe. A radio frequency signal is transmitted to the probe and the reflected signal is phase and amplitude detected at a rapid rate for the purpose of identifying the fluids. Multiple probes may be selectively positioned to monitor the behavior of the fluids including their flow rate. Fluids may be identified as between two or more different fluids as well as multiple phases of the same fluid based on differences between their complex permittivities.

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

Tetris and Word games lead to fewer intrusive memories when applied several days after analogue trauma.

PubMed

Hagenaars, Muriel A; Holmes, Emily A; Klaassen, Fayette; Elzinga, Bernet

2017-01-01

Background : Intrusive trauma memories are a key symptom of posttraumatic stress disorder (PTSD), so disrupting their recurrence is highly important. Intrusion development was hindered by visuospatial interventions administered up to 24 hours after analogue trauma. It is unknown whether interventions can be applied later, and whether modality or working-memory load are crucial factors. Objectives : This study tested: (1) whether a visuospatial task would lead to fewer intrusions compared to a reactivation-only group when applied after memory reactivation four days after analogue trauma exposure (extended replication), (2) whether both tasks (i.e. one aimed to be visuospatial, one more verbal) would lead to fewer intrusions than the reactivation-only group (intervention effect), and (3) whether supposed task modality (visuospatial or verbal) is a critical component (modality effect). Method : Fifty-four participants were randomly assigned to reactivation+Tetris (visuospatial), reactivation+Word games (verbal), or reactivation-only (no task). They watched an aversive film (day 0) and recorded intrusive memories of the film in diary A. On day 4, memory was reactivated, after which participants played Tetris, Word games, or had no task for 10 minutes. They then kept a second diary (B). Informative hypotheses were evaluated using Bayes factors. Results : Reactivation+Tetris and reactivation+Word games resulted in relatively fewer intrusions from the last day of diary A to the first day of diary B than reactivation-only (objective 1 and 2). Thus, both tasks were effective even when applied days after analogue trauma. Reactivation-only was not effective. Reactivation+Word games appeared to result in fewer intrusions than reactivation+Tetris (objective 3; modality effect), but this evidence was weak. Explorative analyses showed that Word games were more difficult than Tetris. Conclusions : Applying a task four days after the trauma film (during memory reconsolidation) was effective. The modality versus working-memory load issue is inconclusive.

Quantification of the Intrusion Process at Kïlauea Volcano, Hawai'I

NASA Astrophysics Data System (ADS)

Wright, T. L.; Marsh, B. D.

2014-12-01

Knowing the time between initial intrusion and later eruption of a given volume of differentiated magma is key to evaluating the connections among magma transport and emplacement, solidification and differentiation, and melt extraction and eruption. Cooling rates for two Kïlauea lava lakes as well as known parent composition and residence times for intrusions that resulted in fractionated lavas later erupted on the East Rift Zone in 1955 (34 years) and 1977 (22 years) allow intrusion dimensions to be calculated. We model intrusions beneath Kïlauea's East Rift Zone near their point of separation from the magma transport path at ~ 5 km depth using Jaeger's (1957) method calibrated against Alae and Makaopuhi lava lakes with wallrock temperatures above the curie point at 450-550°C. Minimum thicknesses of 50-70 meters are found for intrusions that fed the two fractionated lavas, as well as for long-lived magma bodies identified from geodetic monitoring during many East Rift eruptions. These intrusions began as dikes, but probably became sills or laccolithic bodies that remained near the transport path. Short-lived intrusions also arrested near the magma transport path, but that retain a dike geometry, are hypothesized to serve as a trigger for the small but discrete increments of seaward movement on Kïlauea's south flank that characterize slow-slip earthquakes. Two additional thoughts arise from the quantitative modeling of magma cooling. First, long-term heating of the wallrock surrounding the horizontal East Rift Zone transport path slows the rate of cooling within the conduit, possibly contributing to the longevity of the East Rift eruption that began in 1983. Second, the combined effects of heating of the wall rock and ever-increasing magma supply rate from the mantle may have forced breakdown and widening of the vertical transport conduit, which could explain the 5-15-km deep long-period earthquake swarms beneath Kīlauea's summit between 1987 and 1992.

Preliminary evaluation of solution-mining intrusion into a salt-dome repository

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

Not Available

1981-06-01

This report is the product of the work of an ONWI task force to evaluate inadvertant human intrusion into a salt dome repository by solution mining. It summarizes the work in the following areas: a general review of the levels of defense that could reduce both the likelihood and potential consequences of human intrusion into a salt dome repository; evaluation of a hypothetical intrusion scenario and its consequences; recommendation for further studies. The conclusions of this task force report can be summarized as follows: (1) it is not possible at present to establish with certainty that solution mining is crediblemore » as a human-intrusion event. The likelihood of such an intrusion will depend on the effectiveness of the preventive measures; (2) an example analysis based on the realistic approach is presented in this report; it concluded that the radiological consequences are strongly dependent upon the mode of radionuclide release from the waste form, time after emplacement, package design, impurities in the host salt, the amount of a repository intercepted, the solution mining cavity form, the length of time over which solution mining occurs, the proportion of contaminated salt source for human consumption compared to other sources, and the method of salt purification for culinary purposes; (3) worst case scenarios done by other studies suggest considerable potential for exposures to man while preliminary evaluations of more realistic cases suggest significantly reduced potential consequences. Mathematical model applications to process systems, guided by more advanced assumptions about human intrusion into geomedia, will shed more light on the potential for concerns and the degree to which mitigative measures will be required.« less

Overhead spine arch analysis of dairy cows from three-dimensional video

NASA Astrophysics Data System (ADS)

Abdul Jabbar, K.; Hansen, M. F.; Smith, M. L.; Smith, L. N.

2017-02-01

We present a spine arch analysis method in dairy cows using overhead 3D video data. This method is aimed for early stage lameness detection. That is important in order to allow early treatment; and thus, reduce the animal suffering and minimize the high forecasted financial losses, caused by lameness. Our physical data collection setup is non-intrusive, covert and designed to allow full automation; therefore, it could be implemented on a large scale or daily basis with high accuracy. We track the animal's spine using shape index and curvedness measure from the 3D surface as she walks freely under the 3D camera. Our spinal analysis focuses on the thoracic vertebrae region, where we found most of the arching caused by lameness. A cubic polynomial is fitted to analyze the arch and estimate the locomotion soundness. We have found more accurate results by eliminating the regular neck/head movements' effect from the arch. Using 22-cow data set, we are able to achieve an early stage lameness detection accuracy of 95.4%.

“SmartMonitor” — An Intelligent Security System for the Protection of Individuals and Small Properties with the Possibility of Home Automation

PubMed Central

Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław

2014-01-01

“SmartMonitor” is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the “SmartMonitor” system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons. PMID:24905854

Validation of the Portuguese self-administered computerised 24-hour dietary recall among second-, third- and fourth-grade children.

PubMed

Carvalho, M A; Baranowski, T; Foster, E; Santos, O; Cardoso, B; Rito, A; Pereira Miguel, J

2015-12-01

Current methods for assessing children's dietary intake, such as interviewer-administered 24-h dietary recall (24-h DR), are time consuming and resource intensive. Self-administered instruments offer a low-cost diet assessment method for use with children. The present study assessed the validity of the Portuguese self-administered, computerised, 24-h DR (PAC24) against the observation of school lunch. Forty-one, 7-10-year-old children from two elementary schools, in Lisbon, were observed during school lunch followed by completion of the PAC24 the next day. Accuracy for reporting items was measured in terms of matches, intrusions and omissions; accuracy for reporting amounts was measured in terms of arithmetic and absolute differences for matches and amounts for omissions and intrusions; and accuracy for reporting items and amounts combined was measured in terms of total inaccuracy. The ratio of the estimated weight of food consumed with the actual weight consumed was calculated along with the limits of agreement using the method of Bland and Altman. Comparison of PAC24 against observations at the food level resulted in values of 67.0% for matches, 11.5% for intrusions and 21.5% for omissions. The mean for total inaccuracy was 3.44 servings. For amounts, accuracy was high for matches (-0.17 and 0.23 servings for arithmetic and absolute differences, respectively) and lower for omissions (0.61 servings) and intrusions (0.55 servings). PAC24 was found to under-estimate the weight of food on average by 32% of actual intake. PAC24 is a lower-burden procedure for both respondents and researchers and, with slight modification, comprises a promising method for assessing diet among children. © 2014 The British Dietetic Association Ltd.

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.

Detection of concealed cars in complex cargo X-ray imagery using Deep Learning.

PubMed

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

2017-01-01

Non-intrusive inspection systems based on X-ray radiography techniques are routinely used at transport hubs to ensure the conformity of cargo content with the supplied shipping manifest. As trade volumes increase and regulations become more stringent, manual inspection by trained operators is less and less viable due to low throughput. Machine vision techniques can assist operators in their task by automating parts of the inspection workflow. Since cars are routinely involved in trafficking, export fraud, and tax evasion schemes, they represent an attractive target for automated detection and flagging for subsequent inspection by operators. Development and evaluation of a novel method for the automated detection of cars in complex X-ray cargo imagery. X-ray cargo images from a stream-of-commerce dataset were classified using a window-based scheme. The limited number of car images was addressed by using an oversampling scheme. Different Convolutional Neural Network (CNN) architectures were compared with well-established bag of words approaches. In addition, robustness to concealment was evaluated by projection of objects into car images. CNN approaches outperformed all other methods evaluated, achieving 100% car image classification rate for a false positive rate of 1-in-454. Cars that were partially or completely obscured by other goods, a modus operandi frequently adopted by criminals, were correctly detected. We believe that this level of performance suggests that the method is suitable for deployment in the field. It is expected that the generic object detection workflow described can be extended to other object classes given the availability of suitable training data.

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.

Predictive uncertainty analysis of a saltwater intrusion model using null-space Monte Carlo

USGS Publications Warehouse

Herckenrath, Daan; Langevin, Christian D.; Doherty, John

2011-01-01

Because of the extensive computational burden and perhaps a lack of awareness of existing methods, rigorous uncertainty analyses are rarely conducted for variable-density flow and transport models. For this reason, a recently developed null-space Monte Carlo (NSMC) method for quantifying prediction uncertainty was tested for a synthetic saltwater intrusion model patterned after the Henry problem. Saltwater intrusion caused by a reduction in fresh groundwater discharge was simulated for 1000 randomly generated hydraulic conductivity distributions, representing a mildly heterogeneous aquifer. From these 1000 simulations, the hydraulic conductivity distribution giving rise to the most extreme case of saltwater intrusion was selected and was assumed to represent the "true" system. Head and salinity values from this true model were then extracted and used as observations for subsequent model calibration. Random noise was added to the observations to approximate realistic field conditions. The NSMC method was used to calculate 1000 calibration-constrained parameter fields. If the dimensionality of the solution space was set appropriately, the estimated uncertainty range from the NSMC analysis encompassed the truth. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. Reducing the dimensionality of the null-space for the processing of the random parameter sets did not result in any significant gains in efficiency and compromised the ability of the NSMC method to encompass the true prediction value. The addition of intrapilot point heterogeneity to the NSMC process was also tested. According to a variogram comparison, this provided the same scale of heterogeneity that was used to generate the truth. However, incorporation of intrapilot point variability did not make a noticeable difference to the uncertainty of the prediction. With this higher level of heterogeneity, however, the computational burden of generating calibration-constrained parameter fields approximately doubled. Predictive uncertainty variance computed through the NSMC method was compared with that computed through linear analysis. The results were in good agreement, with the NSMC method estimate showing a slightly smaller range of prediction uncertainty than was calculated by the linear method. Copyright 2011 by the American Geophysical Union.

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.

Electrical resistivity tomography to quantify in situ liquid content in a full-scale dry anaerobic digestion reactor.

PubMed

André, L; Lamy, E; Lutz, P; Pernier, M; Lespinard, O; Pauss, A; Ribeiro, T

2016-02-01

The electrical resistivity tomography (ERT) method is a non-intrusive method widely used in landfills to detect and locate liquid content. An experimental set-up was performed on a dry batch anaerobic digestion reactor to investigate liquid repartition in process and to map spatial distribution of inoculum. Two array electrodes were used: pole-dipole and gradient arrays. A technical adaptation of ERT method was necessary. Measured resistivity data were inverted and modeled by RES2DINV software to get resistivity sections. Continuous calibration along resistivity section was necessary to understand data involving sampling and physicochemical analysis. Samples were analyzed performing both biochemical methane potential and fiber quantification. Correlations were established between the protocol of reactor preparation, resistivity values, liquid content, methane potential and fiber content representing liquid repartition, high methane potential zones and degradations zones. ERT method showed a strong relevance to monitor and to optimize the dry batch anaerobic digestion process. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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

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

Hierarchical Kohonenen net for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A; Huff, Julie

2005-04-01

A novel multilevel hierarchical Kohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data set in detecting anomalies. Randomly selected subsets that contain both attacks and normal records from the KDD Cup 1999 benchmark data are used to train the hierarchical net. We use a confidence measure to label the clusters. Then we use the test set from the same KDD Cup 1999 benchmark to test the hierarchical net. We show that a hierarchical K-Map in which each layer operates on a small subset of the feature space is superior to a single-layer K-Map operating on the whole feature space in detecting a variety of attacks in terms of detection rate as well as false positive rate.

Applications of electromagnetic principles in the design and development of proximity wireless sensors

NASA Astrophysics Data System (ADS)

Alam, Md Nazmul

Sensors and sensing system are playing dominant roles in monitoring the health of infrastructure, such as bridges, power lines, gas pipelines, rail roads etc. Sensing modalities employing Surface Acoustic Waves (SAW), Electromagnetic (EM) and optical have been investigated and reported. Sensors that utilize the perturbation of EM fields as function of the change in the physical structural or material phenomenon are of particular interest because of their inherent synergy with electronic system and diagnostic techniques, e.g. Time Domain Reflectometry (TDR), Joint-Time-Frequency-Domain-Reflectometry (JTFDR). The focus of this work is to study and develop new sensing and monitoring concepts that are based on EM principles. First, the analyses, design and development of a static electric field type sensor are presented for application in embedded concrete moisture content measurement. The analytical formulation and results based on conformal mapping method for an interdigitated sensor clearly show the dependency of the field penetration depth and the inter-electrode capacitance on the electrode sizes and their spacings. It is observed that larger electrode size and small separation are needed in order to achieve substantially higher capacitance or large field penetration depth. A meander and a circular sensor are fabricated and tested to demonstrate concrete moisture content measurements that show that moisture content is a linear function of sensor interelectrode capacitance. Second, sub-wavelength dimension non-intrusive wave launchers are designed and tested that can launch TDR or JTFDR type broadband surface wave waveforms in the VHF-UHF bands in order to detect cable faults. Greater than 3:1 transmission bandwidth (100-300 MHz) is obtained with a cylindrical launcher on square orthogonal ground plane while with a CSW launcher more than an octave (100-240 MHz) bandwidth is achieved. Open circuit faults are detected using surface waves and TDR on two XLPE cables. Third, a new mathematical method is developed that can be used to determine the changes in the dielectric constant of a cable insulating material. By comparing the experimental JTFDR waveform signatures from a new and an aged cable, it is demonstrated that the change in the average dielectric constant of the insulation material can be estimated from the phase transfer functions obtained from the FFT of measured magnitude and phase responses. The experimental data obtained for two types of cables, XLPE and EPR show that the dielectric constant decreases with accelerated aging. Finally, JTFDR surface wave sensing method is developed and applied to determine the locations of aging related insulation damage in power cables. The comparative power spectral responses of conducted and non-intrusive surface wave JTFDR waveforms clearly show the resulting bandwidth reduction in the latter primarily because of the reflective nature of the coupling. It is demonstrated that with the help of a non-intrusive wave launcher and a 120 MHz Gaussian chirp waveform the location of aging related insulation damages can be detected. Experiments conducted show the cross-correlation peaks at subsequent aging intervals as the cable is aged inside a heat chamber.

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...

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...

Cyber Surveillance for Flood Disasters

PubMed Central

Lo, Shi-Wei; Wu, Jyh-Horng; Lin, Fang-Pang; Hsu, Ching-Han

2015-01-01

Regional heavy rainfall is usually caused by the influence of extreme weather conditions. Instant heavy rainfall often results in the flooding of rivers and the neighboring low-lying areas, which is responsible for a large number of casualties and considerable property loss. The existing precipitation forecast systems mostly focus on the analysis and forecast of large-scale areas but do not provide precise instant automatic monitoring and alert feedback for individual river areas and sections. Therefore, in this paper, we propose an easy method to automatically monitor the flood object of a specific area, based on the currently widely used remote cyber surveillance systems and image processing methods, in order to obtain instant flooding and waterlogging event feedback. The intrusion detection mode of these surveillance systems is used in this study, wherein a flood is considered a possible invasion object. Through the detection and verification of flood objects, automatic flood risk-level monitoring of specific individual river segments, as well as the automatic urban inundation detection, has become possible. The proposed method can better meet the practical needs of disaster prevention than the method of large-area forecasting. It also has several other advantages, such as flexibility in location selection, no requirement of a standard water-level ruler, and a relatively large field of view, when compared with the traditional water-level measurements using video screens. The results can offer prompt reference for appropriate disaster warning actions in small areas, making them more accurate and effective. PMID:25621609

A Novel Method to Detect Early Colorectal Cancer Based on Chromosome Copy Number Variation in Plasma.

PubMed

Xu, Jun-Feng; Kang, Qian; Ma, Xing-Yong; Pan, Yuan-Ming; Yang, Lang; Jin, Peng; Wang, Xin; Li, Chen-Guang; Chen, Xiao-Chen; Wu, Chao; Jiao, Shao-Zhuo; Sheng, Jian-Qiu

2018-01-01

Colonoscopy screening has been accepted broadly to evaluate the risk and incidence of colorectal cancer (CRC) during health examination in outpatients. However, the intrusiveness, complexity and discomfort of colonoscopy may limit its application and the compliance of patients. Thus, more reliable and convenient diagnostic methods are necessary for CRC screening. Genome instability, especially copy-number variation (CNV), is a hallmark of cancer and has been proved to have potential in clinical application. We determined the diagnostic potential of chromosomal CNV at the arm level by whole-genome sequencing of CRC plasma samples (n = 32) and healthy controls (n = 38). Arm level CNV was determined and the consistence of arm-level CNV between plasma and tissue was further analyzed. Two methods including regular z score and trained Support Vector Machine (SVM) classifier were applied for detection of colorectal cancer. In plasma samples of CRC patients, the most frequent deletions were detected on chromosomes 6, 8p, 14q and 1p, and the most frequent amplifications occurred on chromosome 19, 5, 2, 9p and 20p. These arm-level alterations detected in plasma were also observed in tumor tissues. We showed that the specificity of regular z score analysis for the detection of colorectal cancer was 86.8% (33/38), whereas its sensitivity was only 56.3% (18/32). Applying a trained SVM classifier (n = 40 in trained group) as the standard to detect colorectal cancer relevance ratio in the test samples (n = 30), a sensitivity of 91.7% (11/12) and a specificity 88.9% (16/18) were finally reached. Furthermore, all five early CRC patients in stages I and II were successfully detected. Trained SVM classifier based on arm-level CNVs can be used as a promising method to screen early-stage CRC. © 2018 The Author(s). Published by S. Karger AG, Basel.

Non-intrusive refrigerant charge indicator

DOEpatents

Mei, Viung C.; Chen, Fang C.; Kweller, Esher

2005-03-22

A non-intrusive refrigerant charge level indicator includes a structure for measuring at least one temperature at an outside surface of a two-phase refrigerant line section. The measured temperature can be used to determine the refrigerant charge status of an HVAC system, and can be converted to a pressure of the refrigerant in the line section and compared to a recommended pressure range to determine whether the system is under-charged, properly charged or over-charged. A non-intrusive method for assessing the refrigerant charge level in a system containing a refrigerant fluid includes the step of measuring a temperature at least one outside surface of a two-phase region of a refrigerant containing refrigerant line, wherein the temperature measured can be converted to a refrigerant pressure within the line section.

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.

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.

The effects of alveolar bone loss and miniscrew position on initial tooth displacement during intrusion of the maxillary anterior teeth: Finite element analysis

PubMed Central

Cho, Sun-Mi; Choi, Sung-Hwan; Sung, Sang-Jin; Yu, Hyung-Seog

2016-01-01

Objective The aim of this study was to determine the optimal loading conditions for pure intrusion of the six maxillary anterior teeth with miniscrews according to alveolar bone loss. Methods A three-dimensional finite element model was created for a segment of the six anterior teeth, and the positions of the miniscrews and hooks were varied after setting the alveolar bone loss to 0, 2, or 4 mm. Under 100 g of intrusive force, initial displacement of the individual teeth in three directions and the degree of labial tilting were measured. Results The degree of labial tilting increased with reduced alveolar bone height under the same load. When a miniscrew was inserted between the two central incisors, the amounts of medial-lateral and anterior-posterior displacement of the central incisor were significantly greater than in the other conditions. When the miniscrews were inserted distally to the canines and an intrusion force was applied distal to the lateral incisors, the degree of labial tilting and the amounts of displacement of the six anterior teeth were the lowest, and the maximum von Mises stress was distributed evenly across all the teeth, regardless of the bone loss. Conclusions Initial tooth displacement similar to pure intrusion of the six maxillary anterior teeth was induced when miniscrews were inserted distal to the maxillary canines and an intrusion force was applied distal to the lateral incisors. In this condition, the maximum von Mises stresses were relatively evenly distributed across all the teeth, regardless of the bone loss. PMID:27668194

Beta-blockers May Reduce Intrusive Thoughts in Newly Diagnosed Cancer Patients

PubMed Central

Lindgren, Monica E.; Fagundes, Christopher P.; Alfano, Catherine M.; Povoski, Stephen P.; Agnese, Doreen M.; Arnold, Mark W.; Farrar, William B.; Yee, Lisa D.; Carson, William E.; Schmidt, Carl R.; Kiecolt-Glaser, Janice K.

2012-01-01

Objective A cancer diagnosis provokes significant levels of emotional distress, with intrusive thoughts being the most common manifestation among breast cancer survivors. Cancer-related intrusive thoughts can take the form of emotional memories, flashbacks, nightmares, and intrusive images. Emotional arousal after a severe life stressor prolongs adrenergic activation, which in turn may increase risk for posttraumatic symptomatology. However, antihypertensive beta-blockers block adrenergic activation and are known to reduce traumatic memories and related psychological distress. Thus, the current study examined the association between beta-blocker use and the severity of cancer-related intrusive thoughts and related symptoms following a cancer diagnosis. Methods The 174 breast and 36 female colorectal cancer patients who had recently undergone diagnostic screening or biopsy included 39 beta-blocker users and 171 non-users. Prior to any cancer treatment including surgery, participants completed questionnaires that included the Impact of Events Scale (IES) and the Center for Epidemiological Studies Depression Scale (CES-D). Analyses controlled for age, education, cancer stage, cancer type, days since diagnosis, marital status, depression, and comorbidities. Results Although the high rates of cancer-related distress in this sample were similar to those of other studies with recently diagnosed patients, beta-blocker users endorsed 32% fewer cancer-related intrusive thoughts than non-users. Conclusions Recently diagnosed cancer patients using beta-blockers reported less cancer-related psychological distress. These results suggest that beta-blocker use may benefit cancer patients’ psychological adjustment following diagnosis, and provide a promising direction for future investigations on the pharmacological benefits of beta-blockers for cancer-related distress. PMID:23255459

A new physical barrier system for seawater intrusion control

NASA Astrophysics Data System (ADS)

Abdoulhalik, Antoifi; Ahmed, Ashraf; Hamill, G. A.

2017-06-01

The construction of subsurface physical barriers is one of various methods used to control seawater intrusion (SWI) in coastal aquifers. This study proposes the mixed physical barrier (MPB) as a new barrier system for seawater intrusion control, which combines an impermeable cutoff wall and a semi-permeable subsurface dam. The effect of the traditionally-used physical barriers on transient saltwater wedge dynamics was first explored for various hydraulic gradients, and the workability of the MPB was thereafter thoroughly analysed. A newly developed automated image analysis based on light-concentration conversion was used in the experiments, which were completed in a porous media tank. The numerical code SEAWAT was used to assess the consistency of the experimental data and examine the sensitivity of the performance of the barriers to various key parameters. The results show that the MPB induced a visible lifting of the dense saline flux upward towards the outlet by the light freshwater. This saltwater lifting mechanism, observed for the first time, induced significant reduction to the saline water intrusion length. The use of the MPB yielded up to 62% and 42% more reduction of the saltwater intrusion length than the semi-permeable dam and the cutoff wall, respectively. The performance achieved by the MPB with a wall depth of 40% of the aquifer thickness was greater than that of a single cutoff wall with a penetration depth of 90% of the aquifer thickness (about 13% extra reduction). This means that the MPB could produce better seawater intrusion reduction than the traditionally used barriers at even lower cost.

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

Identification of saline water intrusion in part of Cauvery deltaic region, Tamil Nadu, Southern India: using GIS and VES methods

NASA Astrophysics Data System (ADS)

Gnanachandrasamy, G.; Ramkumar, T.; Venkatramanan, S.; Chung, S. Y.; Vasudevan, S.

2016-06-01

We use electrical resistivity data arrayed in a 2715 km2 region with 30 locations to identify the saline water intrusion zone in part of Cauvery deltaic region, offshore Eastern India. From this dataset we are able to derive information on groundwater quality, thickness of aquifer zone, structural and stratigraphic conditions relevant to groundwater conditions, and permeability of aquifer systems. A total of 30 vertical electrode soundings (VES) were carried out by Schlumberger electrode arrangement to indicate complete lithology of this region using curve matching techniques. The electrical soundings exhibited that H and HK type curves were suitable for 16 shallow locations, and QH, KQ, K, KH, QQ, and HA curves were fit for other location. Low resistivity values suggested that saline water intrusion occurred in this region. According to final GIS map, most of the region was severely affected by seawater intrusion due to the use of over-exploitation of groundwater.The deteriorated groundwater resources in this coastal region should raise environmental and health concerns.

Sulfide Intrusion and Detoxification in the Seagrass Zostera marina

PubMed Central

Hasler-Sheetal, Harald; Holmer, Marianne

2015-01-01

Gaseous sulfide intrusion into seagrasses growing in sulfidic sediments causes little or no harm to the plant, indicating the presence of an unknown sulfide tolerance or detoxification mechanism. We assessed such mechanism in the seagrass Zostera marina in the laboratory and in the field with scanning electron microscopy coupled to energy dispersive X-ray spectroscopy, chromatographic and spectrophotometric methods, and stable isotope tracing coupled with a mass balance of sulfur compounds. We found that Z. marina detoxified gaseous sediment-derived sulfide through incorporation and that most of the detoxification occurred in underground tissues, where sulfide intrusion was greatest. Elemental sulfur was a major detoxification compound, precipitating on the inner wall of the aerenchyma of underground tissues. Sulfide was metabolized into thiols and entered the plant sulfur metabolism as well as being stored as sulfate throughout the plant. We conclude that avoidance of sulfide exposure by reoxidation of sulfide in the rhizosphere or aerenchyma and tolerance of sulfide intrusion by incorporation of sulfur in the plant are likely major survival strategies of seagrasses in sulfidic sediments. PMID:26030258

Four-dimensional electrical conductivity monitoring of stage-driven river water intrusion: Accounting for water table effects using a transient mesh boundary and conditional inversion constraints

DOE PAGES

Johnson, Tim; Versteeg, Roelof; Thomle, Jon; ...

2015-08-01

Our paper describes and demonstrates two methods of providing a priori information to the surface-based time-lapse three-dimensional electrical resistivity tomography (ERT) problem for monitoring stage-driven or tide-driven surface water intrusion into aquifers. First, a mesh boundary is implemented that conforms to the known location of the water table through time, thereby enabling the inversion to place a sharp bulk conductivity contrast at that boundary without penalty. Moreover, a nonlinear inequality constraint is used to allow only positive or negative transient changes in EC to occur within the saturated zone, dependent on the relative contrast in fluid electrical conductivity between surfacemore » water and groundwater. A 3-D field experiment demonstrates that time-lapse imaging results using traditional smoothness constraints are unable to delineate river water intrusion. The water table and inequality constraints provide the inversion with the additional information necessary to resolve the spatial extent of river water intrusion through time.« less

Four-dimensional electrical conductivity monitoring of stage-driven river water intrusion: Accounting for water table effects using a transient mesh boundary and conditional inversion constraints

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

Johnson, Tim; Versteeg, Roelof; Thomle, Jon

Our paper describes and demonstrates two methods of providing a priori information to the surface-based time-lapse three-dimensional electrical resistivity tomography (ERT) problem for monitoring stage-driven or tide-driven surface water intrusion into aquifers. First, a mesh boundary is implemented that conforms to the known location of the water table through time, thereby enabling the inversion to place a sharp bulk conductivity contrast at that boundary without penalty. Moreover, a nonlinear inequality constraint is used to allow only positive or negative transient changes in EC to occur within the saturated zone, dependent on the relative contrast in fluid electrical conductivity between surfacemore » water and groundwater. A 3-D field experiment demonstrates that time-lapse imaging results using traditional smoothness constraints are unable to delineate river water intrusion. The water table and inequality constraints provide the inversion with the additional information necessary to resolve the spatial extent of river water intrusion through time.« less

Aeromagnetic and radio echo ice-sounding measurements show much greater area of the Dufek intrusion, Antarctica

USGS Publications Warehouse

Behrendt, John C.; Drewry, D.J.; Jankowski, E.; Grim, M.S.

1980-01-01

A combined aeromagnetic and radio echo ice-sounding survey made in 1978 in Antarctica over the Dufek layered mafic intrusion suggests a minimum area of the intrusion of about 50,000 square kilometers, making it comparable in size with the Bushveld Complex of Africa. Comparisons of the magnetic and subglacial topographic profiles illustrate the usefulness of this combination of methods in studying bedrock geology beneath ice-covered areas. Magnetic anomalies range in peak-to-trough amplitude from about 50 nanoteslas over the lowermost exposed portion of the section in the Dufek Massif to about 3600 nanoteslas over the uppermost part of the section in the Forrestal Range. Theoretical magnetic anomalies, computed from a model based on the subice topography fitted to the highest amplitude observed magnetic anomalies, required normal and reversed magnetizations ranging from 10-3 to 10-2 electromagnetic units per cubic centimeter. This result is interpreted as indicating that the Dufek intrusion cooled through the Curie isotherm during one or more reversals of the earth's magnetic field. Copyright ?? 1980 AAAS.

Assessing the impact of sea level rise due to climate change on seawater intrusion in Mekong Delta, Vietnam.

PubMed

Vu, D T; Yamada, T; Ishidaira, H

2018-03-01

In the context of climate change, salinity intrusion into rivers has been, and will be, one of the most important issues for coastal water resources management. A combination of changes, including increased temperature, change in regional rainfall, especially sea level rise (SLR) related to climate change, will have significant impacts on this phenomenon. This paper presents the outcomes of a study conducted in the Mekong Delta of Vietnam (MKD) for evaluating the effect of sea water intrusion under a new SLR scenario. Salinity intrusion was simulated by one-dimensional (1D) modeling. The relative sea level projection was constructed corresponding to the RCP 6.0 emission scenario for MKD based on the statistical downscaling method. The sea level in 2050 is projected to increase from 25 cm to 30 cm compared to the baseline period (in 2000). Furthermore, the simulated results suggested that salinity greater than 4 g/l, which affects rice yield, will intrude up to 50-60 km into the river. Approximately 30,000 ha of agricultural area will be affected if the sea level rise is 30 cm.

Late Vendian Complexes in the Structure of Metamorphic Basement of the Fore Range Zone, Greater Caucasus

NASA Astrophysics Data System (ADS)

Kamzolkin, V. A.; Latyshev, A. V.; Vidyapin, Yu. P.; Somin, M. L.; Smul'skaya, A. I.; Ivanov, S. D.

2018-05-01

The paper presents new data on the composition, age, and relationships (with host and overlying deposits) of intrusive rocks in the basement of the Fore Range zone (Greater Caucasus), in the Malaya Laba River Basin. The evolutionary features of intrusive units located within the Blyb metamorphic complex are described. It is shown for the first time that the lower levels of this complex are, in a structural sense, outcrops of the Late Vendian basement. The basement is composed of the Balkan Formation and a massif of quartz metadiorites that intrudes it; for the rocks of this massif, ages ranging from 549 ± 7.4 to 574.1 ± 6.7 Ma are obtained for three U-Pb datings by the SHRIMP-II method. The Herzyinan magmatic event is represented by a group of granodiorite intrusions penetrating the Blyb complex on a series of faults extending along its boundary with the Main Range zone. The obtained estimate for the U-Pb age of one of the intrusions (319 ± 3.8 Ma) corresponds to the end of the Serpukhovian stage of the Early Carboniferous.

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.

Exploration criteria for low permeability geothermal resources. Final report. [Coso KGRA

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

Norton, D.

1977-10-01

Low permeability geothermal systems related to high temperature plutons in the upper crust were analyzed in order to ascertain those characteristics of these systems which could be detected by surface and shallow subsurface exploration methods. Analyses were designed to integrate data and concepts from the literature, which relate to the transport processes, together with computer simulation of idealized systems. The systems were analyzed by systematically varying input parameters in order to understand their effect on the variables which might be measured in an exploration-assessment program. The methods were applied to a prospective system in its early stages of evaluation. Datamore » from the Coso system were used. The study represents a first-order approximation to transport processes in geothermal systems, which consist of high temperature intrusions, host rock, and fluids. Included in an appendix are operations procedures for interactive graphics programs developed during the study. (MHR)« less

Mandibular canine intrusion with the segmented arch technique: A finite element method study.

PubMed

Caballero, Giselle Milagros; Carvalho Filho, Osvaldo Abadia de; Hargreaves, Bernardo Oliveira; Brito, Hélio Henrique de Araújo; Magalhães Júnior, Pedro Américo Almeida; Oliveira, Dauro Douglas

2015-06-01

Mandibular canines are anatomically extruded in approximately half of the patients with a deepbite. Although simultaneous orthodontic intrusion of the 6 mandibular anterior teeth is not recommended, a few studies have evaluated individual canine intrusion. Our objectives were to use the finite element method to simulate the segmented intrusion of mandibular canines with a cantilever and to evaluate the effects of different compensatory buccolingual activations. A finite element study of the right quadrant of the mandibular dental arch together with periodontal structures was modeled using SolidWorks software (Dassault Systèmes Americas, Waltham, Mass). After all bony, dental, and periodontal ligament structures from the second molar to the canine were graphically represented, brackets and molar tubes were modeled. Subsequently, a 0.021 × 0.025-in base wire was modeled with stainless steel properties and inserted into the brackets and tubes of the 4 posterior teeth to simulate an anchorage unit. Finally, a 0.017 × 0.025-in cantilever was modeled with titanium-molybdenum alloy properties and inserted into the first molar auxiliary tube. Discretization and boundary conditions of all anatomic structures tested were determined with HyperMesh software (Altair Engineering, Milwaukee, Wis), and compensatory toe-ins of 0°, 4°, 6°, and 8° were simulated with Abaqus software (Dassault Systèmes Americas). The 6° toe-in produced pure intrusion of the canine. The highest amounts of periodontal ligament stress in the anchor segment were observed around the first molar roots. This tooth showed a slight tendency for extrusion and distal crown tipping. Moreover, the different compensatory toe-ins tested did not significantly affect the other posterior teeth. The segmented mechanics simulated in this study may achieve pure mandibular canine intrusion when an adequate amount of compensatory toe-in (6°) is incorporated into the cantilever to prevent buccal and lingual crown tipping. The effects on the posterior anchorage segment were small and initially concentrated on the first molar. Copyright © 2015 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Active sensors for health monitoring of aging aerospace structures

NASA Astrophysics Data System (ADS)

Giurgiutiu, Victor; Redmond, James M.; Roach, Dennis P.; Rackow, Kirk

2000-06-01

A project to develop non-intrusive active sensors that can be applied on existing aging aerospace structures for monitoring the onset and progress of structural damage (fatigue cracks and corrosion) is presented. The state of the art in active sensors structural health monitoring and damage detection is reviewed. Methods based on (a) elastic wave propagation and (b) electro-mechanical (E/M) impedance technique are cited and briefly discussed. The instrumentation of these specimens with piezoelectric active sensors is illustrated. The main detection strategies (E/M impedance for local area detection and wave propagation for wide area interrogation) are discussed. The signal processing and damage interpretation algorithms are tuned to the specific structural interrogation method used. In the high frequency E/M impedance approach, pattern recognition methods are used to compare impedance signatures taken at various time intervals and to identify damage presence and progression from the change in these signatures. In the wave propagation approach, the acousto- ultrasonic methods identifying additional reflection generated from the damage site and changes in transmission velocity and phase are used. Both approaches benefit from the use of artificial intelligence neural networks algorithms that can extract damage features based on a learning process. Design and fabrication of a set of structural specimens representative of aging aerospace structures is presented. Three built-up specimens, (pristine, with cracks, and with corrosion damage) are used. The specimen instrumentation with active sensors fabricated at the University of South Carolina is illustrated. Preliminary results obtained with the E/M impedance method on pristine and cracked specimens are presented.

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.

Design process and preliminary psychometric study of a video game to detect cognitive impairment in senior adults.

PubMed

Valladares-Rodriguez, Sonia; Perez-Rodriguez, Roberto; Facal, David; Fernandez-Iglesias, Manuel J; Anido-Rifon, Luis; Mouriño-Garcia, Marcos

2017-01-01

Assessment of episodic memory has been traditionally used to evaluate potential cognitive impairments in senior adults. Typically, episodic memory evaluation is based on personal interviews and pen-and-paper tests. This article presents the design, development and a preliminary validation of a novel digital game to assess episodic memory intended to overcome the limitations of traditional methods, such as the cost of its administration, its intrusive character, the lack of early detection capabilities, the lack of ecological validity, the learning effect and the existence of confounding factors. Our proposal is based on the gamification of the California Verbal Learning Test (CVLT) and it has been designed to comply with the psychometric characteristics of reliability and validity. Two qualitative focus groups and a first pilot experiment were carried out to validate the proposal. A more ecological, non-intrusive and better administrable tool to perform cognitive assessment was developed. Initial evidence from the focus groups and pilot experiment confirmed the developed game's usability and offered promising results insofar its psychometric validity is concerned. Moreover, the potential of this game for the cognitive classification of senior adults was confirmed, and administration time is dramatically reduced with respect to pen-and-paper tests. Additional research is needed to improve the resolution of the game for the identification of specific cognitive impairments, as well as to achieve a complete validation of the psychometric properties of the digital game. Initial evidence show that serious games can be used as an instrument to assess the cognitive status of senior adults, and even to predict the onset of mild cognitive impairments or Alzheimer's disease.

Attenuating fearful memories: effect of cued extinction on intrusions.

PubMed

Marks, Elizabeth H; Zoellner, Lori A

2014-12-01

Exposure-based therapies for posttraumatic stress disorder are thought to reduce intrusive memories through extinction processes. Methods that enhance extinction may translate to improved treatment. Rat research suggests retrieving a memory via a conditioned stimulus (CS) cue, and then modifying the retrieved memory within a specific reconsolidation window may enhance extinction. In humans, studies (e.g., Kindt & Soeter, 2013; Schiller et al., 2010) using basic learning paradigms show discrepant findings. Using a distressing film paradigm, participants (N = 148) completed fear acquisition and extinction. At extinction, they were randomized to 1 of 3 groups: CS cue within reconsolidation window, CS cue outside window, or non-CS cue within window. Intrusions were assessed 24 hr after extinction. Participants receiving the CS cue and completing extinction within the reconsolidation window had more intrusions (M = 2.40, SD = 2.54) than those cued outside (M = 1.65, SD = 1.70) or those receiving a non-CS cue (M = 1.24, SD = 1.26), F(2, 145) = 4.52, p = .01, d = 0.55. Consistent with the reconsolidation hypothesis, presenting a CS cue does appear to activate a specific period of time during which a memory can be updated. However, the CS cue caused increased, rather than decreased, frequency of intrusions. Understanding parameters of preextinction cueing may help us better understand reconsolidation as a potential memory updating mechanism.

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...

An Autonomic Framework for Integrating Security and Quality of Service Support in Databases

ERIC Educational Resources Information Center

Alomari, Firas

2013-01-01

The back-end databases of multi-tiered applications are a major data security concern for enterprises. The abundance of these systems and the emergence of new and different threats require multiple and overlapping security mechanisms. Therefore, providing multiple and diverse database intrusion detection and prevention systems (IDPS) is a critical…

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