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.

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

A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-03-25

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

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

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.…

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.

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.

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.

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 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.

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

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.

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network.

PubMed

Han, Ruisong; Yang, Wei; Zhang, Li

2018-02-10

Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA.

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

Intrusion Detection in Control Systems using Sequence Characteristics

NASA Astrophysics Data System (ADS)

Kiuchi, Mai; Onoda, Takashi

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

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

PubMed

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

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

ERIC Educational Resources Information Center

Koc, Levent

2013-01-01

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

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

PubMed

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

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

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

Intrusion detection: systems and models

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

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

PubMed Central

Li, Yuancheng; Jing, Sitong

2018-01-01

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

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.

The architecture of a network level intrusion detection system

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

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

1990-08-15

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Pathway from child sexual and physical abuse to risky sex among emerging adults: the role of trauma-related intrusions and alcohol problems.

PubMed

Walsh, Kate; Latzman, Natasha E; Latzman, Robert D

2014-04-01

Some evidence suggests that risk reduction programming for sexual risk behaviors (SRB) has been minimally effective, which emphasized the need for research on etiological and mechanistic factors that can be addressed in prevention and intervention programming. Childhood sexual and physical abuse have been linked with SRB among older adolescents and emerging adults; however, pathways to SRB remain unclear. This study adds to the literature by testing a model specifying that traumatic intrusions after early abuse may increase risk for alcohol problems, which in turn may increase the likelihood of engaging in various types of SRB. Participants were 1,169 racially diverse college students (72.9% female, 37.6% black/African-American, and 33.6% white) who completed anonymous questionnaires assessing child abuse, traumatic intrusions, alcohol problems, and sexual risk behavior. The hypothesized path model specifying that traumatic intrusions and alcohol problems account for associations between child abuse and several aspects of SRB was a good fit for the data; however, for men, stronger associations emerged between physical abuse and traumatic intrusions and between traumatic intrusions and alcohol problems, whereas for women, alcohol problems were more strongly associated with intent to engage in risky sex. Findings highlight the role of traumatic intrusions and alcohol problems in explaining paths from childhood abuse to SRB in emerging adulthood, and suggest that risk reduction programs may benefit from an integrated focus on traumatic intrusions, alcohol problems, and SRB for individuals with abuse experiences. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.

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...

Water Intrusion Problems in Transit Tunnels

DOT National Transportation Integrated Search

1986-05-01

This report presents the findings of five case studies in which an in-depth analysis was made of tunnel water intrusion problems in transit tunnels. Water intrusion parameters of transit systems in Atlanta, Boston, Buffalo, New York and Washington, D...

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

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…

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.

Externalizing symptoms, effortful control, and intrusive parenting: A test of bidirectional longitudinal relations during early childhood.

PubMed

Eisenberg, Nancy; Taylor, Zoe E; Widaman, Keith F; Spinrad, Tracy L

2015-11-01

At approximately 30, 42, and 54 months of age (N = 231), the relations among children's externalizing symptoms, intrusive maternal parenting, and children's effortful control (EC) were examined. Both intrusive parenting and low EC have been related to psychopathology, but children's externalizing problems and low EC might affect the quality of parenting and one another. Mothers' intrusive behavior with their children was assessed with observations, children's EC was measured with mothers' and caregivers' reports, and children's externalizing symptoms were assessed with mothers', fathers', and caregivers' reports. In a structural equation panel model, bidirectional relations between intrusive parenting and EC were found: EC at 30 and 42 months predicted low levels of intrusive parenting a year later, controlling for prior levels of parenting and vice versa. Moreover, high levels of children's externalizing problems at both 30 and 42 months negatively predicted EC a year later, controlling for prior levels of EC. Although externalizing problems positively predicted high EC over time, this appeared to be a suppression effect because these variables had a strong negative pattern in the zero-order correlations. Moreover, when controlling for the stability of intrusive parenting, EC, and externalizing (all exhibited significant stability across time) and the aforementioned cross-lagged predictive paths, EC and externalizing problems were still negatively related within the 54-month assessment. The findings are consistent with the view that children's externalizing behavior undermines their EC and contributes to intrusive mothering and that relations between intrusive parenting and EC are bidirectional across time. Thus, interventions that focus on modifying children's externalizing problems (as well as the quality of parenting) might affect the quality of parenting they receive and, hence, subsequent problems with adjustment.

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

A New Intrusion Detection Method Based on Antibody Concentration

NASA Astrophysics Data System (ADS)

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

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

Fingerprinting Software Defined Networks and Controllers

DTIC Science & Technology

2015-03-01

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

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.

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.

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.

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

PubMed

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

2017-08-26

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

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

PubMed Central

Carro, Belen; Sanchez-Esguevillas, Antonio

2017-01-01

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

A novel interacting multiple model based network intrusion detection scheme

NASA Astrophysics Data System (ADS)

Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

2006-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Prospective relations between intrusive parenting and child behavior problems: Differential moderation by parasympathetic nervous system regulation and child sex.

PubMed

Rudd, Kristen L; Alkon, Abbey; Yates, Tuppett M

2017-10-15

This study examined children's parasympathetic nervous system (PNS) regulation, which was indexed by respiratory sinus arrhythmia (RSA) during rest, reactivity, and recovery episodes, and sex as moderators of predicted relations between observed intrusive parenting and later observer-rated child behavior problems. Child-caregiver dyads (N=250; 50% girls; 46% Latino/a) completed a series of laboratory assessments yielding independent measures of intrusive parenting at age 4, PNS regulation at age 6, and child behavior problems at age 8. Results indicated that intrusive parenting was related to more internalizing problems among boys who showed low RSA reactivity (i.e., PNS withdrawal from pre-startle to startle challenge), but RSA reactivity did not moderate this relation among girls. Interestingly, RSA recovery (i.e., PNS activation from startle challenge to post-startle) moderated these relations differently for boys and girls. For girls with relatively low RSA post-startle (i.e., less recovery), intrusive parenting was positively related to both internalizing and externalizing problems. However, the reverse was true for boys, such that there was a significant positive relation between intrusive parenting and later externalizing problems among boys who evidenced relatively high RSA post-startle (i.e., more recovery). Findings provide evidence for the moderation of intrusive caregiving effects by children's PNS regulation while highlighting the differential patterning of these relations across distinct phases of the regulatory response and as a function of child sex. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

Vapor intrusion risk of fuel ether oxygenates methyl tert-butyl ether (MTBE), tert-amyl methyl ether (TAME) and ethyl tert-butyl ether (ETBE): A modeling study.

PubMed

Ma, Jie; Xiong, Desen; Li, Haiyan; Ding, Yi; Xia, Xiangcheng; Yang, Yongqi

2017-06-15

Vapor intrusion of synthetic fuel additives represents a critical yet still neglected problem at sites contaminated by petroleum fuel releases. This study used an advanced numerical model to investigate the vapor intrusion potential of fuel ether oxygenates methyl tert-butyl ether (MTBE), tert-amyl methyl ether (TAME), and ethyl tert-butyl ether (ETBE). Simulated indoor air concentration of these compounds can exceed USEPA indoor air screening level for MTBE (110μg/m 3 ). Our results also reveal that MTBE has much higher chance to cause vapor intrusion problems than TAME and ETBE. This study supports the statements made by USEPA in the Petroleum Vapor Intrusion (PVI) Guidance that the vertical screening criteria for petroleum hydrocarbons may not provide sufficient protectiveness for fuel additives, and ether oxygenates in particular. In addition to adverse impacts on human health, ether oxygenate vapor intrusion may also cause aesthetic problems (i.e., odour and flavour). Overall, this study points out that ether oxygenates can cause vapor intrusion problems. We recommend that USEPA consider including the field measurement data of synthetic fuel additives in the existing PVI database and possibly revising the PVI Guidance as necessary. Copyright © 2017 Elsevier B.V. All rights reserved.

High-resolution Self-Organizing Maps for advanced visualization and dimension reduction.

PubMed

Saraswati, Ayu; Nguyen, Van Tuc; Hagenbuchner, Markus; Tsoi, Ah Chung

2018-05-04

Kohonen's Self Organizing feature Map (SOM) provides an effective way to project high dimensional input features onto a low dimensional display space while preserving the topological relationships among the input features. Recent advances in algorithms that take advantages of modern computing hardware introduced the concept of high resolution SOMs (HRSOMs). This paper investigates the capabilities and applicability of the HRSOM as a visualization tool for cluster analysis and its suitabilities to serve as a pre-processor in ensemble learning models. The evaluation is conducted on a number of established benchmarks and real-world learning problems, namely, the policeman benchmark, two web spam detection problems, a network intrusion detection problem, and a malware detection problem. It is found that the visualization resulted from an HRSOM provides new insights concerning these learning problems. It is furthermore shown empirically that broad benefits from the use of HRSOMs in both clustering and classification problems can be expected. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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

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

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.

Evidential reasoning research on intrusion detection

NASA Astrophysics Data System (ADS)

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

2003-09-01

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

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

DTIC Science & Technology

2014-03-27

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

Investigation of Saltwater Intrusion and Recirculation of Seawater for Henry Constant Dispersion and Velocity-Dependent Dispersion Problems and Field-Scale Problem

NASA Astrophysics Data System (ADS)

Motz, L. H.; Kalakan, C.

2013-12-01

Three problems regarding saltwater intrusion, namely the Henry constant dispersion and velocity-dependent dispersion problems and a larger, field-scale velocity-dependent dispersion problem, have been investigated to determine quantitatively how saltwater intrusion and the recirculation of seawater at a coastal boundary are related to the freshwater inflow and the density-driven buoyancy flux. Based on dimensional analysis, saltwater intrusion and the recirculation of seawater are dependent functions of the independent ratio of freshwater advective flux relative to the density-driven vertical buoyancy flux, defined as az (or a for an isotropic aquifer), and the aspect ratio of horizontal and vertical dimensions of the cross-section. For the Henry constant dispersion problem, in which the aquifer is isotropic, saltwater intrusion and recirculation are related to an additional independent dimensionless parameter that is the ratio of the constant dispersion coefficient treated as a scalar quantity, the porosity, and the freshwater advective flux, defined as b. For the Henry velocity-dependent dispersion problem, the ratio b is zero, and saltwater intrusion and recirculation are related to an additional independent dimensionless parameter that is the ratio of the vertical and horizontal dispersivities, or rα = αz/αx. For an anisotropic aquifer, saltwater intrusion and recirculation are also dependent on the ratio of vertical and horizontal hydraulic conductivities, or rK = Kz/Kx. For the field-scale velocity-dependent dispersion problem, saltwater intrusion and recirculation are dependent on the same independent ratios as the Henry velocity-dependent dispersion problem. In the two-dimensional cross-section for all three problems, freshwater inflow occurs at an upgradient boundary, and recirculated seawater outflow occurs at a downgradient coastal boundary. The upgradient boundary is a specified-flux boundary with zero freshwater concentration, and the downgradient boundary is a specified-head boundary with a specified concentration equal to seawater. Equivalent freshwater heads are specified at the downstream boundary to account for density differences between freshwater and saltwater at the downstream boundary. The three problems were solved using the numerical groundwater flow and transport code SEAWAT for two conditions, i.e., first for the uncoupled condition in which the fluid density is constant and thus the flow and transport equations are uncoupled in a constant-density flowfield, and then for the coupled condition in which the fluid density is a function of the total dissolved solids concentration and thus the flow and transport equations are coupled in a variable-density flowfield. A wide range of results for the landward extent of saltwater intrusion and the amount of recirculation of seawater at the coastal boundary was obtained by varying the independent dimensionless ratio az (or a in problem one) in all three problems. The dimensionless dispersion ratio b was also varied in problem one, and the dispersivity ratio rα and the hydraulic conductivity ratio rK were also varied in problems two and three.

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

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…

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

Railway clearance intrusion detection method with binocular stereo vision

NASA Astrophysics Data System (ADS)

Zhou, Xingfang; Guo, Baoqing; Wei, Wei

2018-03-01

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

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.

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...

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.

Anomaly-based intrusion detection for SCADA systems

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

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

2006-07-01

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

Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

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

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

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

NASA Astrophysics Data System (ADS)

Pham, Congduc

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

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

NASA Astrophysics Data System (ADS)

Salamatova, T.; Zhukov, V.

2017-02-01

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

Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

USGS Publications Warehouse

Sanz, E.; Voss, C.I.

2006-01-01

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only concentration observations. Permeability, freshwater inflow, solute molecular diffusivity, and porosity can be estimated with roughly equivalent confidence using observations of only the logarithm of concentration. Furthermore, covariance analysis allows a logical reduction of the number of estimated parameters for ill-posed inverse seawater intrusion problems. Ill-posed problems may exhibit poor estimation convergence, have a non-unique solution, have multiple minima, or require excessive computational effort, and the condition often occurs when estimating too many or co-dependent parameters. For the Henry problem, such analysis allows selection of the two parameters that control system physics from among all possible system parameters. ?? 2005 Elsevier Ltd. All rights reserved.

Psychological Intrusion – An Overlooked Aspect of Dental Fear

PubMed Central

Chapman, Helen R.; Kirby-Turner, Nick

2018-01-01

Dental fear/anxiety is a widely recognised problem affecting a large proportion of the population. It can result in avoidance and/or difficulty accepting dental care. We believe that psychological intrusion may play a role in the aetiology and maintenance of dental fear for at least some individuals. In this narrative review we will take a developmental perspective in order to understand its impact across the lifespan. We will consider the nature of ‘self,’ parenting styles, the details of intrusive parenting or parental psychological control, and briefly touch upon child temperament and parental anxiety. Finally, we draw together the supporting (largely unrecognised) evidence available in the dental literature. We illustrate the paper with clinical examples and discuss possibly effective ways of addressing the problem. We conclude that psychological intrusion appears to play an important role in dental fear, for at least some individuals, and we call for detailed research into the extent and exact nature of the problem. A simple means of identifying individuals who are vulnerable to psychological intrusion would be useful for dentists. PMID:29719519

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.

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.

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.

Mother-Child Interaction and Early Language Skills in Children Born to Mothers with Substance Abuse and Psychiatric Problems.

PubMed

J Haabrekke, Kristin; Siqveland, Torill; Smith, Lars; Wentzel-Larsen, Tore; Walhovd, Kristine B; Moe, Vibeke

2015-10-01

This prospective, longitudinal study with data collected at four time points investigated how maternal psychiatric symptoms, substance abuse and maternal intrusiveness in interaction were related to early child language skills. Three groups of mothers were recruited during pregnancy: One from residential treatment institutions for substance abuse (n = 18), one from psychiatric outpatient treatment (n = 22) and one from well-baby clinics (n = 30). Maternal substance abuse and anti-social and borderline personality traits were assessed during pregnancy, postpartum depression at 3 months, maternal intrusiveness in interaction at 12 months, and child language skills at 2 years. Results showed that the mothers in the substance abuse group had the lowest level of education, they were younger and they were more likely to be single mothers than the mothers in the two other groups. There was a significant difference in expressive language between children born to mothers with substance abuse problems and those born to comparison mothers, however not when controlling for maternal age, education and single parenthood. No group differences in receptive language skills were detected. Results further showed that maternal intrusiveness observed in mother-child interaction at 12 months was significantly related to child expressive language at 2 years, also when controlling for socio-demographic risk factors. This suggests that in addition to addressing substance abuse and psychiatric problems, there is a need for applying treatment models promoting sensitive caregiving, in order to enhance child expressive language skills.

Identification and Control of Pollution from Salt Water Intrusion.

ERIC Educational Resources Information Center

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

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

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

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions

DTIC Science & Technology

2007-03-01

Intelligence AIS Artificial Immune System ANN Artificial Neural Networks API Application Programming Interface BFS Breadth-First Search BIS Biological...problem domain is too large for only one algorithm’s application . It ranges from network - based sniffer systems, responsible for Enterprise-wide coverage...options to network administrators in choosing detectors to employ in future ID applications . Objectives Our hypothesis validity is based on a set

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

An Efficient Method for Detecting Misbehaving Zone Manager in MANET

NASA Astrophysics Data System (ADS)

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

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

Case-Based Multi-Sensor Intrusion Detection

NASA Astrophysics Data System (ADS)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

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

The study and implementation of the wireless network data security model

NASA Astrophysics Data System (ADS)

Lin, Haifeng

2013-03-01

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

Network Anomaly Detection Based on Wavelet Analysis

NASA Astrophysics Data System (ADS)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

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

Detection of network attacks based on adaptive resonance theory

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Non-intrusive methods of characterizing vehicles on the highway.

DOT National Transportation Integrated Search

2003-06-01

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

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

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

A Comparative Study of Unsupervised Anomaly Detection Techniques Using Honeypot Data

NASA Astrophysics Data System (ADS)

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

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

An Adaptive Database Intrusion Detection System

ERIC Educational Resources Information Center

Barrios, Rita M.

2011-01-01

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

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

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

Morellas, Vassilios; Johnson, Andrew; Johnston, Chris

2006-07-01

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

Alerts Visualization and Clustering in Network-based Intrusion Detection

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

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

2010-04-01

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

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.

Integrating Security in Real-Time Embedded Systems

DTIC Science & Technology

2017-04-26

b) detect any intrusions/a ttacks once tl1ey occur and (c) keep the overall system safe in the event of an attack. 4. Analysis and evaluation of...beyond), we expanded our work in both security integration and attack mechanisms, and worked on demonstrations and evaluations in hardware. Year I...scheduling for each busy interval w ith the calculated arrival time w indow. Step 1 focuses on the problem of finding the quanti ty of each task

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.

An Optimal Method for Detecting Internal and External Intrusion in MANET

NASA Astrophysics Data System (ADS)

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

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

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

PubMed

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Neural Network Based Intrusion Detection System for Critical Infrastructures

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

Todd Vollmer; Ondrej Linda; Milos Manic

2009-07-01

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

Carbamazepine Treatment of Hyperactivity and Intrusiveness in Dementia.

PubMed

Stewart, Jonathan T

Behavioral problems are seen in most patients with dementia and are often poorly characterized in the literature. We present a 70-year-old man with advanced Alzheimer disease and problematic disinhibited behaviors, including intrusiveness and Witzelsucht (disinhibited humor). These symptoms responded robustly to carbamazepine. Carbamazepine may be a useful adjunct in managing problematic behaviors in dementia, especially when those problems can be framed as behavioral disinhibition.

Automated Software Vulnerability Analysis

NASA Astrophysics Data System (ADS)

Sezer, Emre C.; Kil, Chongkyung; Ning, Peng

Despite decades of research, software continues to have vulnerabilities. Successful exploitations of these vulnerabilities by attackers cost millions of dollars to businesses and individuals. Unfortunately, most effective defensive measures, such as patching and intrusion prevention systems, require an intimate knowledge of the vulnerabilities. Many systems for detecting attacks have been proposed. However, the analysis of the exploited vulnerabilities is left to security experts and programmers. Both the human effortinvolved and the slow analysis process are unfavorable for timely defensive measure to be deployed. The problem is exacerbated by zero-day attacks.

Addressing software security and mitigations in the life cycle

NASA Technical Reports Server (NTRS)

Gilliam, David; Powell, John; Haugh, Eric; Bishop, Matt

2003-01-01

Traditionally, security is viewed as an organizational and Information Technology (IIJ systems function comprising of Firewalls, intrusion detection systems (IDS), system security settings and patches to the operating system (OS) and applications running on it. Until recently, little thought has been given to the importance of security as a formal approach in the software life cycle. The Jet Propulsion Laboratory has approached the problem through the development of an integrated formal Software Security Assessment Instrument (SSAI) with six foci for the software life cycle.

Addressing software security and mitigations in the life cycle

NASA Technical Reports Server (NTRS)

Gilliam, David; Powell, John; Haugh, Eric; Bishop, Matt

2004-01-01

Traditionally, security is viewed as an organizational and Information Technology (IT) systems function comprising of firewalls, intrusion detection systems (IDS), system security settings and patches to the operating system (OS) and applications running on it. Until recently, little thought has been given to the importance of security as a formal approach in the software life cycle. The Jet Propulsion Laboratory has approached the problem through the development of an integrated formal Software Security Assessment Instrument (SSAI) with six foci for the software life cycle.

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%.

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

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

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

2001-09-01

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

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

DTIC Science & Technology

2003-11-01

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

BioVapor Model Evaluation

EPA Science Inventory

General background on modeling and specifics of modeling vapor intrusion are given. Three classical model applications are described and related to the problem of petroleum vapor intrusion. These indicate the need for model calibration and uncertainty analysis. Evaluation of Bi...

The Effects of Saltwater Intrusion to Flood Mitigation Project

NASA Astrophysics Data System (ADS)

Azida Abu Bakar, Azinoor; Khairudin Khalil, Muhammad

2018-03-01

The objective of this study is to determine the effects of saltwater intrusion to flood mitigation project located in the flood plains in the district of Muar, Johor. Based on the studies and designs carried out, one of the effective flood mitigation options identified is the Kampung Tanjung Olak bypass and Kampung Belemang bypass at the lower reaches of Sungai Muar. But, the construction of the Kampung Belemang and Tanjung Olak bypass, while speeding up flood discharges, may also increase saltwater intrusion during drought low flows. Establishing the dynamics of flooding, including replicating the existing situation and the performance with prospective flood mitigation interventions, is most effectively accomplished using computer-based modelling tools. The finding of this study shows that to overcome the problem, a barrage should be constructed at Sungai Muar to solve the saltwater intrusion and low yield problem of the river.

In-situ trainable intrusion detection system

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

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

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

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

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.

Smart container UWB sensor system for situational awareness of intrusion alarms

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

Code of Federal Regulations, 2013 CFR

2013-10-01

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

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

Code of Federal Regulations, 2014 CFR

2014-10-01

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

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

Code of Federal Regulations, 2012 CFR

2012-10-01

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

Using Unix system auditing for detecting network intrusions

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

Christensen, M.J.

1993-03-01

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

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

NASA Astrophysics Data System (ADS)

Chen, Xinjia; Lacy, Fred; Carriere, Patrick

2015-05-01

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

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

DTIC Science & Technology

2014-03-27

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

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

DTIC Science & Technology

2004-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-08-01

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

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.

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.

Intrusive fathering, children's self-regulation and social skills: a mediation analysis.

PubMed

Stevenson, M; Crnic, K

2013-06-01

Fathers have unique influences on children's development, and particularly in the development of social skills. Although father-child relationship influences on children's social competence have received increased attention in general, research on fathering in families of children with developmental delays (DD) is scant. This study examined the pathway of influence among paternal intrusive behaviour, child social skills and child self-regulatory ability, testing a model whereby child regulatory behaviour mediates relations between fathering and child social skills. Participants were 97 families of children with early identified DD enrolled in an extensive longitudinal study. Father and mother child-directed intrusiveness was coded live in naturalistic home observations at child age 4.5, child behaviour dysregulation was coded from a video-taped laboratory problem-solving task at child age 5, and child social skills were measured using independent teacher reports at child age 6. Analyses tested for mediation of the relationship between fathers' intrusiveness and child social skills by child behaviour dysregulation. Fathers' intrusiveness, controlling for mothers' intrusiveness and child behaviour problems, was related to later child decreased social skills and this relationship was mediated by child behaviour dysregulation. Intrusive fathering appears to carry unique risk for the development of social skills in children with DD. Findings are discussed as they related to theories of fatherhood and parenting in children with DD, as well as implications for intervention and future research. © 2012 The Authors. Journal of Intellectual Disability Research © 2012 John Wiley & Sons Ltd, MENCAP & IASSID.

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

NASA Astrophysics Data System (ADS)

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

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

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

NASA Astrophysics Data System (ADS)

Phit, Thyda; Abe, Kôki

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

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.

Improving the Quality of Alerts and Predicting Intruder's Next Goal with Hidden Colored Petri-Net

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

Yu, Dong; Frincke, Deb A.

2006-06-22

Intrusion detection systems (IDS) often provide poor quality alerts, which are insufficient to support rapid identification of ongoing attacks or predict an intruder’s next likely goal. In this paper, we propose a novel approach to alert post-processing and correlation, the Hidden Colored Petri-Net (HCPN). Different from most other alert correlation methods, our approach treats the alert correlation problem as an inference problem rather than a filter problem. Our approach assumes that the intruder’s actions are unknown to the IDS and can be inferred only from the alerts generated by the IDS sensors. HCPN can describe the relationship between different stepsmore » carried out by intruders, model observations (alerts) and transitions (actions) separately, and associate each token element (system state) with a probability (or confidence). The model is an extension to Colored Petri-Net (CPN) .It is so called “hidden” because the transitions (actions) are not directly observable but can be inferred by looking through the observations (alerts). These features make HCPN especially suitable for discovering intruders’ actions from their partial observations (alerts,) and predicting intruders’ next goal. Our experiments on DARPA evaluation datasets and the attack scenarios from the Grand Challenge Problem (GCP) show that HCPN has promise as a way to reducing false positives and negatives, predicting intruder’s next possible action, uncovering intruders’ intrusion strategies after the attack scenario has happened, and providing confidence scores.« less

A Learning System for Discriminating Variants of Malicious Network Traffic

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

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

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

Perimeter intrusion detection and assessment system

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

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

1977-01-01

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

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

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Sainani, Varsha

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

Establishing and Maintaining Treatment Effects with Less Intrusive Consequences VIA a Pairing Procedure

PubMed Central

Vorndran, Christina M; Lerman, Dorothea C

2006-01-01

The generality and long-term maintenance of a pairing procedure designed to improve the efficacy of less intrusive procedures were evaluated for the treatment of problem behavior maintained by automatic reinforcement exhibited by 2 individuals with developmental disabilities. Results suggested that a less intrusive procedure could be established as a conditioned punisher by pairing it with an effective punisher contingent on problem behavior. Generalization across multiple therapists was demonstrated for both participants. However, generalization to another setting was not achieved for 1 participant until pairing was conducted in the second setting. Long-term maintenance was observed with 1 participant in the absence of further pairing trials. Maintenance via intermittent pairing trials was successful for the other participant. PMID:16602384

Anomaly Detection Based on Sensor Data in Petroleum Industry Applications

PubMed Central

Martí, Luis; Sanchez-Pi, Nayat; Molina, José Manuel; Garcia, Ana Cristina Bicharra

2015-01-01

Anomaly detection is the problem of finding patterns in data that do not conform to an a priori expected behavior. This is related to the problem in which some samples are distant, in terms of a given metric, from the rest of the dataset, where these anomalous samples are indicated as outliers. Anomaly detection has recently attracted the attention of the research community, because of its relevance in real-world applications, like intrusion detection, fraud detection, fault detection and system health monitoring, among many others. Anomalies themselves can have a positive or negative nature, depending on their context and interpretation. However, in either case, it is important for decision makers to be able to detect them in order to take appropriate actions. The petroleum industry is one of the application contexts where these problems are present. The correct detection of such types of unusual information empowers the decision maker with the capacity to act on the system in order to correctly avoid, correct or react to the situations associated with them. In that application context, heavy extraction machines for pumping and generation operations, like turbomachines, are intensively monitored by hundreds of sensors each that send measurements with a high frequency for damage prevention. In this paper, we propose a combination of yet another segmentation algorithm (YASA), a novel fast and high quality segmentation algorithm, with a one-class support vector machine approach for efficient anomaly detection in turbomachines. The proposal is meant for dealing with the aforementioned task and to cope with the lack of labeled training data. As a result, we perform a series of empirical studies comparing our approach to other methods applied to benchmark problems and a real-life application related to oil platform turbomachinery anomaly detection. PMID:25633599

Procrastination as a Self-Regulation Failure: The Role of Impulsivity and Intrusive Thoughts.

PubMed

Rebetez, Marie My Lien; Rochat, Lucien; Barsics, Catherine; Van der Linden, Martial

2018-02-01

Procrastination has been described as the quintessence of self-regulatory failure. This study examines the relationships between this self-regulatory failure and other manifestations of self-regulation problems, namely impulsivity and intrusive thoughts. One hundred and forty-one participants completed questionnaires assessing procrastination, impulsivity (in particular, the urgency and lack of perseverance dimensions), and intrusive thoughts (i.e., rumination and daydreaming). Main results show that urgency mediated the association between rumination and procrastination, whereas rumination did not mediate the relation between urgency and procrastination. Lack of perseverance mediated the association between daydreaming and procrastination, and daydreaming mediated the relation between lack of perseverance and procrastination. This study highlights the role of impulsivity and intrusive thoughts in procrastination, specifies the links between these self-regulation problems, and provides insights into their (potential) underlying mechanisms. It also opens interesting prospects for management strategies for implementing targeted psychological interventions to reduce impulsive manifestations and/or thought control difficulties accompanying procrastination.

Time to face it! Facebook intrusion and the implications for romantic jealousy and relationship satisfaction.

PubMed

Elphinston, Rachel A; Noller, Patricia

2011-11-01

Young people's exposure to social network sites such as Facebook is increasing, along with the potential for such use to complicate romantic relationships. Yet, little is known about the overlaps between the online and offline worlds. We extended previous research by investigating the links between Facebook intrusion, jealousy in romantic relationships, and relationship outcomes in a sample of undergraduates currently in a romantic relationship. A Facebook Intrusion Questionnaire was developed based on key features of technological (behavioral) addictions. An eight-item Facebook Intrusion Questionnaire with a single-factor structure was supported; internal consistency was high. Facebook intrusion was linked to relationship dissatisfaction, via jealous cognitions and surveillance behaviors. The results highlight the possibility of high levels of Facebook intrusion spilling over into romantic relationships, resulting in problems such as jealousy and dissatisfaction. The results have implications for romantic relationships and for Facebook users in general.

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.

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.

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

MODEL UNCERTAINTY ANALYSIS, FIELD DATA COLLECTION AND ANALYSIS OF CONTAMINATED VAPOR INTRUSION INTO BUILDINGS

EPA Science Inventory

To address uncertainty associated with the evaluation of vapor intrusion problems we are working on a three part strategy that includes: evaluation of uncertainty in model-based assessments; collection of field data and assessment of sites using EPA and state protocols.

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

NASA Technical Reports Server (NTRS)

Lee, R. D. (Inventor)

1983-01-01

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

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

DTIC Science & Technology

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

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

PubMed

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

2017-08-01

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

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.

Overview of USEPA's ORD Technical Outreach and Support Activities on Vapor Intrusion Impacts - 03/2008

EPA Science Inventory

The science of determining, characterizing and managing vapor intrusion risks is constantly evolving. Much remains to be done in assisting regulators, consultants and other decision-makers to make informed decisions in mitigating the problem and reducing these risks. ORD has been...

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

Interpersonal Problems Predict Differential Response to Cognitive Versus Behavioral Treatment in a Randomized Controlled Trial

PubMed Central

Newman, Michelle G.; Jacobson, Nicholas C.; Erickson, Thane M.; Fisher, Aaron J.

2016-01-01

Objective We examined dimensional interpersonal problems as moderators of cognitive behavioral therapy (CBT) versus its components (cognitive therapy [CT] and behavioral therapy [BT]). We predicted that people with generalized anxiety disorder (GAD) whose interpersonal problems reflected more dominance and intrusiveness would respond best to a relaxation-based BT compared to CT or CBT, based on studies showing that people with personality features associated with a need for autonomy respond best to treatments that are more experiential, concrete, and self-directed compared to therapies involving abstract analysis of one’s problems (e.g., containing CT). Method This was a secondary analysis of Borkovec, Newman, Pincus, and Lytle (2002). Forty-seven participants with principal diagnoses of GAD were assigned randomly to combined CBT (n = 16), CT (n = 15), or BT (n = 16). Results As predicted, compared to participants with less intrusiveness, those with dimensionally more intrusiveness responded with greater GAD symptom reduction to BT than to CBT at posttreatment and greater change to BT than to CT or CBT across all follow-up points. Similarly, those with more dominance responded better to BT compared to CT and CBT at all follow-up points. Additionally, being overly nurturant at baseline was associated with GAD symptoms at baseline, post, and all follow-up time-points regardless of therapy condition. Conclusions Generally anxious individuals with domineering and intrusive problems associated with higher need for control may respond better to experiential behavioral interventions than to cognitive interventions, which may be perceived as a direct challenge of their perceptions. PMID:28077221

Interpersonal Problems Predict Differential Response to Cognitive Versus Behavioral Treatment in a Randomized Controlled Trial.

PubMed

Newman, Michelle G; Jacobson, Nicholas C; Erickson, Thane M; Fisher, Aaron J

2017-01-01

We examined dimensional interpersonal problems as moderators of cognitive behavioral therapy (CBT) versus its components (cognitive therapy [CT] and behavioral therapy [BT]). We predicted that people with generalized anxiety disorder (GAD) whose interpersonal problems reflected more dominance and intrusiveness would respond best to a relaxation-based BT compared to CT or CBT, based on studies showing that people with personality features associated with a need for autonomy respond best to treatments that are more experiential, concrete, and self-directed compared to therapies involving abstract analysis of one's problems (e.g., containing CT). This was a secondary analysis of Borkovec, Newman, Pincus, and Lytle (2002). Forty-seven participants with principal diagnoses of GAD were assigned randomly to combined CBT (n = 16), CT (n = 15), or BT (n = 16). As predicted, compared to participants with less intrusiveness, those with dimensionally more intrusiveness responded with greater GAD symptom reduction to BT than to CBT at posttreatment and greater change to BT than to CT or CBT across all follow-up points. Similarly, those with more dominance responded better to BT compared to CT and CBT at all follow-up points. Additionally, being overly nurturant at baseline was associated with GAD symptoms at baseline, post, and all follow-up time-points regardless of therapy condition. Generally anxious individuals with domineering and intrusive problems associated with higher need for control may respond better to experiential behavioral interventions than to cognitive interventions, which may be perceived as a direct challenge of their perceptions. Copyright © 2016. Published by Elsevier Ltd.

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 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

Maternal Attributions of Infant Behavior and Parenting in Toddlerhood Predict Teacher-Rated Internalizing Problems in Childhood.

PubMed

Wagner, Nicholas J; Gueron-Sela, Noa; Bedford, Rachael; Propper, Cathi

2018-06-12

Social-information-processing theories of parenting posit that parents' beliefs and attributions about their children's behaviors contribute to how parents interact with their children. The purpose of this study was to examine the associations between negative parenting attributions in infancy, harsh-intrusive parenting in toddlerhood, and children's internalizing problems (IPs) in early childhood. Using data from a diverse longitudinal study (n = 206), the current study used a structural equation modeling approach to test if mothers' negative attributions measured at 6 months predicted teacher ratings of children's IPs in 1st grade, as well as the extent to which observed harsh-intrusive parenting behaviors measured at ages 1, 2, and 3 years mediated this link. Maternal negative attributions in infancy predict more IPs in 1st grade, but this link becomes nonsignificant when observed harsh-intrusive parenting is included as a mediator. A significant indirect effect suggests that harsh-intrusive parenting mediates the association between early negative attributions and eventual IPs. Findings from this study identify harsh-intrusive parenting behaviors as one potential mechanism through which the effects of early attributions are carried forward to influence children's IPs. The developmental and clinical implications of these findings are discussed.

Development test results of the Portable, Reconfigurable Sky Sensor (PRSS)

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

Blattman, D.A.

1993-12-31

The protection of assets against surreptitious access from the sky is a continuing problem. The Portable, Reconfigurable Sky Sensor is designed to provide volumetric intruder detection against low-observable aircraft, helicopters, and parachutists in the sky. Multiple systems may be joined to form continuous detection volume for applications such as borders. The PRSS is resistant to nuisance alarms due to wind up to 70 mph, rain/snow up to 6 inches/hour or small targets such as birds. The PRSS has been successfully tested against multiple intrusions with altitude range from 50 to 3,000 feet and cross-range up to 3,000 feet. This papermore » summarizes some of these field tests and lists specifications and potential uses.« less

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

NASA Astrophysics Data System (ADS)

McEvoy, Thomas Richard; Wolthusen, Stephen D.

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

Hysteretic behavior in seawater intrusion in response to discontinuous drought periods

NASA Astrophysics Data System (ADS)

Salandin, P.; Darvini, G.

2017-12-01

The seawater intrusion (SWI) represents a relevant problem for communities living in many coastal regions and in small islands, where the amount of fresh water available for human consumption or irrigation purposes depends on the equilibrium between the natural groundwater recharge from precipitations and the surrounding sea. This issue is exacerbated by climate changes, and, as a consequence, the reduction of natural groundwater recharge and the decrease the seaward flows of fresh water rather than sea level rise, as recently demonstrated by Ketabchi et al. (2016), leads to magnify the seawater intrusion into coastal aquifers. The temporal fluctuation of the fresh water table level are a natural consequence of the interaction of the aquifer with a water body or due to the seasonal replenishment of the water table. The severe and prolonged drought phenomena as that observed in last years in some areas of the Mediterranean, as over the central western Mediterranean basin, Italy and Spain, where a decreasing trend in total precipitation was detected (Alpert et al., 2002) in addition to the rise in temperature, enlarges the variation of the freshwater flux and can magnify the progression of the saline wedge. In the present study we demonstrate that the presence of varying boundary constraints or forcing factors may lead to hysteretic behavior in saltwater intrusion, showing dependence of the saline wedge on historic conditions. Therefore, the dynamic behavior of SWI may depend on both the present and past forcing conditions. To this aim different transient simulations supported by evidences deduced from a physical model are carried out to assess the presence of the hysteretic effects in the SWI phenomenon and to evaluate its influence in the management of the coastal aquifers for both the rational exploitation and the corrected management of water resources. About 70% of the world's population dwells in coastal zones. Therefore the optimal exploitation of fresh groundwater and the control of seawater intrusion are the challenges of the present day and future water supply engineers and managers. The existence of hysteretic effects further challenges the modelling of wedge saltwater intrusion and indicates that past forcing conditions should be considered in the interpretation of SWI measurements and predictions.

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

Sexually intrusive behaviour following brain injury: approaches to assessment and rehabilitation.

PubMed

Bezeau, Scott C; Bogod, Nicholas M; Mateer, Catherine A

2004-03-01

Sexually intrusive behaviour, which may range from inappropriate commentary to rape, is often observed following a traumatic brain injury. It may represent novel behaviour patterns or an exacerbation of pre-injury personality traits, attitudes, and tendencies. Sexually intrusive behaviour poses a risk to staff and residents of residential facilities and to the community at large, and the development of a sound assessment and treatment plan for sexually intrusive behaviour is therefore very important. A comprehensive evaluation is best served by drawing on the fields of neuropsychology, forensic psychology, and cognitive rehabilitation. The paper discusses the types of brain damage that commonly lead to sexually intrusive behaviour, provides guidance for its assessment, and presents a three-stage treatment model. The importance of a multidisciplinary approach to both assessment and treatment is emphasized. Finally, a case example is provided to illustrate the problem and the possibilities for successful management.

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.

The appraisal of intrusive thoughts in relation to obsessional-compulsive symptoms.

PubMed

Barrera, Terri L; Norton, Peter J

2011-01-01

Research has shown that although intrusive thoughts occur universally, the majority of individuals do not view intrusive thoughts as being problematic (Freeston, Ladouceur, Thibodeau, & Gagnon, 1991; Rachman & de Silva, 1978; Salkovskis & Harrison, 1984). Thus, it is not the presence of intrusive thoughts that leads to obsessional problems but rather some other factor that plays a role in the development of abnormal obsessions. According to the cognitive model of obsessive-compulsive disorder (OCD) put forth by Salkovskis (1985), the crucial factor that differentiates between individuals with OCD and those without is the individual's appraisal of the naturally occurring intrusive thoughts. This study aimed to test Salkovskis's model by examining the role of cognitive biases (responsibility, thought-action fusion, and thought control) as well as distress in the relationship between intrusive thoughts and obsessive-compulsive symptoms in an undergraduate sample of 326 students. An existing measure of intrusive thoughts (the Revised Obsessional Intrusions Inventory) was modified for this study to include a scale of distress associated with each intrusive thought in addition to the current frequency scale. When the Yale-Brown Obsessive-Compulsive Scale was used as the measure of OCD symptoms, a significant interaction effect of frequency and distress of intrusive thoughts resulted. Additionally, a significant three-way interaction of Frequency × Distress × Responsibility was found when the Obsessive Compulsive Inventory-Revised was used as the measure of OCD symptoms. These results indicate that the appraisal of intrusive thoughts is important in predicting OCD symptoms, thus providing support for Salkovskis's model of OCD.

The Role of Parents in Young Adolescents' Competence with Peers: An Observational Study of Advice Giving and Intrusiveness

ERIC Educational Resources Information Center

Poulin, Francois; Nadeau, Karine; Scaramella, Laura V.

2012-01-01

Young adolescents who encounter difficulties with peers can consult with their parents to help solve these problems. In this context, this study examines the contribution of adolescents' disclosure, parental advice giving, and parental intrusiveness into adolescents' social and behavioral adjustment. Young adolescents (N = 93; 49% girls; mean age…

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.

Intimate Partner Violence, Maternal Gatekeeping, and Child Conduct Problems

PubMed Central

Zvara, Bharathi J.; Mills-Koonce, W. Roger; Cox, Martha

2017-01-01

We examined the mediating role of parenting behavior on the relationship between intimate partner violence and child conduct problems, as well as the moderating role of maternal gatekeeping to these associations. The sample (N = 395) is from a longitudinal study of rural poverty in the eastern United States, exploring the ways in which child, family, and contextual factors shape child development over time. Study findings indicate that a father’s harsh–intrusive parenting behavior may be a key mediating pathway linking intimate partner violence and child conduct problems. Study findings further provide evidence for problematic outcomes for children when mothers encourage fathers with high levels of harsh–intrusive parenting to interact with their children. PMID:28943690

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

Tong, Xiaojun; Wang, Zhu; Yu, Haining

2009-10-01

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

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

PubMed Central

Avalappampatty Sivasamy, Aneetha; Sundan, Bose

2015-01-01

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

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

PubMed

Sivasamy, Aneetha Avalappampatty; Sundan, Bose

2015-01-01

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

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

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

Jared Verba; Michael Milvich

2008-05-01

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

Appliance of Independent Component Analysis to System Intrusion Analysis

NASA Astrophysics Data System (ADS)

Ishii, Yoshikazu; Takagi, Tarou; Nakai, Kouji

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

Visual behavior characterization for intrusion and misuse detection

NASA Astrophysics Data System (ADS)

Erbacher, Robert F.; Frincke, Deborah

2001-05-01

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

Body, mother, mind: anorexia, femininity and the intrusive object.

PubMed

Lawrence, Marilyn

2002-08-01

This paper takes as its starting point the preponderance of female to male patients who suffer from anorexia. The author suggests that there may be something specific about certain experiences of femaleness which predispose towards anxieties of intrusion. Two contemporary theories of the aetiology of anorexia are outlined. Both of these suggest that the problem has its origins in intrusion or invasion of different sorts. The author suggests that many women who suffer from anorexia have an intrusive object instated in their minds, which may not necessarily be the result of actual intrusions in external reality. In the final part of the paper, the author examines the intrusiveness of anorexic patients in the transference and suggests that such patients very often harbour profound phantasies of intruding between the parents, with a wish to regain their special place with mother, untroubled by the presence of father. It is further suggested that the psychopathology underlying certain cases of anorexia leads to a failure in symbolisation. This failure in turn complicates the clinical picture, making such patients particularly difficult to think with about their difficulties.

Simulation Of Seawater Intrusion With 2D And 3D Models: Nauru Island Case Study

NASA Astrophysics Data System (ADS)

Ghassemi, F.; Jakeman, A. J.; Jacobson, G.; Howard, K. W. F.

1996-03-01

With the advent of large computing capacities during the past few decades, sophisticated models have been developed for the simulation of seawater intrusion in coastal and island aquifers. Currently, several models are commercially available for the simulation of this problem. This paper describes the mathematical basis and application of the SUTRA and HST3D models to simulate seawater intrusion in Nauru Island, in the central Pacific Ocean. A comparison of the performance and limitations of these two models in simulating a real problem indicates that three-dimensional simulation of seawater intrusion with the HST3D model has the major advantage of being able to specify natural boundary conditions as well as pumping stresses. However, HST3D requires a small grid size and short time steps in order to maintain numerical stability and accuracy. These requirements lead to solution of a large set of linear equations that requires the availability of powerful computing facilities in terms of memory and computing speed. Combined results of the two simulation models indicate a safe pumping rate of 400 m3/d for the aquifer on Nauru Island, where additional fresh water is presently needed for the rehabilitation of mined-out land.

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.

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 Simulation-Optimization Model for the Management of Seawater Intrusion

NASA Astrophysics Data System (ADS)

Stanko, Z.; Nishikawa, T.

2012-12-01

Seawater intrusion is a common problem in coastal aquifers where excessive groundwater pumping can lead to chloride contamination of a freshwater resource. Simulation-optimization techniques have been developed to determine optimal management strategies while mitigating seawater intrusion. The simulation models are often density-independent groundwater-flow models that may assume a sharp interface and/or use equivalent freshwater heads. The optimization methods are often linear-programming (LP) based techniques that that require simplifications of the real-world system. However, seawater intrusion is a highly nonlinear, density-dependent flow and transport problem, which requires the use of nonlinear-programming (NLP) or global-optimization (GO) techniques. NLP approaches are difficult because of the need for gradient information; therefore, we have chosen a GO technique for this study. Specifically, we have coupled a multi-objective genetic algorithm (GA) with a density-dependent groundwater-flow and transport model to simulate and identify strategies that optimally manage seawater intrusion. GA is a heuristic approach, often chosen when seeking optimal solutions to highly complex and nonlinear problems where LP or NLP methods cannot be applied. The GA utilized in this study is the Epsilon-Nondominated Sorted Genetic Algorithm II (ɛ-NSGAII), which can approximate a pareto-optimal front between competing objectives. This algorithm has several key features: real and/or binary variable capabilities; an efficient sorting scheme; preservation and diversity of good solutions; dynamic population sizing; constraint handling; parallelizable implementation; and user controlled precision for each objective. The simulation model is SEAWAT, the USGS model that couples MODFLOW with MT3DMS for variable-density flow and transport. ɛ-NSGAII and SEAWAT were efficiently linked together through a C-Fortran interface. The simulation-optimization model was first tested by using a published density-independent flow model test case that was originally solved using a sequential LP method with the USGS's Ground-Water Management Process (GWM). For the problem formulation, the objective is to maximize net groundwater extraction, subject to head and head-gradient constraints. The decision variables are pumping rates at fixed wells and the system's state is represented with freshwater hydraulic head. The results of the proposed algorithm were similar to the published results (within 1%); discrepancies may be attributed to differences in the simulators and inherent differences between LP and GA. The GWM test case was then extended to a density-dependent flow and transport version. As formulated, the optimization problem is infeasible because of the density effects on hydraulic head. Therefore, the sum of the squared constraint violation (SSC) was used as a second objective. The result is a pareto curve showing optimal pumping rates versus the SSC. Analysis of this curve indicates that a similar net-extraction rate to the test case can be obtained with a minor violation in vertical head-gradient constraints. This study shows that a coupled ɛ-NSGAII/SEAWAT model can be used for the management of groundwater seawater intrusion. In the future, the proposed methodology will be applied to a real-world seawater intrusion and resource management problem for Santa Barbara, CA.

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.

People with symptoms of Ménière's disease: the relationship between illness intrusiveness, illness uncertainty, dizziness handicap, and depression.

PubMed

Arroll, Megan; Dancey, Christine P; Attree, Elizabeth A; Smith, Sharon; James, Trevor

2012-07-01

The goal of this study was to assess the impact of dizziness handicap, illness intrusiveness (in relation to vertigo, tinnitus, and hearing problems), and illness uncertainty on depression in people with the symptoms of Ménière's disease. Ménière's disease is a progressive disease of the inner ear, the symptoms of which are vertigo, tinnitus, hearing loss, and aural fullness. Although pharmacologic treatments may reduce acute vertigo spells and dizziness, they rarely disappear entirely. Previous research shows that Ménière's disease is unpredictable and has a negative impact on patients' quality of life. Questionnaires measuring Dizziness Handicap, Illness Intrusiveness, Illness Uncertainty, and Depression were completed by 74 people with self-reported symptoms of Ménière's disease. Bivariate correlations, repeated-measures analysis of variance, and multiple regression analyses were used to assess the contribution of dizziness handicap, illness intrusiveness, and illness uncertainty to depression. Vertigo was more intrusive than tinnitus, hearing problems, and most other comparator illnesses. The intrusiveness of the symptoms of Ménière's disease accounted for 32% of the variance in depression scores, which were high; illness uncertainty did not account for additional variance. Dizziness handicap accounted for 31% of the variation in depression. Although the symptoms of Ménière's disease may not be alleviated by psychological methods, programs that target cognitions in relation to the embarrassment in front of others, and the feeling of being handicapped, may lessen the psychosocial impact of the symptoms of Ménière's disease, which may reduce some of the depression felt in this group.

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 Distributed SQL Injection Attacks in a Eucalyptus Cloud Environment

NASA Technical Reports Server (NTRS)

Kebert, Alan; Barnejee, Bikramjit; Solano, Juan; Solano, Wanda

2013-01-01

The cloud computing environment offers malicious users the ability to spawn multiple instances of cloud nodes that are similar to virtual machines, except that they can have separate external IP addresses. In this paper we demonstrate how this ability can be exploited by an attacker to distribute his/her attack, in particular SQL injection attacks, in such a way that an intrusion detection system (IDS) could fail to identify this attack. To demonstrate this, we set up a small private cloud, established a vulnerable website in one instance, and placed an IDS within the cloud to monitor the network traffic. We found that an attacker could quite easily defeat the IDS by periodically altering its IP address. To detect such an attacker, we propose to use multi-agent plan recognition, where the multiple source IPs are considered as different agents who are mounting a collaborative attack. We show that such a formulation of this problem yields a more sophisticated approach to detecting SQL injection attacks within a cloud computing environment.

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.

AMDIS Case Conference: Intrusive Medication Safety Alerts.

PubMed

Graham, J; Levick, D; Schreiber, R

2010-01-01

Clinical decision support that provides enhanced patient safety at the point of care frequently encounters significant pushback from clinicians who find the process intrusive or time-consuming. We present a hypothetical medical center's dilemma about its allergy alerting system and discuss similar problems faced by real hospitals. We then share some lessons learned and best practices for institutions who wish to implement these tools themselves.

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

PubMed Central

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

2014-01-01

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

Seismic signature of active intrusions in mountain chains.

PubMed

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

2018-01-01

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

Seismic signature of active intrusions in mountain chains

PubMed Central

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

2018-01-01

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

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

PubMed

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

2017-03-04

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

Opportunities and Barriers to Address Seawater Intrusion Along California's Coast

NASA Astrophysics Data System (ADS)

Langridge, R.

2016-12-01

In many California coastal areas reliant on groundwater seawater intrusion is a serious problem. This presentation will discuss how particular groundwater management institutions in the state are addressing seawater intrusion issues, how stakeholders are participating in this process, and how scientific information can contribute to policies that support reducing or halting ongoing intrusion. In 2014, the California Legislature passed the Sustainable Groundwater Management Act (SGMA). The Act established requirements for 127 high and medium priority groundwater basins to form groundwater sustainability agencies (GSAs) and develop plans to sustainably manage their basin. Sustainable is defined in SGMA as avoiding specific unacceptable impacts, including significant and unreasonable seawater intrusion. Special Act Districts, created by an act of the legislature, have the option to be the sole GSA in their service area, and they can provide a window into current and potentially future strategies to address seawater intrusion. Additionally, adjudicated basins are often considered one of the best approaches to achieve efficient groundwater management, and these basins are exempt from SGMA and managed pursuant to a court judgment. The strategies utilized to manage seawater intrusion by three special act districts and five adjudicated basins will be discussed. These basins cover significant areas of central and southern California and all have experienced seawater intrusion. Our research team just completed reports for the State Water Resources Control Board on all the adjudicated and special act districts in the state, and this presentation will draw on our findings to better understand the barriers and opportunities to alleviate seawater intrusion and the information required to develop solutions.

Type D personality, stress coping strategies and self-efficacy as predictors of Facebook intrusion.

PubMed

Błachnio, Agata; Przepiorka, Aneta; Czuczwar, Stanisław Jerzy

2017-07-01

Recently, Facebook has become one of the most popular social networking sites. People use it more and more often. A number of studies have recently addressed the issue of excessive Facebook use, showing this phenomenon to be a spreading problem. The main aim of the present study was to examine whether Type D personality, self-efficacy and coping strategies are related to Facebook intrusion. The participants were 882 students of Polish universities, all of them Facebook users (72% women, mean age: 22.25 years, SD =2.06). We used the Facebook Intrusion Questionnaire, the Facebook Intensity Scale, the General Self-Efficacy Scale, the Coping Inventory for Stressful Situations, and the Type D Scale. We applied the pen-and-paper procedure. Our results indicate that emotion-oriented and avoidance-oriented strategies of coping in stressful situations are predictors of Facebook intrusion and Facebook intensity. The relations between both Facebook intrusion and intensity and social inhibition are significant only when emotion-oriented coping strategy is controlled. The knowledge of whether coping strategies in stressful situations, such as focus on emotions or avoidance, are related to Facebook intrusion might be useful for clinical purposes. Copyright © 2017 Elsevier Ireland 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

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

Non-Intrusive Techniques of Inspections During the Pre-Launch Phase of Space Vehicle

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rejkumar; Bardina, Jorge E.

2005-01-01

This paper addresses a method of non-intrusive local inspection of surface and sub-surface conditions, interfaces, laminations and seals in both space vehicle and ground operations with an integrated suite of imaging sensors during pre-launch operations. It employs an advanced Raman spectrophotometer with additional spectrophotometers and lidar mounted on a flying robot to constantly monitor the space hardware as well as inner surface of the vehicle and ground operations hardware. This paper addresses a team of micro flying robots with necessary sensors and photometers to monitor the entire space vehicle internally and externally. The micro flying robots can reach altitude with least amount of energy, where astronauts have difficulty in reaching and monitoring the materials and subsurface faults. The micro flying robot has an embedded fault detection system which acts as an advisory system and in many cases micro flying robots act as a Supervisor to fix the problems. As missions expand to a sustainable presence in the Moon, and extend for durations longer than one year in lunar outpost, the effectiveness of the instrumentation and hardware has to be revolutionized if NASA is to meet high levels of mission safety, reliability, and overall success. The micro flying robot uses contra-rotating propellers powered by an ultra-thin, ultrasonic motor with currently the world's highest power weight ratio, and is balanced in mid-air by means of the world's first stabilizing mechanism using a linear actuator. The essence of micromechatronics has been brought together in high-density mounting technology to minimize the size and weight. The robot can take suitable payloads of photometers, embedded chips for image analysis and micro pumps for sealing cracks or fixing other material problems. This paper also highlights advantages that this type of non-intrusive techniques offer over costly and monolithic traditional techniques.

Assessing security technology's impact: old tools for new problems.

PubMed

Kreissl, Reinhard

2014-09-01

The general idea developed in this paper from a sociological perspective is that some of the foundational categories on which the debate about privacy, security and technology rests are blurring. This process is a consequence of a blurring of physical and digital worlds. In order to define limits for legitimate use of intrusive digital technologies, one has to refer to binary distinctions such as private versus public, human versus technical, security versus insecurity to draw differences determining limits for the use of surveillance technologies. These distinctions developed in the physical world and are rooted in a cultural understanding of pre-digital culture. Attempts to capture the problems emerging with the implementation of security technologies using legal reasoning encounter a number of problems since law is by definition oriented backwards, adapting new developments to existing traditions, whereas the intrusion of new technologies in the physical world produces changes and creates fundamentally new problems.

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

PubMed

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

2007-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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.

Executive functions in adolescents with spina bifida: relations with autonomy development and parental intrusiveness.

PubMed

Tuminello, Elizabeth R; Holmbeck, Grayson N; Olson, Rick

2012-01-01

The current study was part of a larger longitudinal investigation and examined the relation of parent-report and performance measures of executive functioning (EF) with measures of behavioral and emotional autonomy and parental intrusiveness in adolescents with and without spina bifida (SB; n=65 in a comparison sample and 61 in an SB sample; M age=14.55, SD=0.63). For both groups, higher levels of parent-reported EF problems predicted higher levels of observed child dependency and lower levels of teacher-reported intrinsic motivation. Higher scores on performance EF measures predicted lower levels of observed child dependency and observed maternal intrusiveness for both groups. In adolescents with SB only, higher performance EF scores predicted higher intrinsic motivation and emotional autonomy from both mother and father and predicted lower levels of observed paternal intrusiveness. While causal conclusions cannot be drawn, EFs appear to be closely related to autonomy development and parental intrusiveness, particularly for adolescents with SB. These results suggest that the inclusion of EF training in interventions targeting adolescents with SB may be beneficial for autonomy development.

Surveillance for unattended gas compressor stations

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

Stastny, F.J.

1974-06-01

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

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

DOEpatents

Piper, T.C.

1980-09-24

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

Vapor intrusion risk of lead scavengers 1,2-dibromoethane (EDB) and 1,2-dichloroethane (DCA).

PubMed

Ma, Jie; Li, Haiyan; Spiese, Richard; Wilson, John; Yan, Guangxu; Guo, Shaohui

2016-06-01

Vapor intrusion of synthetic fuel additives represented a critical yet still neglected problem at sites impacted by petroleum fuel releases. This study used an advanced numerical model to simulate the vapor intrusion risk of lead scavengers 1,2-dibromoethane (ethylene dibromide, EDB) and 1,2-dichloroethane (DCA) under different site conditions. We found that simulated EDB and DCA indoor air concentrations can exceed USEPA screening level (4.7 × 10(-3) μg/m(3) for EDB and 1.1 × 10(-1) μg/m(3) for DCA) if the source concentration is high enough (is still within the concentration range found at leaking UST site). To evaluate the chance that vapor intrusion of EDB might exceed the USEPA screening levels for indoor air, the simulation results were compared to the distribution of EDB at leaking UST sites in the US. If there is no degradation of EDB or only abiotic degradation of EDB, from 15% to 37% of leaking UST sites might exceed the USEPA screening level. This study supports the statements made by USEPA in the Petroleum Vapor Intrusion (PVI) Guidance that the screening criteria for petroleum hydrocarbon may not provide sufficient protectiveness for fuel releases containing EDB and DCA. Based on a thorough literature review, we also compiled previous published data on the EDB and DCA groundwater source concentrations and their degradation rates. These data are valuable in evaluating EDB and DCA vapor intrusion risk. In addition, a set of refined attenuation factors based on site-specific information (e.g., soil types, source depths, and degradation rates) were provided for establishing site-specific screening criteria for EDB and DCA. Overall, this study points out that lead scavengers EDB and DCA may cause vapor intrusion problems. As more field data of EDB and DCA become available, we recommend that USEPA consider including these data in the existing PVI database and possibly revising the PVI Guidance as necessary. Copyright © 2016 Elsevier Ltd. All rights reserved.

The political and legal aspects of space applications

NASA Technical Reports Server (NTRS)

Hanessian, J., Jr.

1972-01-01

The political and legal repercussions of space programs both domestic and foreign are explored. Emphasis are placed on earth resources exploration (exploration based on information rights), jurisdictional problems, problems of sharing space benefits with other countries, criminal launch and use of satellites, intrusion into territorial sovereignty, and problems of establishing data ownership.

Non-intrusive measurements of frictional forces between micro-spheres and flat surfaces

NASA Astrophysics Data System (ADS)

Lin, Wei-Hsun; Daraio, Chiara; Daraio's Group Team

2014-03-01

We report a novel, optical pump-probe experimental setup to study micro-friction phenomena between micro-particles and a flat surface. We present a case study of stainless steel microspheres, of diameter near 250 μm, in contact with different surfaces of variable roughness. In these experiments, the contact area between the particles and the substrates is only a few nanometers wide. To excite the particles, we deliver an impulse using a pulsed, high-power laser. The reaction force resulting from the surface ablation induced by the laser imparts a controlled initial velocity to the target particle. This initial velocity can be varied between 10-5 to 1 m/s. We investigate the vibrating and rolling motions of the micro-particles by detecting their velocity and displacement with a laser vibrometer and a high-speed microscope camera. We calculate the effective Hamaker constant from the vibrating motion of a particle, and study its relation to the substrate's surface roughness. We analyze the relation between rolling friction and the minimum momentum required to break surface bonding forces. This non-contact and non-intrusive technique could be employed to study a variety of contact and tribology problems at the microscale.

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...

Analysis of an algorithm for distributed recognition and accountability

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

Ko, C.; Frincke, D.A.; Goan, T. Jr.

1993-08-01

Computer and network systems are available to attacks. Abandoning the existing huge infrastructure of possibly-insecure computer and network systems is impossible, and replacing them by totally secure systems may not be feasible or cost effective. A common element in many attacks is that a single user will often attempt to intrude upon multiple resources throughout a network. Detecting the attack can become significantly easier by compiling and integrating evidence of such intrusion attempts across the network rather than attempting to assess the situation from the vantage point of only a single host. To solve this problem, we suggest an approachmore » for distributed recognition and accountability (DRA), which consists of algorithms which ``process,`` at a central location, distributed and asynchronous ``reports`` generated by computers (or a subset thereof) throughout the network. Our highest-priority objectives are to observe ways by which an individual moves around in a network of computers, including changing user names to possibly hide his/her true identity, and to associate all activities of multiple instance of the same individual to the same network-wide user. We present the DRA algorithm and a sketch of its proof under an initial set of simplifying albeit realistic assumptions. Later, we relax these assumptions to accommodate pragmatic aspects such as missing or delayed ``reports,`` clock slew, tampered ``reports,`` etc. We believe that such algorithms will have widespread applications in the future, particularly in intrusion-detection system.« less

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

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

NASA Astrophysics Data System (ADS)

Hu, Haibin

2017-05-01

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

Characterizing and Improving Distributed Intrusion Detection Systems.

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

Hurd, Steven A; Proebstel, Elliot P.

2007-11-01

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

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

NASA Astrophysics Data System (ADS)

Zhou, Mian; Lang, Sheau-Dong

2005-03-01

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

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.

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.

Testing specificity among parents' depressive symptoms, parenting, and child internalizing and externalizing symptoms.

PubMed

Gruhn, Meredith A; Dunbar, Jennifer P; Watson, Kelly H; Reising, Michelle M; McKee, Laura; Forehand, Rex; Cole, David A; Compas, Bruce E

2016-04-01

The present study examined the specificity in relations between observed withdrawn and intrusive parenting behaviors and children's internalizing and externalizing symptoms in an at-risk sample of children (ages 9 to 15 years old) of parents with a history of depression (N = 180). Given past findings that parental depression and parenting behaviors may differentially impact boys and girls, gender was examined as a moderator of the relations between these factors and child adjustment. Correlation and linear regression analyses showed that parental depressive symptoms were significantly related to withdrawn parenting for parents of boys and girls and to intrusive parenting for parents of boys only. When controlling for intrusive parenting, preliminary analyses demonstrated that parental depressive symptoms were significantly related to withdrawn parenting for parents of boys, and this association approached significance for parents of girls. Specificity analyses yielded that, when controlling for the other type of problem (i.e., internalizing or externalizing), withdrawn parenting specifically predicted externalizing problems but not internalizing problems in girls. No evidence of specificity was found for boys in this sample, suggesting that impaired parenting behaviors are diffusely related to both internalizing and externalizing symptoms for boys. Overall, results highlight the importance of accounting for child gender and suggest that targeting improvement in parenting behaviors and the reduction of depressive symptoms in interventions with parents with a history of depression may have potential to reduce internalizing and externalizing problems in this high-risk population. (c) 2016 APA, all rights reserved).

Testing Specificity Among Parents’ Depressive Symptoms, Parenting, and Child Internalizing and Externalizing Symptoms

PubMed Central

Gruhn, Meredith A.; Dunbar, Jennifer P.; Watson, Kelly H.; Reising, Michelle M.; McKee, Laura; Forehand, Rex; Cole, David A.; Compas, Bruce E.

2016-01-01

The present study examined the specificity in relations between observed withdrawn and intrusive parenting behaviors and children's internalizing and externalizing symptoms in an at risk sample of children (ages 9 to 15-years-old) of parents with a history of depression (N = 180). Given past findings that parental depression and parenting behaviors may differentially impact boys and girls, gender was examined as a moderator of the relations between these factors and child adjustment. Correlation and linear regression analyses showed that parental depressive symptoms were significantly related to withdrawn parenting for parents of boys and girls and to intrusive parenting for parents of boys only. When controlling for intrusive parenting, preliminary analyses demonstrated that parental depressive symptoms were significantly related to withdrawn parenting for parents of boys, and this association approached significance for parents of girls. Specificity analyses yielded that, when controlling for the other type of problem (i.e., internalizing or externalizing), withdrawn parenting specifically predicted externalizing problems but not internalizing problems in girls. No evidence of specificity was found for boys in this sample, suggesting that impaired parenting behaviors are diffusely related to both internalizing and externalizing symptoms for boys. Overall, results highlight the importance of accounting for child gender and suggest that targeting improvement in parenting behaviors and the reduction of depressive symptoms in interventions with parents with a history of depression may have potential to reduce internalizing and externalizing problems in this high-risk population. PMID:26882467

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.

College Students' Integration of Education and Employment: Perceived Intrusion of Personal Problems in the Workplace.

ERIC Educational Resources Information Center

Chavous, Dawn; Chambliss, Catherine

In this study students' perceptions of the workplace were analyzed to see how personal problems affected work ability. It was hypothesized that personal problems negatively affect students' ability to complete various types of tasks at work. It was also hypothesized that regardless of their attitudes toward the work environment, the more…

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

Volumetric Security Alarm Based on a Spherical Ultrasonic Transducer Array

NASA Astrophysics Data System (ADS)

Sayin, Umut; Scaini, Davide; Arteaga, Daniel

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

Non-intrusive appliance monitor apparatus

DOEpatents

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

1989-08-15

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

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.

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.

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...

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

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

NASA Astrophysics Data System (ADS)

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

2007-07-01

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

Dynamics of large-diameter water pipes in hydroelectric power plants

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Robotic guarded motion system and method

DOEpatents

Bruemmer, David J.

2010-02-23

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

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Multi-User Low Intrusive Occupancy Detection

PubMed Central

Widyawan, Widyawan; Lazovik, Alexander

2018-01-01

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

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

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Internet use, Facebook intrusion, and depression: Results of a cross-sectional study.

PubMed

Błachnio, A; Przepiórka, A; Pantic, I

2015-09-01

Facebook has become a very popular social networking platform today, particularly among adolescents and young adults, profoundly changing the way they communicate and interact. However, some reports have indicated that excessive Facebook use might have detrimental effects on mental health and be associated with certain psychological problems. Because previous findings on the relationship between Facebook addiction and depression were not unambiguous, further investigation was required. The main objective of our study was to examine the potential associations between Internet use, depression, and Facebook intrusion. A total of 672 Facebook users took part in the cross-sectional study. The Facebook Intrusion Questionnaire and the Center for Epidemiologic Studies Depression Scale were used. For collecting the data, the snowball sampling procedure was used. We showed that depression can be a predictor of Facebook intrusion. Our results provides additional evidence that daily Internet use time in minutes, gender, and age are also predictors of Facebook intrusion: that Facebook intrusion can be predicted by being male, young age, and an extensive number of minutes spent online. On the basis of this study, it is possible to conclude that there are certain demographic - variables, such as age, gender, or time spent online - that may help in outlining the profile of a user who may be in danger of becoming addicted to Facebook. This piece of knowledge may serve for prevention purposes. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

A 2D fluid motion model of the estuarine water circulation: Physical analysis of the salinity stratification in the Sebou estuary

NASA Astrophysics Data System (ADS)

Haddout, Soufiane; Maslouhi, Abdellatif; Magrane, Bouchaib

2018-02-01

Estuaries, which are coastal bodies of water connecting the riverine and marine environment, are among the most important ecosystems in the world. Saltwater intrusion is the movement of coastal saline water into an estuary, which makes up-estuary water, that becomes salty due to the mixing of freshwater with saltwater. It has become a serious environmental problem in the Sebou estuary (Morocco) during wet and dry seasons, which have a considerable impact on residential water supply, agricultural water supply as well as urban industrial production. The variations of salt intrusion, and the vertical stratification under different river flow conditions in the Sebou estuary were investigated in this paper using a two-dimensional numerical model. The model was calibrated and verified against water level variation, and salinity variation during 2016, respectively. Additionally, the model validation process showed that the model results fit the observed data fairly well ( R2 > 0.85, NSC > 0.89 and RMSE = 0.26 m). Model results show that freshwater is a dominant influencing factor to the saltwater intrusion and controlled salinity structure, vertical stratification and length of the saltwater intrusion. Additionally, the extent of salinity intrusion depends on the balance between fresh water discharges and saltwater flow from the sea. This phenomenon can be reasonably predicted recurring to mathematical models supported by monitored data. These tools can be used to quantify how much fresh water is required to counterbalance salinity intrusion at the upstream water intakes.

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.

The Problem of Pseudoscience in Science Education and Implications of Constructivist Pedagogy

ERIC Educational Resources Information Center

Mugaloglu, Ebru Z.

2014-01-01

The intrusion of pseudoscience into science classrooms is a problem in science education today. This paper discusses the implications of constructivist pedagogy, which relies on the notions of viability and inter-subjectivity, in a context favourable to the acceptance of pseudoscience. Examples from written statements illustrate how prospective…

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.

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.

Nocturnal insomnia symptoms and stress-induced cognitive intrusions in risk for depression: A 2-year prospective study

PubMed Central

Pillai, Vivek; Drake, Christopher L.

2018-01-01

Nearly half of US adults endorse insomnia symptoms. Sleep problems increase risk for depression during stress, but the mechanisms are unclear. During high stress, individuals having difficulty falling or staying asleep may be vulnerable to cognitive intrusions after stressful events, given that the inability to sleep creates a period of unstructured and socially isolated time in bed. We investigated the unique and combined effects of insomnia symptoms and stress-induced cognitive intrusions on risk for incident depression. 1126 non-depressed US adults with no history of DSM-5 insomnia disorder completed 3 annual web-based surveys on sleep, stress, and depression. We examined whether nocturnal insomnia symptoms and stress-induced cognitive intrusions predicted depression 1y and 2y later. Finally, we compared depression-risk across four groups: non-perseverators with good sleep, non-perseverators with insomnia symptoms, perseverators with good sleep, and perseverators with insomnia symptoms. Insomnia symptoms (β = .10–.13, p < .001) and cognitive intrusions (β = .19–.20, p < .001) predicted depression severity 1y and 2y later. Depression incidence across 2 years was 6.2%. Perseverators with insomnia had the highest rates of depression (13.0%), whereas good sleeping non-perseverators had the lowest rates (3.3%, Relative Risk = 3.94). Perseverators with sleep latency >30 m reported greater depression than good sleeping perseverators (t = 2.09, p < .04). Cognitive intrusions following stress creates a depressogenic mindset, and nocturnal wakefulness may augment the effects of cognitive arousal on depression development. Poor sleepers may be especially vulnerable to cognitive intrusions when having difficulty initiating sleep. As treatable behaviors, nighttime wakefulness and cognitive arousal may be targeted to reduce risk for depression in poor sleepers. PMID:29438400

Nocturnal insomnia symptoms and stress-induced cognitive intrusions in risk for depression: A 2-year prospective study.

PubMed

Kalmbach, David A; Pillai, Vivek; Drake, Christopher L

2018-01-01

Nearly half of US adults endorse insomnia symptoms. Sleep problems increase risk for depression during stress, but the mechanisms are unclear. During high stress, individuals having difficulty falling or staying asleep may be vulnerable to cognitive intrusions after stressful events, given that the inability to sleep creates a period of unstructured and socially isolated time in bed. We investigated the unique and combined effects of insomnia symptoms and stress-induced cognitive intrusions on risk for incident depression. 1126 non-depressed US adults with no history of DSM-5 insomnia disorder completed 3 annual web-based surveys on sleep, stress, and depression. We examined whether nocturnal insomnia symptoms and stress-induced cognitive intrusions predicted depression 1y and 2y later. Finally, we compared depression-risk across four groups: non-perseverators with good sleep, non-perseverators with insomnia symptoms, perseverators with good sleep, and perseverators with insomnia symptoms. Insomnia symptoms (β = .10-.13, p < .001) and cognitive intrusions (β = .19-.20, p < .001) predicted depression severity 1y and 2y later. Depression incidence across 2 years was 6.2%. Perseverators with insomnia had the highest rates of depression (13.0%), whereas good sleeping non-perseverators had the lowest rates (3.3%, Relative Risk = 3.94). Perseverators with sleep latency >30 m reported greater depression than good sleeping perseverators (t = 2.09, p < .04). Cognitive intrusions following stress creates a depressogenic mindset, and nocturnal wakefulness may augment the effects of cognitive arousal on depression development. Poor sleepers may be especially vulnerable to cognitive intrusions when having difficulty initiating sleep. As treatable behaviors, nighttime wakefulness and cognitive arousal may be targeted to reduce risk for depression in poor sleepers.

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

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.

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

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…

Human-machine analytics for closed-loop sense-making in time-dominant cyber defense problems

NASA Astrophysics Data System (ADS)

Henry, Matthew H.

2017-05-01

Many defense problems are time-dominant: attacks progress at speeds that outpace human-centric systems designed for monitoring and response. Despite this shortcoming, these well-honed and ostensibly reliable systems pervade most domains, including cyberspace. The argument that often prevails when considering the automation of defense is that while technological systems are suitable for simple, well-defined tasks, only humans possess sufficiently nuanced understanding of problems to act appropriately under complicated circumstances. While this perspective is founded in verifiable truths, it does not account for a middle ground in which human-managed technological capabilities extend well into the territory of complex reasoning, thereby automating more nuanced sense-making and dramatically increasing the speed at which it can be applied. Snort1 and platforms like it enable humans to build, refine, and deploy sense-making tools for network defense. Shortcomings of these platforms include a reliance on rule-based logic, which confounds analyst knowledge of how bad actors behave with the means by which bad behaviors can be detected, and a lack of feedback-informed automation of sensor deployment. We propose an approach in which human-specified computational models hypothesize bad behaviors independent of indicators and then allocate sensors to estimate and forecast the state of an intrusion. State estimates and forecasts inform the proactive deployment of additional sensors and detection logic, thereby closing the sense-making loop. All the while, humans are on the loop, rather than in it, permitting nuanced management of fast-acting automated measurement, detection, and inference engines. This paper motivates and conceptualizes analytics to facilitate this human-machine partnership.

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.

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.

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

PubMed

Noto, Keith; Brodley, Carla; Slonim, Donna

2012-01-01

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

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

PubMed Central

Brodley, Carla; Slonim, Donna

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

Chen, Siyue; Leung, Henry; Dondo, Maxwell

2014-05-01

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

Layered intrusion formation by top down thermal migration zone refining (Invited)

NASA Astrophysics Data System (ADS)

Lundstrom, C.

2009-12-01

The formation of layered mafic intrusions by crystallization from cooling magmas represents the textbook example of igneous differentiation, often attributed to fractional crystallization through gravitational settling. Yet in detail, such interpretations have significant problems such that it remains unclear how these important features form. Put in the Earth perspective that no km scale blob of >50% melt has ever been imaged geophysically and that geochronological studies repeatedly indicate age inconsistencies with “big tank” magma chambers, it may be questioned if km scale magma chambers have ever existed. I will present the case for forming layered intrusions by a top down process whereby arriving basaltic magma reaches a permeability barrier, begins to underplate and forms the intrusion incrementally by sill injection with the body growing downward at ~1 mm/yr rate or less. A temperature gradient zone occurs in the overlying previously emplaced sills, leading to chemical components migrating by diffusion. As long as the rate of diffusion can keep up with rate of sill addition, the body will differentiate along a path similar to a liquid line of descent. In this talk, I will integrate data from 3 areas: 1) laboratory experiments examining the behavior of partially molten silicates in a temperature gradient (thermal migration); 2) numerical modeling of the moving temperature gradient zone process using IRIDIUM (Boudreau, 2003); 3) measurements of Fe isotope ratios and geochronology from the Sonju Lake Intrusion in the Duluth Complex. This model provides the ability to form km scale intrusions by a seismically invisible means, can explain million year offsets in chronology, and has implications for reef development and PGE concentration. Most importantly, this model of top down layered intrusion formation, following a similar recent proposal for granitoid formation (Lundstrom, 2009), represents a testable hypothesis: because temperature gradient driven diffusion leads to the prediction of heavy isotope ratios near the top of the intrusion and light ratios near the bottom of the intrusion, analyses of Fe, Mg and Si isotopes provide an important new tool for examining igneous differentiation.

Clinical report--the evaluation of sexual behaviors in children.

PubMed

Kellogg, Nancy D

2009-09-01

Most children will engage in sexual behaviors at some time during childhood. These behaviors may be normal but can be confusing and concerning to parents or disruptive or intrusive to others. Knowledge of age-appropriate sexual behaviors that vary with situational and environmental factors can assist the clinician in differentiating normal sexual behaviors from sexual behavior problems. Most situations that involve sexual behaviors in young children do not require child protective services intervention; for behaviors that are age-appropriate and transient, the pediatrician may provide guidance in supervision and monitoring of the behavior. If the behavior is intrusive, hurtful, and/or age-inappropriate, a more comprehensive assessment is warranted. Some children with sexual behavior problems may reside or have resided in homes characterized by inconsistent parenting, violence, abuse, or neglect and may require more immediate intervention and referrals.

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

Comparing Cognitive, Relational and Stress Mechanisms Underlying Gender Differences in Recovery from Bereavement-Related Internalizing Problems

ERIC Educational Resources Information Center

Little, Michelle; Sandler, Irwin N.; Wolchik, Sharlene A.; Tein, Jenn-Yun; Ayers, Tim S.

2009-01-01

Four putative mediators underlying gender differences in youths' recovery from bereavement-related internalizing problems were examined in a sample (N = 109; age range = 8-16 years at the initial assessment) of parentally bereaved youth: intrusive thoughts about grief, postdeath stressors, negative appraisals of postdeath stressors, and fear of…

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.

Exposure to Violence, Social Cognitive Processing, and Sleep Problems in Urban Adolescents

PubMed Central

Kliewer, Wendy; Lepore, Stephen J.

2014-01-01

Exposure to violence is associated with elevated levels of sleep problems in adolescence, which contributes to poor mental and physical health and impaired academic performance. However, reasons underlying the associations between exposure to violence and sleep difficulty have not been examined. This study tested a social cognitive processing path model linking experiences of witnessing and directly experiencing community violence and sleep problems. Participants were 362 early adolescents (M age = 12.45 yrs, SD = 0.59; Range 11 to 14 yrs; 48.9% male; 51% Latino/a; 34% black) from urban communities enrolled in a middle-school-based intervention study on the east coast of the United States that was designed to reduce the negative effects of exposure to violence. All youth in the current study reported witnessing or directly experiencing community violence. Adolescents completed four school-based assessments over an 18-month period, reporting on their exposure to community violence, sleep problems, intrusive thoughts about and social constraints in talking about violence, and life events. A path model that included both victimization and witnessing violence revealed that wave 1 witnessing violence, but not victimization, was associated with elevated social constraints in talking about violence at wave 2, which was associated with elevated intrusive thoughts at wave 3, which was associated with poor sleep quality at wave 4. Prior levels of all constructs were controlled in the analysis, in addition to life events, single parent household status, children’s age and sex, intervention condition, and school. Youth exposed to violence may benefit from help in processing their experiences, thus reducing social constraints in talking about their experiences and associated intrusive thoughts. This is turn may improve sleep outcomes. PMID:25218396

Exposure to violence, social cognitive processing, and sleep problems in urban adolescents.

PubMed

Kliewer, Wendy; Lepore, Stephen J

2015-02-01

Exposure to violence is associated with elevated levels of sleep problems in adolescence, which contributes to poor mental and physical health and impaired academic performance. However, reasons underlying the associations between exposure to violence and sleep difficulty have not been examined. This study tested a social cognitive processing path model linking experiences of witnessing and directly experiencing community violence and sleep problems. Participants were 362 early adolescents (M age = 12.45 years, SD = 0.59; range 11-14 years; 48.9% male; 51% Latino/a; 34% black) from urban communities enrolled in a middle-school-based intervention study on the east coast of the United States that was designed to reduce the negative effects of exposure to violence. All youth in the current study reported witnessing or directly experiencing community violence. Adolescents completed four school-based assessments over an 18-month period, reporting on their exposure to community violence, sleep problems, intrusive thoughts about and social constraints in talking about violence, and life events. A path model that included both victimization and witnessing violence revealed that wave 1 witnessing violence, but not victimization, was associated with elevated social constraints in talking about violence at wave 2, which was associated with elevated intrusive thoughts at wave 3, which was associated with poor sleep quality at wave 4. Prior levels of all constructs were controlled in the analysis, in addition to life events, single parent household status, children's age and sex, intervention condition, and school. Youth exposed to violence may benefit from help in processing their experiences, thus reducing social constraints in talking about their experiences and associated intrusive thoughts. This is turn may improve sleep outcomes.

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

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.

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.

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.

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.

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.

Linking magnetic fabric and cumulate texture in layered mafic-ultramafic intrusions (Invited)

NASA Astrophysics Data System (ADS)

O Driscoll, B.; Stevenson, C.; Magee, C.

2013-12-01

Research on the magnetic fabrics of igneous rocks, pioneered by Balsley and Buddington[1] and Khan[2], has greatly contributed to our understanding of magma dynamics in lava flows, sheet intrusions and plutons over the past five decades. However, considerably few magnetic fabric studies have focused on layered mafic-ultramafic intrusions, particularly ';lopolithic' intrusions, despite the fact that such rocks may preserve a large range of small-scale kinematic structures potentially related to important magma chamber processes. This may be partly due to the fact that mafic-ultramafic cumulates commonly exhibit visible planar fabrics (mineral lamination), as well as compositional layering, in contrast to the frequent absence of such features in granite bodies or fine-grained mafic lava flows. Indeed, debates in the 1970s and 1980s on the development of layering and mineral fabrics in mafic-ultramafic intrusions, focused around the crystal settling versus in situ crystallisation paradigms, are classic in the subject of igneous petrology. Central to these debates is the notion that a wide range of magma chamber processes occur in layered mafic-ultramafic intrusions that are not frequently considered to occur in their relatively viscous granitic counterparts; in essence, the latter have historically been viewed as much more likely to ';freeze-in' a primary magma flow fabric whilst mafic-ultramafic intrusions are subjected to a more protracted solidification history. This wide array of potential initial sources for layering and mineral fabrics in layered mafic-ultramafic intrusions, together with the possible modification of textures at the postcumulus stage, demands a cautious application of any fabric analysis and presents a problem well-suited to interrogation by the AMS technique. The purpose of this contribution is to provide specific context on the application of AMS to elucidating the formation of cumulates in layered mafic-ultramafic intrusions. Examples of AMS data from a suite of different cumulate textures are discussed and some obstacles and issues surrounding interpretation of these magnetic fabrics are explored. The integration of the AMS technique with several complementary tools, including quantitative measurements of crystal size and shape, is also evaluated with reference to several well-studied layered intrusions. Finally, some perspectives are offered on future applications and directions for the measurement and interpretation of magnetic fabrics in layered intrusions. [1] Balsley and Buddington (1960) American Journal of Science A258, 6-20. [2] Khan (1962) Journal of Geophysical Research 67, 2873-2885

Numerical Study of Groundwater Flow and Salinity Distribution Cycling Controlled by Seawater/Freshwater Interaction in Karst Aquifer Using SEAWAT

NASA Astrophysics Data System (ADS)

Xu, Z.; Hu, B.

2017-12-01

The interest to predict seawater intrusion and salinity distribution in Woodville Karst Plain (WKP) has increased due to the huge challenge on quality of drinkable water and serious environmental problems. Seawater intrudes into the conduit system from submarine karst caves at Spring Creek Spring due to density difference and sea level rising, nowadays the low salinity has been detected at Wakulla Spring which is 18 km from coastal line. The groundwater discharge at two major springs and salinity distribution in this area is controlled by the seawater/freshwater interaction under different rainfall conditions: during low rainfall periods, seawater flow into the submarine spring through karst windows, then the salinity rising at the submarine spring leads to seawater further intrudes into conduit system; during high rainfall periods, seawater is pushed out by fresh water discharge at submarine spring. The previous numerical studies of WKP mainly focused on the density independent transport modeling and seawater/freshwater discharge at major karst springs, in this study, a SEAWAT model has been developed to fully investigate the salinity distribution in the WKP under repeating phases of low rainfall and high rainfall periods, the conduit system was simulated as porous media with high conductivity and porosity. The precipitation, salinity and discharge at springs were used to calibrate the model. The results showed that the salinity distribution in porous media and conduit system is controlled by the rainfall change, in general, the salinity distribution inland under low rainfall conditions is much higher and wider than the high rainfall conditions. The results propose a prediction on the environmental problem caused by seawater intrusion in karst coastal aquifer, in addition, provide a visual and scientific basis for future groundwater remediation.

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.

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.

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

Analytical and numerical study of the salinity intrusion in the Sebou river estuary (Morocco) - effect of the "Super Blood Moon" (total lunar eclipse) of 2015

NASA Astrophysics Data System (ADS)

Haddout, Soufiane; Igouzal, Mohammed; Maslouhi, Abdellatif

2016-09-01

The longitudinal variation of salinity and the maximum salinity intrusion length in an alluvial estuary are important environmental concerns for policy makers and managers since they influence water quality, water utilization and agricultural development in estuarine environments and the potential use of water resources in general. The supermoon total lunar eclipse is a rare event. According to NASA, they have only occurred 5 times in the 1900s - in 1910, 1928, 1946, 1964 and 1982. After the 28 September 2015 total lunar eclipse, a Super Blood Moon eclipse will not recur before 8 October 2033. In this paper, for the first time, the impact of the combination of a supermoon and a total lunar eclipse on the salinity intrusion along an estuary is studied. The 28 September 2015 supermoon total lunar eclipse is the focus of this study and the Sebou river estuary (Morocco) is used as an application area. The Sebou estuary is an area with high agricultural potential, is becoming one of the most important industrial zones in Morocco and it is experiencing a salt intrusion problem. Hydrodynamic equations for tidal wave propagation coupled with the Savenije theory and a numerical salinity transport model (HEC-RAS software "Hydrologic Engineering Center River Analysis System") are applied to study the impact of the supermoon total lunar eclipse on the salinity intrusion. Intensive salinity measurements during this extreme event were recorded along the Sebou estuary. Measurements showed a modification of the shape of axial salinity profiles and a notable water elevation rise, compared with normal situations. The two optimization parameters (Van der Burgh's and dispersion coefficients) of the analytical model are estimated based on the Levenberg-Marquardt's algorithm (i.e., solving nonlinear least-squares problems). The salinity transport model was calibrated and validated using field data. The results show that the two models described very well the salt intrusion during the supermoon total lunar eclipse day. A good fit between computed salinity and measurements is obtained, as verified by statistical performance tests. These two models can give a rapid assessment of salinity distribution and consequently help to ensure the safety of the water supply, even during such infrequent astronomical phenomenon.

Intrusions of Modernity on a Traditional Culture.

ERIC Educational Resources Information Center

Thomas, Anne Horsfall

1991-01-01

Presents a teacher's impressions of India, gathered during a Fulbright-sponsored study tour. Examines modernizing influences in the midst of traditional culture, religious cultural groups and potential religious conflict, women's status, and problems due to overpopulation. (CH)

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.

Stochastic reduced order models for inverse problems under uncertainty

PubMed Central

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

2014-01-01

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

The reason for a Daly gap in magmatic series of large igneous provinces: geological and petrological evidences

NASA Astrophysics Data System (ADS)

Sharkov, Evgenii; Bogina, Maria; Chistyakov, Alexeii

2017-04-01

One of the most important problems of magmatic petrology over the past century is a «Daly Gap» [Daly, 1914]. It describes the lack of intermediate compositions (i.e., andesite, trachyandesite) in volcanic provinces like ocean islands, LIPs, & arcs, giving rise to "bimodal" basalt-rhyolite, basalt-trachyte or basanite-phonolite suites (Menzies, 2016). At the same time, the origin of the bimodal distribution still remains unclear. Among models proposed to explain the origin of the bimodal series are liquid immiscibility (Charlier et al 2011), physico-chemical specifics of melts (Mungal, Martin,1995), high water content in a primary melt (Melekhova et al., 2012), influence of latent heat production (Nelson et al., 2011), appearance of differentiated transitional chambers with hawaiites below and trachytes on top (Ferla et al., 2006), etc. In this case, the bimodal series are characterized by similar geochemical and isotopic-geochemical features of mafic and sialic members. At the same time, some bimodal series are produced by melting of sialic crust over basaltic chambers (Philpottas and Ague, 2009). This results in the essentially different isotopic characteristics of mafic and sialic members, as exemplified by the bimodal rapakivi granites-anorthosite complexes (Ramo, 1991; Sharkov, 2010). In addition, the bimodal basalt-trachyte series are widely spread in oceanic islands where sialic crust is absent. Thus, it is generally accepted that two contrasting melts were formed in magma chambers beneath volcanoes. Such chambers survived as intrusions and are available for geological study and deciphering their role in the formation of the bimodal magmatic series. We discuss this problem by the example of alkali Fe-Ti basalts and trachytes usually developed in LIPs. Transitional magmatic chambers of such series are represented by bimodal syenite-gabbro intrusions, in particular, by the Elet'ozero intrusion (2086±30 Ma) in Northern Karelia (Russia). The intrusion intruded Archean granite-gneisses and, like syenite-gabbro intrusive complexes everywhere, was formed in two intrusive phases. The first phase is represented by mafic-ultramafic layered intrusion derived from alkali Fe-Ti basalt. The second phase is made up of alkali syenites, which are close in composition to alkali trachyte. At the same time, syenite and gabbro have close ɛNd(2080) (2.99 and 3.09, respectively). So, we faced the intrusive version of alkali basalt-trachyte series. We believe that neither crystallization differentiation, nor immiscible splitting, nor other within-chamber processes were responsible for a Daly Gap. The formation of the latter is rather related to the generation of two compositionally different independent partial melts from the same mantle plume head: (1) alkali Fe-Ti basalts derived from plume head owing to adiabatic melting, and (2) trachytes produced by incongruent melting of upper cooled margin of the head under the influence of fluids, which percolated from underlying adiabatic melting zone. The existence of primary trachyte melts is supported by the finds of "melt pockets" in mantle xenoliths in basalts.

Fear of cancer progression and cancer-related intrusive cognitions in breast cancer survivors.

PubMed

Mehnert, Anja; Berg, Petra; Henrich, Gerhard; Herschbach, Peter

2009-12-01

To assess the character and frequency of fear of progression (FoP) and to clarify its relationship with cancer-related intrusive cognitions in breast cancer survivors. A sample of 1083 patients was recruited in this cross-sectional study through a population-based Cancer Registry an average of 47 month following diagnosis (66% response rate). Participants completed self-report measures assessing fear of cancer progression (FoP-Q-SF), posttraumatic stress-disorder symptoms (PCL-C), coping strategies (DWI) and quality of life (QoL) (SF-8). In total, 23.6% of women were classified as having moderate to high FoP. Being nervous prior to doctors' appointments or examinations and being afraid of relying on strangers for activities of daily living were the most frequent fears. FoP was significantly associated with younger age, having children, disease progress, chemotherapy, perceived amount of impairments, physical and mental QoL, but not with time since initial diagnosis. Intrusive cognitions were screened in 37% of the sample. We found significant correlations between FoP and intrusive thoughts (r=0.63), avoidance (r=0.57), hyperarousal (r=0.54) and posttraumatic stress disorder diagnosis (r=0.42). Factors significantly associated with moderate and high FoP included a depressive coping style as well as an active problem-oriented coping style, intrusion, avoidance and hyperarousal symptoms (Nagelkerke's R(2)=0.44). Findings of this study give information regarding the frequency and the character of anxiety in breast cancer survivors and underline the relation of FoP to the reality of living with breast cancer. Results suggest that intrusive cognitions as well as avoidance and hyperarousal symptoms seem to be closely related to future-oriented fears of cancer recurrence.

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

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.

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.

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.

Subsurface Intrusion Detection System

DTIC Science & Technology

2014-02-25

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

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

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

Potential for portal detection of human chemical and biological contamination

NASA Astrophysics Data System (ADS)

Settles, Gary S.; McGann, William J.

2001-08-01

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

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

LaFreniere, L. M.; Environmental Science Division

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

IDAS : ITS Deployment Analysis System

DOT National Transportation Integrated Search

1997-05-01

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

RTO Technical Report: A Quarterly Listing

NASA Technical Reports Server (NTRS)

2002-01-01

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

Effectiveness of Audible Warning Devices on Emergency Vehicles.

DOT National Transportation Integrated Search

1977-08-01

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

Geochemical and isotopic data for restricting seawater intrusion and groundwater circulation in a series of typical volcanic islands in the South China Sea.

PubMed

Zhang, Wenjie; Chen, Xi; Tan, Hongbing; Zhang, Yanfei; Cao, Jifu

2015-04-15

The decline of groundwater table and deterioration of water quality related to seawater have long been regarded as a crucial problem in coastal regions. In this work, a hydrogeologic investigation using combined hydrochemical and isotopic approaches was conducted in the coastal region of the South China Sea near the Leizhou peninsular to provide primary insight into seawater intrusion and groundwater circulation. Hydrochemical and isotopic data show that local groundwater is subjected to anthropogenic activities and geochemical processes, such as evaporation, water-rock interaction, and ion exchange. However, seawater intrusion driven by the over-exploitation of groundwater and insufficient recharge is the predominant factor controlling groundwater salinization. Systematic and homologic isotopic characteristics of most samples suggest that groundwater in volcanic area is locally recharged and likely caused by modern precipitation. However, very depleted stable isotopes and extremely low tritium of groundwater in some isolated aquifers imply a dominant role of palaeowater. Copyright © 2015 Elsevier Ltd. All rights reserved.

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).

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

Recommendations for the Investigation of Vapor Intrusion

DTIC Science & Technology

2008-04-01

Abbreviations COC constituent of concern 1,1-dfa 1,1- difluoroethane EPA U.S. Environmental Protection Agency ESTCP Environmental Security...lines. During one sample event, the leak tracer itself caused significant problems. During this sample event, 1,1- difluoroethane (1,1-dfa, the

Recommendations for the Investigation of Vapor Intrusion

DTIC Science & Technology

2007-12-01

1,1-dfa 1,1- difluoroethane EPA U.S. Environmental Protection Agency ESTCP Environmental Security Technology Certification Program NHDES...the leak tracer itself caused significant problems. During this sample event, 1,1- difluoroethane (1,1-dfa, the propellant in duster spray) was used

ODOT research news : winter quarter 2003.

DOT National Transportation Integrated Search

2003-01-01

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

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

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

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

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

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

DOEpatents

Weigle, Eric H [Los Alamos, NM

2010-08-24

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

Intrusion detection using secure signatures

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

Nelson, Trent Darnel; Haile, Jedediah

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

Critical Infrastructure Protection and Resilience Literature Survey: Modeling and Simulation

DTIC Science & Technology

2014-11-01

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

TANDI: threat assessment of network data and information

NASA Astrophysics Data System (ADS)

Holsopple, Jared; Yang, Shanchieh Jay; Sudit, Moises

2006-04-01

Current practice for combating cyber attacks typically use Intrusion Detection Sensors (IDSs) to passively detect and block multi-stage attacks. This work leverages Level-2 fusion that correlates IDS alerts belonging to the same attacker, and proposes a threat assessment algorithm to predict potential future attacker actions. The algorithm, TANDI, reduces the problem complexity by separating the models of the attacker's capability and opportunity, and fuse the two to determine the attacker's intent. Unlike traditional Bayesian-based approaches, which require assigning a large number of edge probabilities, the proposed Level-3 fusion procedure uses only 4 parameters. TANDI has been implemented and tested with randomly created attack sequences. The results demonstrate that TANDI predicts future attack actions accurately as long as the attack is not part of a coordinated attack and contains no insider threats. In the presence of abnormal attack events, TANDI will alarm the network analyst for further analysis. The attempt to evaluate a threat assessment algorithm via simulation is the first in the literature, and shall open up a new avenue in the area of high level fusion.

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.

A network security monitor

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

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

1989-11-01

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

Low-Cost Ground Sensor Network for Intrusion Detection

DTIC Science & Technology

2017-09-01

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

Detailed Field Investigation of Vapor Intrusion Processes

DTIC Science & Technology

2008-08-01

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

Early Warning Systems Assure Safe Schools

ERIC Educational Resources Information Center

Greenhalgh, John

1973-01-01

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

A 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…

Adjoint sensitivity analysis of chaotic dynamical systems with non-intrusive least squares shadowing

NASA Astrophysics Data System (ADS)

Blonigan, Patrick J.

2017-11-01

This paper presents a discrete adjoint version of the recently developed non-intrusive least squares shadowing (NILSS) algorithm, which circumvents the instability that conventional adjoint methods encounter for chaotic systems. The NILSS approach involves solving a smaller minimization problem than other shadowing approaches and can be implemented with only minor modifications to preexisting tangent and adjoint solvers. Adjoint NILSS is demonstrated on a small chaotic ODE, a one-dimensional scalar PDE, and a direct numerical simulation (DNS) of the minimal flow unit, a turbulent channel flow on a small spatial domain. This is the first application of an adjoint shadowing-based algorithm to a three-dimensional turbulent flow.

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.

Development of an Assessment Procedure for Seawater Intrusion Mitigation

NASA Astrophysics Data System (ADS)

Hsi Ting, F.; Yih Chi, T.

2017-12-01

The Pingtung Plain is one of the areas with extremely plentiful groundwater resources in Taiwan. Due to that the application of the water resource is restricted by significant variation of precipitation between wet and dry seasons, groundwater must be used as a recharge source to implement the insufficient surface water resource during dry seasons. In recent years, the coastal aquaculture rises, and the over withdrawn of groundwater by private well results in fast drop of groundwater level. Then it causes imbalance of groundwater supply and leads to serious seawater intrusion in the coastal areas. The purpose of this study is to develop an integrated numerical model of groundwater resources and seawater intrusion. Soil and Water Assessment Tool (SWAT), MODFLOW and MT3D models were applied to analyze the variation of the groundwater levels and salinity concentration to investigate the correlation of parameters, which are used to the model applications in order to disposal saltwater intrusion. The data of groundwater levels, pumping capacity and hydrogeological data to were collected to build an integrated numerical model. Firstly, we will collect the information of layered aquifer and the data of hydrological parameters to build the groundwater numerical model at Pingtung Plain, and identify the amount of the groundwater which flow into the sea. In order to deal with the future climate change conditions or extreme weather conditions, we will consider the recharge with groundwater model to improve the seawater intrusion problem. The integrated numerical model which describes that seawater intrusion to deep confined aquifers and shallow unsaturated aquifers. Secondly, we will use the above model to investigate the weights influenced by different factors to the amount area of seawater intrusion, and predict the salinity concentration distribution of evaluation at coastal area of Pingtung Plain. Finally, we will simulate groundwater recharge/ injection at the coastal areas in Pington Plain by above model to investigate the analysis of salinity concentration in deep aquifers and the improvement of salinity concentration in shallow aquifers. In addition, a complete plan for managing both the flooding and water resources will be instituted by scheming non-engineering adaptation strategies for homeland planning.

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

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

PubMed Central

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

2012-01-01

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

Photonic sensor applications in transportation security

NASA Astrophysics Data System (ADS)

Krohn, David A.

2007-09-01

There is a broad range of security sensing applications in transportation that can be facilitated by using fiber optic sensors and photonic sensor integrated wireless systems. Many of these vital assets are under constant threat of being attacked. It is important to realize that the threats are not just from terrorism but an aging and often neglected infrastructure. To specifically address transportation security, photonic sensors fall into two categories: fixed point monitoring and mobile tracking. In fixed point monitoring, the sensors monitor bridge and tunnel structural health and environment problems such as toxic gases in a tunnel. Mobile tracking sensors are being designed to track cargo such as shipboard cargo containers and trucks. Mobile tracking sensor systems have multifunctional sensor requirements including intrusion (tampering), biochemical, radiation and explosives detection. This paper will review the state of the art of photonic sensor technologies and their ability to meet the challenges of transportation security.

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

PubMed

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

2012-01-01

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

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.

Reinventing the Department of Education: Real Regulatory Reform.

ERIC Educational Resources Information Center

Bob, Sharon

1995-01-01

Department of Education regulations and initiatives designed to address problems of fraud, abuse, and loan default in federal student aid programs are examined. The scope and intrusiveness of some recent regulations are criticized, and unintended effects are noted, including increased administrative burdens on all institutions. (Author/MSE)

Imagery Rescripting for Personality Disorders

ERIC Educational Resources Information Center

Arntz, Arnoud

2011-01-01

Imagery rescripting is a powerful technique that can be successfully applied in the treatment of personality disorders. For personality disorders, imagery rescripting is not used to address intrusive images but to change the implicational meaning of schemas and childhood experiences that underlie the patient's problems. Various mechanisms that may…

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

EPA Pesticide Factsheets

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

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

DOT National Transportation Integrated Search

2001-04-01

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

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

DOT National Transportation Integrated Search

2001-04-01

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

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2014 CFR

2014-07-01

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

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2013 CFR

2013-07-01

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

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2012 CFR

2012-07-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-08

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Information Assurance Technology Analysis Center Information Assurance Tools Report Intrusion Detection

DTIC Science & Technology

1998-01-01

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

Collaborative Point Paper on Border Surveillance Technology

DTIC Science & Technology

2007-06-01

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

Large Scale System Defense

DTIC Science & Technology

2008-10-01

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

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

PubMed Central

Tolley, William K.

2014-01-01

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

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.

Developing A New Predictive Dispersion Equation Based on Tidal Average (TA) Condition in Alluvial Estuaries

NASA Astrophysics Data System (ADS)

Anak Gisen, Jacqueline Isabella; Nijzink, Remko C.; Savenije, Hubert H. G.

2014-05-01

Dispersion mathematical representation of tidal mixing between sea water and fresh water in The definition of dispersion somehow remains unclear as it is not directly measurable. The role of dispersion is only meaningful if it is related to the appropriate temporal and spatial scale of mixing, which are identified as the tidal period, tidal excursion (longitudinal), width of estuary (lateral) and mixing depth (vertical). Moreover, the mixing pattern determines the salt intrusion length in an estuary. If a physically based description of the dispersion is defined, this would allow the analytical solution of the salt intrusion problem. The objective of this study is to develop a predictive equation for estimating the dispersion coefficient at tidal average (TA) condition, which can be applied in the salt intrusion model to predict the salinity profile for any estuary during different events. Utilizing available data of 72 measurements in 27 estuaries (including 6 recently studied estuaries in Malaysia), regressions analysis has been performed with various combinations of dimensionless parameters . The predictive dispersion equations have been developed for two different locations, at the mouth D0TA and at the inflection point D1TA (where the convergence length changes). Regressions have been carried out with two separated datasets: 1) more reliable data for calibration; and 2) less reliable data for validation. The combination of dimensionless ratios that give the best performance is selected as the final outcome which indicates that the dispersion coefficient is depending on the tidal excursion, tidal range, tidal velocity amplitude, friction and the Richardson Number. A limitation of the newly developed equation is that the friction is generally unknown. In order to compensate this problem, further analysis has been performed adopting the hydraulic model of Cai et. al. (2012) to estimate the friction and depth. Keywords: dispersion, alluvial estuaries, mixing, salt intrusion, predictive equation

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.

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

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.

Chapel Hill Campus Grapples with Problems of Governance.

ERIC Educational Resources Information Center

Jaschik, Scott

1989-01-01

Despite positive outward signs, the University of North Carolina at Chapel Hill is seen by some as resting on its reputation. Faculty and alumni complain that intrusive regulation by the state, lack of respect by the university system administration, and inadequate financial support are endangering its quality. (MSE)

Homeless Youths' Descriptions of Their Parents' Child-Rearing Practices.

ERIC Educational Resources Information Center

Kipke, Michele D.; And Others

1997-01-01

Explored homeless youths' perceptions of their parents' child-rearing practices. Results from 409 youth aged 12 to 23 years reveal the following four parenting styles: supportive/emotionally available; intrusive/unavailable; detached; and problems with drugs/law. Implications of these findings and future research and service provision needs are…

Measurement Properties of Indirect Assessment Methods for Functional Behavioral Assessment: A Review of Research

ERIC Educational Resources Information Center

Floyd, Randy G.; Phaneuf, Robin L.; Wilczynski, Susan M.

2005-01-01

Indirect assessment instruments used during functional behavioral assessment, such as rating scales, interviews, and self-report instruments, represent the least intrusive techniques for acquiring information about the function of problem behavior. This article provides criteria for examining the measurement properties of these instruments…

Building Security and Personal Safety. SPEC Kit 150.

ERIC Educational Resources Information Center

Bingham, Karen Havill

This report on a survey of Association of Research Libraries (ARL) member libraries on building security and personal safety policies examines three areas in detail: (1) general building security (access to the building, key distribution, patrols or monitors, intrusion prevention, lighting, work environment after dark); (2) problem behavior…

Evaluation of Factors Influencing the Groundwater Chemistry in a Small Tropical Island of Malaysia

PubMed Central

Kura, Nura Umar; Ramli, Mohammad Firuz; Sulaiman, Wan Nur Azmin; Ibrahim, Shaharin; Aris, Ahmad Zaharin; Mustapha, Adamu

2013-01-01

Groun in a very complex way. In this work, multivariate statistical analysis was used to evaluate the factors controlling the groundwater chemistry of Kapas Island (Malaysia). Principal component analysis (P dwater chemistry of small tropical islands is influenced by many factors, such as recharge, weathering and seawater intrusion, among others, which interact with each other CA) was applied to 17 hydrochemical parameters from 108 groundwater samples obtained from 18 sampling sites. PCA extracted four PCs, namely seawater intrusion, redox reaction, anthropogenic pollution and weather factors, which collectively were responsible for more than 87% of the total variance of the island’s hydrochemistry. The cluster analysis indicated that three factors (weather, redox reaction and seawater intrusion) controlled the hydrochemistry of the area, and the variables were allocated to three groups based on similarity. A Piper diagram classified the island’s water types into Ca-HCO3 water type, Na-HCO3 water type, Na-SO4-Cl water type and Na-Cl water type, indicating recharge, mixed, weathering and leached from sewage and seawater intrusion, respectively. This work will provide policy makers and land managers with knowledge of the precise water quality problems affecting the island and can also serve as a guide for hydrochemistry assessments of other islands that share similar characteristics with the island in question. PMID:23648442

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

DTIC Science & Technology

2014-02-26

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

Quantifying Associations between Environmental Stressors and Demographic Factors

EPA Science Inventory

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

Techniques for Cyber Attack Attribution

DTIC Science & Technology

2003-10-01

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

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.

Nonintrusive techniques of inspections during the pre-launch phase of space vehicle

NASA Astrophysics Data System (ADS)

Thirumalainambi, Rajkumar; Bardina, Jorge E.; Miyazawa, Osamu

2005-05-01

As missions expand to a sustainable presence in the Moon, and extend for durations longer than one year in lunar outpost, the effectiveness of the instrumentation and hardware has to be revolutionized if NASA is to meet high levels of mission safety, reliability, and overall success. This paper addresses a method of non-intrusive local inspection of surface and sub-surface conditions, interfaces, laminations and seals in both space vehicle and ground operations with an integrated suite of imaging sensors during pre-launch operations. It employs an advanced Raman spectrometer with additional spectrometers and lidar mounted on a flying robot to constantly monitor the space hardware as well as inner surface of the vehicle and ground operations hardware. A team of micro flying robots with necessary sensors and photometers is required to internally and externally monitor the entire space vehicle. The micro flying robots should reach an altitude with least amount of energy, where astronauts have difficulty in reaching and monitoring the materials and subsurface faults. The micro flying robots have an embedded fault detection system which acts as an advisory system and in many cases micro flying robots act as a `Supervisor' to fix the problems. The micro flying robot uses contra-rotating propellers powered by an ultra-thin, ultrasonic motor with currently the world's highest power weight ratio, and is balanced in mid-air by means of the world's first stabilizing mechanism using a linear actuator. The essence of micromechatronics has been brought together in high-density mounting technology to minimize the size and weight. Each robot can take suitable payloads of photometers, embedded chips for image analysis and micro pumps for sealing cracks or fixing other material problems. This paper also highlights advantages that this type of non-intrusive techniques offer over costly and monolithic traditional techniques.

Identifying and quantifying secondhand smoke in multiunit homes with tobacco smoke odor complaints

NASA Astrophysics Data System (ADS)

Dacunto, Philip J.; Cheng, Kai-Chung; Acevedo-Bolton, Viviana; Klepeis, Neil E.; Repace, James L.; Ott, Wayne R.; Hildemann, Lynn M.

2013-06-01

Accurate identification and quantification of the secondhand tobacco smoke (SHS) that drifts between multiunit homes (MUHs) is essential for assessing resident exposure and health risk. We collected 24 gaseous and particle measurements over 6-9 day monitoring periods in five nonsmoking MUHs with reported SHS intrusion problems. Nicotine tracer sampling showed evidence of SHS intrusion in all five homes during the monitoring period; logistic regression and chemical mass balance (CMB) analysis enabled identification and quantification of some of the precise periods of SHS entry. Logistic regression models identified SHS in eight periods when residents complained of SHS odor, and CMB provided estimates of SHS magnitude in six of these eight periods. Both approaches properly identified or apportioned all six cooking periods used as no-SHS controls. Finally, both approaches enabled identification and/or apportionment of suspected SHS in five additional periods when residents did not report smelling smoke. The time resolution of this methodology goes beyond sampling methods involving single tracers (such as nicotine), enabling the precise identification of the magnitude and duration of SHS intrusion, which is essential for accurate assessment of human exposure.

Features extraction algorithm about typical railway perimeter intrusion event

NASA Astrophysics Data System (ADS)

Zhou, Jieyun; Wang, Chaodong; Liu, Lihai

2017-10-01

Research purposes: Optical fiber vibration sensing system has been widely used in the oil, gas, frontier defence, prison and power industries. But, there are few reports about the application in railway defence. That is because the surrounding environment is complicated and there are many challenges to be overcomed in the optical fiber vibration sensing system application. For example, how to eliminate the effects of vibration caused by train, the natural environments such as wind and rain and how to identify and classify the intrusion events. In order to solve these problems, the feature signals of these events should be extracted firstly. Research conclusions: (1) In optical fiber vibration sensing system based on Sagnac interferometer, the peak-to-peak value, peak-to-average ratio, standard deviation, zero-crossing rate, short-term energy and kurtosis may serve as feature signals. (2) The feature signals of resting state, climbing concrete fence, breaking barbed wire, knocking concrete fence and rainstorm have been extracted, which shows significant difference among each other. (3) The research conclusions can be used in the identification and classification of intrusion events.

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.

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.

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

Microsensors for border patrol applications

NASA Astrophysics Data System (ADS)

Falkofske, Dwight; Krantz, Brian; Shimazu, Ron; Berglund, Victor

2005-05-01

A top concern in homeland security efforts is the lack of ability to monitor the thousands of miles of open border with our neighbors. It is not currently feasible to continually monitor the borders for illegal intrusions. The MicroSensor System (MSS) seeks to achieve a low-cost monitoring solution that can be efficiently deployed for border patrol applications. The modifications and issues regarding the unique requirements of this application will be discussed and presented. The MicroSensor System was developed by the Defense Microelectronics Activity (DMEA) for military applications, but border patrol applications, with their unique sensor requirements, demand careful adaptation and modification from the military application. Adaptation of the existing sensor design for border applications has been initiated. Coverage issues, communications needs, and other requirements need to be explored for the border patrol application. Currently, border patrol has a number of deficiencies that can be addressed with a microsensor network. First, a distributed networked sensor field could mitigate the porous border intruder detection problem. Second, a unified database needs to be available to identify aliens attempting to cross into the United States. This database needs to take unique characteristics (e.g. biometrics, fingerprints) recovered from a specialized field unit to reliably identify intruders. Finally, this sensor network needs to provide a communication ability to allow border patrol officers to have quick access to intrusion information as well as equipment tracking and voice communication. MSS already addresses the sensing portion of the solution, including detection of acoustic, infrared, magnetic, and seismic events. MSS also includes a low-power networking protocol to lengthen the battery life. In addition to current military requirements, MSS needs a solar panel solution to extend its battery life to 5 years, and an additional backbone communication link. Expanding the capabilities of MSS will go a long way to improving the security of the nation's porous borders.

Acoustic measurements of soil-pipeflow and internal erosion

USDA-ARS?s Scientific Manuscript database

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

Acoustic measurements of soil pipeflow and internal erosion

USDA-ARS?s Scientific Manuscript database

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

Molecular oxygen detection using frequency modulation diode laser spectroscopy

NASA Technical Reports Server (NTRS)

Wang, Liang-Guo; Sachse, Glen

1990-01-01

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

Numerical Analysis for Relevant Features in Intrusion Detection (NARFid)

DTIC Science & Technology

2009-03-01

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

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

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

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

Network traffic intelligence using a low interaction honeypot

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Sill intrusion in volcanic calderas: implications for vent opening probability

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

[MOSS- Mobile Sensing and Support Detection of depressive moods with an app and help those affected].

PubMed

Weidt, Steffi; Wahle, Fabian; Rufer, Michael; Hörni, Anja; Kowatsch, Tobias

2015-09-01

Major depression is regarded as a significant and serious disease with an increasing prevalence worldwide. However, not all individuals with depressive pressive symptoms seek help for their problems. These untreated "hidden" individuals with depressive symptoms require the design and dissemination of evidence-based, /ow-cost and scalable mental health interventions. Such interventions provided by mobile applications are promising as they have the potential to support people in their everyday life. However, as of today it is unclear how to design mental health applications that are effective and motivating yet non-intrusive. In addressing this problem, the MOSS application is a recent endeavor of a Swiss project team from Universitiitsspital Zurich, ETH Zurich, University of St. Gallen and makora AG, to support people with depressive symptoms. In particular, evidence-based micro-interventions are recommended and triggered by individual characteristics that are derived from self-reports, smartphone interactions and sensor data. After one year of development, the study team now conducts a first empirical study and thus, recruits people affected by depressive symptoms to improve not only the application as such but with it, the delivery of mental health interventions in the long run.

Imbalanced learning for pattern recognition: an empirical study

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Man, Hong; Desai, Sachi; Quoraishee, Shafik

2010-10-01

The imbalanced learning problem (learning from imbalanced data) presents a significant new challenge to the pattern recognition and machine learning society because in most instances real-world data is imbalanced. When considering military applications, the imbalanced learning problem becomes much more critical because such skewed distributions normally carry the most interesting and critical information. This critical information is necessary to support the decision-making process in battlefield scenarios, such as anomaly or intrusion detection. The fundamental issue with imbalanced learning is the ability of imbalanced data to compromise the performance of standard learning algorithms, which assume balanced class distributions or equal misclassification penalty costs. Therefore, when presented with complex imbalanced data sets these algorithms may not be able to properly represent the distributive characteristics of the data. In this paper we present an empirical study of several popular imbalanced learning algorithms on an army relevant data set. Specifically we will conduct various experiments with SMOTE (Synthetic Minority Over-Sampling Technique), ADASYN (Adaptive Synthetic Sampling), SMOTEBoost (Synthetic Minority Over-Sampling in Boosting), and AdaCost (Misclassification Cost-Sensitive Boosting method) schemes. Detailed experimental settings and simulation results are presented in this work, and a brief discussion of future research opportunities/challenges is also presented.

Unsupervised active learning based on hierarchical graph-theoretic clustering.

PubMed

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

2009-10-01

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

Implant/tooth-connected restorations utilizing screw-fixed attachments: a survey of 3,096 sites in function for 3 to 14 years.

PubMed

Fugazzotto, P A; Kirsch, A; Ackermann, K L; Neuendorff, G

1999-01-01

Numerous problems have been reported following various therapies used to attach natural teeth to implants beneath a fixed prosthesis. This study documents the results of 843 consecutive patients treated with 1,206 natural tooth/implant-supported prostheses utilizing 3,096 screw-fixed attachments. After 3 to 14 years in function, only 9 intrusion problems were noted. All problems were associated with fractured or lost screws. This report demonstrates the efficacy of such a treatment approach when a natural tooth/implant-supported fixed prosthesis is contemplated.

Summary appraisals of the Nation's ground-water resources; South Atlantic Gulf region

USGS Publications Warehouse

Cederstrom, D.J.; Boswell, E.H.; Tarver, G.R.

1979-01-01

Ground-water problems generally are not severe. Critical situations are restricted to areas where large quantities of ground water are being withdrawn or where aquifers are contaminated by oil-field or industrial waste. Large withdrawals in coastal areas have caused some saltwater intrusion. In other localities, highly mineralized water may have migrated along fault zones to freshwater aquifers. Many of the present problems can be resolved or ameliorated by redistributing withdrawals or developing alternative water sources.

Noise: A Health Problem.

ERIC Educational Resources Information Center

Environmental Protection Agency, Washington, DC. Office of Noise Abatement and Control.

This booklet contains nine sections describing ways in which noise may endanger health and well-being. Secions are included on: (1) hearing loss; (2) heart disease; (3) other reactions by the body; (4) effects on the unborn; (5) special effects on children; (6) intrusion at home and work; (7) sleep disruption; (8) mental and social well-being; and…

The Intrusion of Corruption into Athletics: An Age-Old Problem.

ERIC Educational Resources Information Center

Thompson, James G.

1986-01-01

Offers examples of corruption in athletics in ancient Greece and in the early years of intercollegiate athletics in the U.S. Criticizes the current win-at-all-costs philosophy in intercollegiate programs. Argues that self-sustaining athletics departments are forced into devious practices to win. Recommends increased involvement by university…

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.

Origin of Fe-Ti Oxide Mineralization in the Middle Paleoproterozoic Elet'ozero Syenite-Gabbro Intrusive Complex (Northern Karelia, Russia)

NASA Astrophysics Data System (ADS)

Sharkov, E. V.; Chistyakov, A. V.; Shchiptsov, V. V.; Bogina, M. M.; Frolov, P. V.

2018-03-01

Magmatic oxide mineralization widely developed in syenite-gabbro intrusive complexes is an important Fe and Ti resource. However, its origin is hotly debatable. Some researchers believe that the oxide ores were formed through precipitation of dense Ti-magnetite in an initial ferrogabbroic magma (Bai et al., 2012), whereas others consider them as a product of immiscible splitting of Fe-rich liquid during crystallization of Fe-Ti basaltic magma (Zhou et al., 2013). We consider this problem with a study of the Middle Paleoproterozoic (2086 ± 30 Ma) Elet'ozero Ti-bearing layered intrusive complex in northern Karelia (Baltic Shield). The first ore-bearing phase of the complex is mainly made up of diverse ferrogabbros, with subordinate clinopyroxenites and peridotites. Fe-Ti oxides (magnetite, Ti-magnetite, and ilmenite) usually account for 10-15 vol %, reaching 30-70% in ore varieties. The second intrusive phase is formed by alkaline and nepheline syenites. Petrographical, mineralogical, and geochemical data indicate that the first phase of the intrusion was derived from a moderately alkaline Fe-Ti basaltic melt, while the parental melt of the second phase was close in composition to alkaline trachyte. The orebodies comprise disseminated and massive ores. The disseminated Fe-Ti oxide ores make up lenses and layers conformable to general layering. Massive ores occur in subordinate amounts as layers and lenses, as well as cross-cutting veins. Elevated Nb and Ta contents in Fe-Ti oxides makes it possible to consider them complex ores. It is shown that the Fe-Ti oxide mineralization is related to the formation of a residual (Fe,Ti)-rich liquid, which lasted for the entire solidification history of the first intrusive phase. The liquid originated through multiple enrichment of Fe and Ti in the crystallization zone of the intrusion owing to the following processes: (1) precipitation of silicate minerals in the crystallization zone with a corresponding increase in the Fe and Ti contents in an interstitial melt; and (2) periodic accumulation of the residual melt in front of this zone. Unlike liquid immiscibility leading to melt splitting into two phases, this liquid dissolved the residual components of the melt. Correspondingly, such an Fe-rich liquid has unusual properties and requires further study.

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.

Predicting and Detecting Emerging Cyberattack Patterns Using StreamWorks

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

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

2014-06-30

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

Aggressiveness, violence, homicidality, homicide, and Lyme disease

PubMed Central

Bransfield, Robert C

2018-01-01

Background No study has previously analyzed aggressiveness, homicide, and Lyme disease (LD). Materials and methods Retrospective LD chart reviews analyzed aggressiveness, compared 50 homicidal with 50 non-homicidal patients, and analyzed homicides. Results Most aggression with LD was impulsive, sometimes provoked by intrusive symptoms, sensory stimulation or frustration and was invariably bizarre and senseless. About 9.6% of LD patients were homicidal with the average diagnosis delay of 9 years. Postinfection findings associated with homicidality that separated from the non-homicidal group within the 95% confidence interval included suicidality, sudden abrupt mood swings, explosive anger, paranoia, anhedonia, hypervigilance, exaggerated startle, disinhibition, nightmares, depersonalization, intrusive aggressive images, dissociative episodes, derealization, intrusive sexual images, marital/family problems, legal problems, substance abuse, depression, panic disorder, memory impairments, neuropathy, cranial nerve symptoms, and decreased libido. Seven LD homicides included predatory aggression, poor impulse control, and psychosis. Some patients have selective hyperacusis to mouth sounds, which I propose may be the result of brain dysfunction causing a disinhibition of a primitive fear of oral predation. Conclusion LD and the immune, biochemical, neurotransmitter, and the neural circuit reactions to it can cause impairments associated with violence. Many LD patients have no aggressiveness tendencies or only mild degrees of low frustration tolerance and irritability and pose no danger; however, a lesser number experience explosive anger, a lesser number experience homicidal thoughts and impulses, and much lesser number commit homicides. Since such large numbers are affected by LD, this small percent can be highly significant. Much of the violence associated with LD can be avoided with better prevention, diagnosis, and treatment of LD. PMID:29576731

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

Investigation of a Neural Network Implementation of a TCP Packet Anomaly Detection System

DTIC Science & Technology

2004-05-01

reconnatre les nouvelles variantes d’attaque. Les réseaux de neurones artificiels (ANN) ont les capacités d’apprendre à partir de schémas et de...Computational Intelligence Techniques in Intrusion Detection Systems. In IASTED International Conference on Neural Networks and Computational Intelligence , pp...Neural Network Training: Overfitting May be Harder than Expected. In Proceedings of the Fourteenth National Conference on Artificial Intelligence , AAAI-97

Perceptual processing advantages for trauma-related visual cues in post-traumatic stress disorder

PubMed Central

Kleim, B.; Ehring, T.; Ehlers, A.

2012-01-01

Background Intrusive re-experiencing in post-traumatic stress disorder (PTSD) comprises distressing sensory impressions from the trauma that seem to occur ‘out of the blue’. A key question is how intrusions are triggered. One possibility is that PTSD is characterized by a processing advantage for stimuli that resemble those that accompanied the trauma, which would lead to increased detection of such cues in the environment. Method We used a blurred picture identification task in a cross-sectional (n=99) and a prospective study (n=221) of trauma survivors. Results Participants with acute stress disorder (ASD) or PTSD, but not trauma survivors without these disorders, identified trauma-related pictures, but not general threat pictures, better than neutral pictures. There were no group differences in the rate of trauma-related answers to other picture categories. The relative processing advantage for trauma-related pictures correlated with re-experiencing and dissociation, and predicted PTSD at follow-up. Conclusions A perceptual processing bias for trauma-related stimuli may contribute to the involuntary triggering of intrusive trauma memories in PTSD. PMID:21733208

Saltwater Intrusion: Climate change mitigation or just water resources management?

NASA Astrophysics Data System (ADS)

Ferguson, G. A.; Gleeson, T.

2011-12-01

Climate change and population growth are expected to substantially increase the vulnerability of global water resources throughout the 21st century. Coastal groundwater systems are a nexus of the world's changing oceanic and hydrologic systems and a critical resource for the over one billion people living in coastal areas as well as for terrestrial and offshore ecosystems. Synthesis studies and detailed simulations predict that rising sea levels could negatively impact coastal aquifers by causing saltwater to intrude landward within coastal aquifers or by saltwater inundation of coastal regions. Saltwater intrusion caused by excessive extraction is already impacting entire island nations and globally in diverse regions such as Nile River delta in Egypt, Queensland, Australia and Long Island, USA. However, the vulnerability of coastal aquifers to sea level rise and excessive extraction has not been systematically compared. Here we show that coastal aquifers are much more vulnerable to groundwater extraction than predicted sea level rise in wide-ranging hydrogeologic conditions and population densities. Low lying areas with small hydraulic gradients are more sensitive to climate change but a review of existing coastal aquifer indicates that saltwater intrusion problems are more likely to arise where water demand is high. No cases studies were found linking saltwater intrusion to sea level rise during the past century. Humans are a key driver in the hydrology of coastal aquifers and that adapting to sea level rise at the expense of better water management is misguided.

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

The investigation of chemical quality of water in tidal rivers

USGS Publications Warehouse

Keighton, Walter B.

1954-01-01

This report has been prepared for the guidance of personnel of the Water Resources Division who are engaged in water-quality investigations of tidal rivers. The study of tidal rivers is beset with many complexities not present in the investigation of non-tidal rivers. The periodic rise and fall of the tide may result in a corresponding periodic change in salinity at a sampling location on the tidal river. When the fresh water discharge is low, saline water may intrude up-river, and any factor changing the relative elevations of the ocean and the mean river level has an effect on the extent of salt-water intrusion. Variations in water composition between samples taken at several locations up or down river, at different depths, or at several locations across the stream are likely to be more pronounced than for similar sets of samples from a non-tidal stream. The nature of these variations and factors responsible for them are discussed, and the need for consideration of them in planning a sampling routine is stressed. The nature and mechanism of ocean-water intrusion in tidal rivers is discussed and sampling procedures for its detection are described. lllustrative examples - mostly from the work of the United States Geological Survey or State agencies - show various methods for correlating and presenting data from quality-of-water surveys of tidal rivers. Each tidal river presents an individual problem which can best be understood from a study of the factors involved. To that end the report is supplemented by an annotated bibliography of selected publications in the field.

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...

Technology That's Ready and Able to Inspect Those Cables

NASA Technical Reports Server (NTRS)

2005-01-01

Attempting to locate a malfunctioning wire in a complex bundle of wires or in a cable that is concealed behind a wall is as difficult as trying to find a needle in a haystack. The result of such an effort can also be costly, time-consuming, and frustrating, whether it is the tedious process of examining cable connections for the Space Shuttle or troubleshooting a cable television hookup. Furthermore, other maintenance restrictions can compound the effort required to locate and repair a particular wiring problem. For example, on the Space Shuttle, once a repair is completed, all systems that have a wire passing through any of the connectors that were disconnected during troubleshooting are affected and, therefore, must undergo retesting, an arduous task that is completely unrelated to the original problem. In an effort to streamline wire inspection and maintenance, two contractors supporting NASA's Kennedy Space Center invented the Standing Wave Reflectometer (SWR) in 1999. In doing so, they leveraged technology that was first developed to detect problems that could lead to aircraft accidents, such as the one that resulted in the catastrophic failure of TWA flight 800 in 1996. The SWR performs a non-intrusive inspection that verifies the condition of electrical power and signal-distribution systems inside the Space Shuttle orbiters. Such testing reduces processing delays and ensures safe operation of these systems.

Stability and social-behavioral consequences of toddlers' inhibited temperament and parenting behaviors.

PubMed

Rubin, Kenneth H; Burgess, Kim B; Hastings, Paul D

2002-01-01

A prospective longitudinal design was employed to ascertain whether different types of behavioral inhibition (i.e., traditional, peer-social) were stable from toddler to preschool age, and whether inhibited temperament and/or parenting style would predict children's subsequent social and behavioral problems. At Time 1, 108 toddlers (54 males, 54 females) and their mothers were observed in the Traditional Inhibition Paradigm and in a toddler-peer session; then at age 4 years, 88 children were observed with unfamiliar peers, and maternal ratings of psychological functioning were obtained. How mothers and their toddlers interacted was also observed. Results revealed meaningful connections between toddler inhibition, maternal intrusive control and derision, and nonsocial behaviors at age 4. Both forms of toddler inhibition predicted socially reticent behavior during free play at 4 years. If mothers demonstrated relatively high frequencies of intrusive control and/or derisive comments, then the association between their toddlers' peer inhibition and 4-year social reticence was significant and positive; whereas if mothers were neither intrusive nor derisive, then toddlers' peer inhibition and 4-year reticence were not significantly associated. Thus, maternal behaviors moderated the relation between toddlers' peer inhibition and preschoolers' social reticence.

Reduced autobiographical memory specificity relates to weak resistance to proactive interference.

PubMed

Smets, Jorien; Wessel, Ineke; Raes, Filip

2014-06-01

Reduced autobiographical memory specificity (rAMS), experiencing intrusive memories, and rumination appear to be risk factors for depression and depressive relapse. The aim of the current study was to investigate whether a weak resistance to proactive interference (PI) might underlie this trio of cognitive risk factors. Resistance to PI refers to being able to ignore cognitive distracters that were previously relevant but became irrelevant for current task goals. Students (N = 65) and depressed patients (N = 37) completed tasks measuring resistance to PI and AMS, and completed questionnaires on intrusive memories and rumination. In both samples, weaker resistance to PI was associated with rAMS. There was no evidence for a relationship between resistance to PI and intrusive memories or rumination. As we did not assess other measures of executive functioning, we cannot conclude whether the observed relationship between rumination and PI is due to unique qualities of PI. Difficulties to deliberately recall specific, rather than general or categoric autobiographical memories appear to be related to more general problems with the inhibition of interference of mental distracters. The results are in line with the executive control account of rAMS. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-02-01

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

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.

Electro-Osmotic Pulse Technology: A Novel Solution to Severe Water Intrusion Problems in Earth Covered Magazines

DTIC Science & Technology

2006-11-01

The situation was deemed ideal for ElectroOsmotic Pulse (EOP) technology. A Return-on-Investment (ROI) study concluded that EOP is also the most...various steps in the EOP system installation: Figure 15 shows the chipping operation for installing a ¾-inch wide mixed metal-oxide coated titanium

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

Non-intrusive tunable resonant microwave cavity for optical detected magnetic resonance of NV centres in nanodiamonds

NASA Astrophysics Data System (ADS)

Le Floch, Jean-Michel; Bradac, Carlo; Volz, Thomas; Tobar, Michael E.; Castelletto, Stefania

2013-12-01

Optically detected magnetic resonance (ODMR) in nanodiamond nitrogen-vacancy (NV) centres is usually achieved by applying a microwave field delivered by micron-size wires, strips or antennas directly positioned in very close proximity (~ μm) of the nanodiamond crystals. The microwave field couples evanescently with the ground state spin transition of the NV centre (2.87 GHz at zero magnetic field), which results in a reduction of the centre photoluminescence. We propose an alternative approach based on the construction of a dielectric resonator. We show that such a resonator allows for the efficient detection of NV spins in nanodiamonds without the constraints associated to the laborious positioning of the microwave antenna next to the nanodiamonds, providing therefore improved flexibility. The resonator is based on a tunable Transverse Electric Mode in a dielectric-loaded cavity, and we demonstrate that the resonator can detect single NV centre spins in nanodiamonds using less microwave power than alternative techniques in a non-intrusive manner. This method can achieve higher precision measurement of ODMR of paramagnetic defects spin transition in the micro to millimetre-wave frequency domain. Our approach would permit the tracking of NV centres in biological solutions rather than simply on the surface, which is desirable in light of the recently proposed applications of using nanodiamonds containing NV centres for spin labelling in biological systems with single spin and single particle resolution.

Petrology of Ortsog-Uul peridotite-gabbro massif in Western Mongolia

NASA Astrophysics Data System (ADS)

Shapovalova, M.; Tolstykh, N.; Shelepaev, R.; Cherdantseva, M.

2017-12-01

The Ortsog-Uul mafic-ultramafic massif of Western Mongolia is located in a tectonic block with overturned bedding. The massif hosts two intrusions: a rhythmically-layered peridotite-gabbro association (Intrusion 1) and massive Bt-bearing amphibole-olivine gabbro (Intrusion 2). Intrusions 1 and 2 have different petrology features. Early Intrusion 1 (278±2.5Ma) is characterized by lower concentrations of alkalis, titanium and phosphorus than late Intrusion 2 (272±2Ma). The chondrite-normalized REE and primitive mantle-normalized rare elements patterns of Ortsog-Uul intrusions have similar curves of elements distribution. However, Intrusion 2 is characterized higher contents of REE and rare elements. High concentrations of incompatible elements are indicative of strong fractionation process. It has been suggested that Intrusions 1 and 2 derived from compositionally different parental melts. Model calculations (COMAGMAT-3.57) show that parental melts of two intrusions were close to high-Mg picrobasaltic magmas. The concentration of MgO in melt is 16.21 (Intrusion 1) and 16.17 (Intrusion 2). Isotopic data of Ortsog-Uul magmatic rocks exhibit different values of εNd (positive and negative) for Intrusion 1 and 2, respectively.

Analysis of seawater flow through optical fiber

NASA Astrophysics Data System (ADS)

Fernández López, Sheila; Carrera Ramírez, Jesús; Rodriguez Sinobar, Leonor; Benitez, Javier; Rossi, Riccardo; Laresse de Tetto, Antonia

2015-04-01

The relation between sea and coastal aquifer is very important to the human populations living in coastal areas. The interrelation involves the submarine ground water discharge of relatively fresh water to the sea and the intrusion of sea water into the aquifer, which impairs the quality of ground water. The main process in seawater intrusion is managed by fluid-density effects which control the displacement of saline water. The underlain salinity acts as the restoring force, while hydrodynamic dispersion and convection lead to a mixing and vertical displacement of the brine. Because of this, a good definition of this saltwater-freshwater interface is needed what is intimately joined to the study of the movements (velocity fields) of fresh and salt water. As it is well known, the flow of salt water studied in seawater intrusion in stationary state, is nearly null or very low. However, in the rest of cases, this flux can be very important, so it is necessary its study to a better comprehension of this process. One possible manner of carry out this analysis is through the data from optical fiber. So, to research the distribution and velocity of the fresh and saltwater in the aquifer, a fiber optic system (OF) has been installed in Argentona (Baix Maresme, Catalonia). The main objective is to obtain the distributed temperature measurements (OF-DTS) and made progress in the interpretation of the dynamic processes of water. For some applications, the optical fiber acts as a passive temperature sensor but in our case, the technique Heated Active Fiber Optic will be used. This is based on the thermal response of the ground as a heat emission source is introduced. The thermal properties of the soil, dependent variables of soil water content, will make a specific temperature distribution around the cable. From the analyzed data we will deduce the velocity field, the real objective of our problem. To simulate this phenomenon and the coupled transport and flow problem, dominant in seawater intrusion, a finite element code in C ++ language will be developed. Finally, the information obtained numerically with our code will be checked with the field information.

The role of large and small cometary showers in the changes of living conditions on the Earth

NASA Astrophysics Data System (ADS)

Churyumov, K. I.; Steklov, A. F.; Vidmachenko, A. P.; Dashkiev, G. N.; Stepahno, I. V.; Steklov, E. A.; Slipchenko, A. S.; Romaniuk, Ya. O.

2016-10-01

1. The supremum of astrophysical problems in modern astronomy. With the introduction into service in 1974, of the largest at that time, six-meter telescope BTA at Zelenchukskaya Astrophysical Observatory (SAO) - Department of Extragalactic Research and relativistic astrophysics was established. Its main task was to study the so-called super-distant boundary fields and extreme states of substances of stars, galactic nuclei in the early epoch of the Universe. Now, after 40 years, these tasks are as popular and relevant: quasars, pulsars, gravitational lenses, black holes, active galactic nuclei, etc. Already established telescopes with diameters of multicomponent mirrors of 8-10 meters or more. Astronomical observatories had gone high into the mountains, to the special mountain on the islands in the oceans, in the alpine desert and into space. Extreme problems on the supremum still attracts the strongest efforts of astrophysicists in the world. But what about the other side of extreme tasks: with the tasks of astrophysics for "infimum"? Let us consider the astrophysical problems of "infimum" in more detail. 2. Infinum of astrophysical problems in modern astronomy. We believe that among the tasks of modern astrophysics can be super-close latent invasion (SCLI). If SCLI develop the concepts of cosmology, our views on the entire universe, on special times and special state of substance, then the infimum problem solving and must save the people and all living creatures on the planet against various types of aerospace dangerous intruders. SСLІ tasks are vital for all of us. These problems must be solved by leaders of countries and of concrete cities. The essence of these tasks determined the real threats and real fears against quite possibly over-close encounters with deadly consequences for all mankind intrusion of comets nucleus and asteroids, as well as the hidden, latent threat against far more numerous invasions of fragments of these bodies. And it is a completely different parties of the well-known asteroid-comet hazard and, especially, of large and small cometary showers. 3. Structural elements "Churyumov Unified Network". Summarize our proposals on the organization of effective structures "Churyumov Unified Network" [1-3, 5, 7-12] for terrestrial Aerospace Monitoring Services (TAMS) traces of all kinds of dangerous intrusions into the skies over our cities and countries. Recall that astrophysicists are most interested traces of dangerous intrusion of fragments of comets and asteroids, meteoroids, fireballs destroying (DIFCAMFD). As a result, we have: 3.1. Churyumov Conceptual club. We create, organize creative associations, collectives of Wildlife Photography on traces of intrusion; we make out it as a Churyumov Conceptual club, groups of simply connected Wildlife Photography on daytime and twilight traces of all kinds of dangerous intrusion. In our "Churyumov Unified Network" this structure is successfully operating since March 2013 [10]. Special registration invasion of the area of the Brovary city near Kiev was made by assistant professor Stepahno IV in December 1998. This organization has given us more than 36000 pictures in our data base. 3.2. Basic services of SAO TAMS. In our works we have described the purpose and meaning of the creation of stationary astronomical observatory (of SAO) of terrestrial aerospace monitoring services. Modern technical design of facilities in observations should "lift" mathematical horizon above the true horizon at the installation site of the photographic automated unified (PGAU). 3.3. Special TAMS MAO services. Each of SAO TAMS services necessary to deploy 1-3 mobile astronomical observatories (MAO) TAMS services. These specialized vehicles at astronomical observatories significantly strengthen the chances of success at "catching" and photodetection of traces of dangerous intrusion in conditions of positional observations. We note the success and the fact of use on Dnieper River near Kyiv of specialized yachts with photorecorder, implemented by assistant professor G.N. Dashkiev. That's why we build big plans in this direction with the creation of several specialized yachts, which can be used in Kiev, Odessa, Nikolaev, where there is an astronomical observatory and meteor patrols. A large comet showers have to capture still far enough in space because they are deadly to of life on Earth. 3.4. Special AAO TAMS our services. Traditional Astronomical observatories (AO Kiev University. Shevchenko, MAO NASU, etc.) in need of of specialized aerial astronomical observatories (AAO) TAMS services based on of use drones, quadrocopters, unmanned aerial vehicles (UAVs) with reliable PGAU [ 4, 6]. This is another important area for scientific and technical development services in TAMS "Churyumov Unified Network". 4. The International Academic Senate (IAS) and its role in the coordination of terrestrial services and networks, mobile, airborne and orbital space monitoring. Chief Scientific Secretary of the IAS Dashkiev GN not just passionate about photo-shoot on all kinds of dangerous intrusion into the sky over our cities, as has already been a great experience and significant progress in our common cause. Therefore, we hope not only to support the leadership of Ukraine, National Academy of Sciences, Security Service of Ukraine, the Emergencies Ministry, but also in the constructive and mutually beneficial cooperation with other countries

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.

Photonic sensor opportunities for distributed and wireless systems in security applications

NASA Astrophysics Data System (ADS)

Krohn, David

2006-10-01

There are broad ranges of homeland security sensing applications that can be facilitated by distributed fiber optic sensors and photonics integrated wireless systems. These applications include [1]: Pipeline, (Monitoring, Security); Smart structures (Bridges, Tunnels, Dams, Public spaces); Power lines (Monitoring, Security); Transportation security; Chemical/biological detection; Wide area surveillance - perimeter; and Port Security (Underwater surveillance, Cargo container). Many vital assets which cover wide areas, such as pipeline and borders, are under constant threat of being attacked or breached. There is a rapidly emerging need to be able to provide identification of intrusion threats to such vital assets. Similar problems exit for monitoring the basic infrastructure such as water supply, power utilities, communications systems as well as transportation. There is a need to develop a coordinated and integrated solution for the detection of threats. From a sensor standpoint, consideration must not be limited to detection, but how does detection lead to intervention and deterrence. Fiber optic sensor technology must be compatible with other surveillance technologies such as wireless mote technology to facilitate integration. In addition, the multi-functionality of fiber optic sensors must be expanded to include bio-chemical detection. There have been a number of barriers for the acceptance and broad use of smart fiber optic sensors. Compared to telecommunications, the volume is low. This fact coupled with proprietary and custom specifications has kept the price of fiber optic sensors high. There is a general lack of a manufacturing infrastructure and lack of standards for packaging and reliability. Also, there are several competing technologies; some photonic based and other approaches based on conventional non-photonic technologies.

Unveiling the Biometric Potential of Finger-Based ECG Signals

PubMed Central

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235

Volcanic hazards and their mitigation: progress and problems

USGS Publications Warehouse

Tilling, R.I.

1989-01-01

A review of hazards mitigation approaches and techniques indicates that significant advances have been made in hazards assessment, volcano monioring, and eruption forecasting. For example, the remarkable accuracy of the predictions of dome-building events at Mount St. Helens since June 1980 is unprecedented. Yet a predictive capability for more voluminous and explosive eruptions still has not been achieved. Studies of magma-induced seismicity and ground deformation continue to provide the most systematic and reliable data for early detection of precursors to eruptions and shallow intrusions. In addition, some other geophysical monitoring techniques and geochemical methods have been refined and are being more widely applied and tested. Comparison of the four major volcanic disasters of the 1980s (Mount St. Helens, U.S.A. (1980), El Chichon, Mexico (1982); Galunggung, Indonesia (1982); and Nevado del Ruiz, Colombia (1985)) illustrates the importance of predisaster geoscience studies, volcanic hazards assessments, volcano monitoring, contingency planning, and effective communications between scientists and authorities. -from Author

Unveiling the biometric potential of finger-based ECG signals.

PubMed

Lourenço, André; Silva, Hugo; Fred, Ana

2011-01-01

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

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.

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

Mechanisms affecting water quality in an intermittent piped water supply.

PubMed

Kumpel, Emily; Nelson, Kara L

2014-01-01

Drinking water distribution systems throughout the world supply water intermittently, leaving pipes without pressure between supply cycles. Understanding the multiple mechanisms that affect contamination in these intermittent water supplies (IWS) can be used to develop strategies to improve water quality. To study these effects, we tested water quality in an IWS system with infrequent and short water delivery periods in Hubli-Dharwad, India. We continuously measured pressure and physicochemical parameters and periodically collected grab samples to test for total coliform and E. coli throughout supply cycles at 11 sites. When the supply was first turned on, water with elevated turbidity and high concentrations of indicator bacteria was flushed out of pipes. At low pressures (<10 psi), elevated indicator bacteria were frequently detected even when there was a chlorine residual, suggesting persistent contamination had occurred through intrusion or backflow. At pressures between 10 and 17 psi, evidence of periodic contamination suggested that transient intrusion, backflow, release of particulates, or sloughing of biofilms from pipe walls had occurred. Few total coliform and no E. coli were detected when water was delivered with a chlorine residual and at pressures >17 psi.

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.

Temporal variability of the Circumpolar Deep Water inflow onto the Ross Sea continental shelf

NASA Astrophysics Data System (ADS)

Castagno, Pasquale; Falco, Pierpaolo; Dinniman, Michael S.; Spezie, Giancarlo; Budillon, Giorgio

2017-02-01

The intrusion of Circumpolar Deep Water (CDW) is the primary source of heat, salt and nutrients onto Antarctica's continental shelves and plays a major role in the shelf physical and biological processes. Different studies have analyzed the processes responsible for the transport of CDW across the Ross Sea shelf break, but until now, there are no continuous observations that investigate the timing of the intrusions. Also, few works have focused on the effect of the tides that control these intrusions. In the Ross Sea, the CDW intrudes onto the shelf in several locations, but mostly along the troughs. We use hydrographic observations and a mooring placed on the outer shelf in the middle of the Drygalski Trough in order to characterize the spatial and temporal variability of CDW inflow onto the shelf. Our data span from 2004 to the beginning of 2014. In the Drygalski Trough, the CDW enters as a 150 m thick layer between 250 and 400 m, and moves upward towards the south. At the mooring location, about 50 km from the shelf break, two main CDW cores can be observed: one on the east side of the trough spreading along the west slope of Mawson Bank from about 200 m to the bottom and the other one in the central-west side from 200 m to about 350 m depth. A signature of this lighter and relatively warm water is detected by the instruments on the mooring at bottom of the Drygalski Trough. High frequency periodic CDW intrusion at the bottom of the trough is related to the diurnal and spring/neap tidal cycles. At lower frequency, a seasonal variability of the CDW intrusion is noticed. A strong inflow of CDW is observed every year at the end of December, while the CDW inflow is at its seasonal minimum during the beginning of the austral fall. In addition an interannual variability is also evident. A change of the CDW intrusion before and after 2010 is observed.

Linking precious metal enrichment and halogen cycling in mafic magmatic systems: insights from the Rum layered intrusion, NW Scotland

NASA Astrophysics Data System (ADS)

Kelly, A. P.; O'Driscoll, B.; Clay, P. L.; Burgess, R.

2017-12-01

Layered intrusions host the world's largest known concentrations of the platinum-group elements (PGE). Emphasis has been attached to the role of halogen-bearing fluids in concentrating the precious metals, but whether this occurs at the magmatic stage, or via subsequent metasomatism, is actively debated. One obstacle to progress has been the analytical difficulty of measuring low abundances of the halogens in the cumulate products of layered intrusions. To elucidate the importance of the halogens in facilitating PGE-mineralisation, as well as fingerprint halogen provenance and assess the importance of halogen cycling in mafic magma systems more generally, a suite of samples encompassing different stages of activity of the Palaeogene Rum layered intrusion was investigated. Halogen abundances were measured by neutron irradiation noble gas mass spectrometric analysis, permitting the detection of relatively low (ppm-ppb) abundances of Cl, Br and I in mg-sized samples. The samples include PGE-enriched chromite seams, various cumulates (e.g., peridotites), picrites (approximating the Rum parental magma), and pegmatites representing volatile-rich melts that circulated the intrusion at a late-stage in its solidification history. The new data reveal that PGE-bearing chromite seams contain relatively low Cl concentrations (2-3 ppm), with high molar ratios of Br/Cl and I/Cl (0.005 and 0.009, respectively). The picrites and cumulates have Br/Cl and I/Cl ratios close to sub-continental lithospheric mantle values of approximately 0.0013 and 0.00002, respectively, and thus likely reflect the Rum magma source region. A positive correlation between Cl and Br signifies comparable partitioning behaviour in all samples. However, I is more variable, displaying a positive correlation with Cl for more primitive samples (e.g. picrite and peridotite), and seemingly decoupling from Br and Cl in chromite seams and pegmatites. The relative enrichment of I over Cl in the chromite seams points to the local involvement of an organic-rich sedimentary assimilant and potentially represents an important trigger for PGE-mineralisation. Similarly high I/Cl signatures in some of the late-stage pegmatites suggest that fluids with this distinctive composition circulated the cooling Rum intrusion for a protracted period of time.

Verifying the secure setup of Unix client/servers and detection of network intrusion

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

Feingold, R.; Bruestle, H.R.; Bartoletti, T.

1995-07-01

This paper describes our technical approach to developing and delivering Unix host- and network-based security products to meet the increasing challenges in information security. Today`s global ``Infosphere`` presents us with a networked environment that knows no geographical, national, or temporal boundaries, and no ownership, laws, or identity cards. This seamless aggregation of computers, networks, databases, applications, and the like store, transmit, and process information. This information is now recognized as an asset to governments, corporations, and individuals alike. This information must be protected from misuse. The Security Profile Inspector (SPI) performs static analyses of Unix-based clients and servers to checkmore » on their security configuration. SPI`s broad range of security tests and flexible usage options support the needs of novice and expert system administrators alike. SPI`s use within the Department of Energy and Department of Defense has resulted in more secure systems, less vulnerable to hostile intentions. Host-based information protection techniques and tools must also be supported by network-based capabilities. Our experience shows that a weak link in a network of clients and servers presents itself sooner or later, and can be more readily identified by dynamic intrusion detection techniques and tools. The Network Intrusion Detector (NID) is one such tool. NID is designed to monitor and analyze activity on an Ethernet broadcast Local Area Network segment and produce transcripts of suspicious user connections. NID`s retrospective and real-time modes have proven invaluable to security officers faced with ongoing attacks to their systems and networks.« less

Identification of Tropical-Extratropical Interactions and Extreme Precipitation Events in the Middle East Based On Potential Vorticity and Moisture Transport

NASA Astrophysics Data System (ADS)

de Vries, A. J.; Ouwersloot, H. G.; Feldstein, S. B.; Riemer, M.; El Kenawy, A. M.; McCabe, M. F.; Lelieveld, J.

2018-01-01

Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability, and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.

Zernike ultrasonic tomography for fluid velocity imaging based on pipeline intrusive time-of-flight measurements.

PubMed

Besic, Nikola; Vasile, Gabriel; Anghel, Andrei; Petrut, Teodor-Ion; Ioana, Cornel; Stankovic, Srdjan; Girard, Alexandre; d'Urso, Guy

2014-11-01

In this paper, we propose a novel ultrasonic tomography method for pipeline flow field imaging, based on the Zernike polynomial series. Having intrusive multipath time-offlight ultrasonic measurements (difference in flight time and speed of ultrasound) at the input, we provide at the output tomograms of the fluid velocity components (axial, radial, and orthoradial velocity). Principally, by representing these velocities as Zernike polynomial series, we reduce the tomography problem to an ill-posed problem of finding the coefficients of the series, relying on the acquired ultrasonic measurements. Thereupon, this problem is treated by applying and comparing Tikhonov regularization and quadratically constrained ℓ1 minimization. To enhance the comparative analysis, we additionally introduce sparsity, by employing SVD-based filtering in selecting Zernike polynomials which are to be included in the series. The first approach-Tikhonov regularization without filtering, is used because it is the most suitable method. The performances are quantitatively tested by considering a residual norm and by estimating the flow using the axial velocity tomogram. Finally, the obtained results show the relative residual norm and the error in flow estimation, respectively, ~0.3% and ~1.6% for the less turbulent flow and ~0.5% and ~1.8% for the turbulent flow. Additionally, a qualitative validation is performed by proximate matching of the derived tomograms with a flow physical model.

Dimensions of maternal parenting and infants’ autonomic functioning interactively predict early internalizing behavior problems

PubMed Central

Propper, Cathi; Gueron-Sela, Noa; Mills-Koonce, W. Roger

2015-01-01

Developmental pathways to childhood internalizing behavior problems are complex, with both environmental and child-level factors contributing to their emergence. The authors use data from a prospective longitudinal study (n = 206) to examine the associations between dimensions of caregiving experiences in the first year of life and anxious/depressed and withdrawn behaviors in early childhood. Additionally, the authors examine the extent to which these associations were moderated by infants’ autonomic functioning in the first year of life indexed using measures of respiratory sinus arrhythmia (RSA) and heart period (HP). Findings suggest that higher levels of maternal sensitivity in infancy are associated with fewer anxious/depressed and withdrawn behaviors at age 3 years. Negative intrusiveness was found to be positively associated with children’s anxious/depressed behaviors but not withdrawn behaviors. Further, moderation analyses suggested that the link between negative intrusive parenting during infancy and subsequent anxious/depressed behaviors is exacerbated for infants with average or low baseline HP and that positive engaging parenting during infancy was negatively related to withdrawn behaviors for infants demonstrating average to high levels baseline HP. Interestingly, RSA was not found to moderate the associations between parenting in infancy and later internalizing behavior problems suggesting that, during infancy, overall autonomic functioning may have greater implications for the development of internalizing behaviors than do parasympathetic influences alone. Implications of these findings and future directions for research are discussed. PMID:26063322

AIDE - Advanced Intrusion Detection Environment

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

Smith, Cathy L.

2013-04-28

Would you like to know when someone has dropped an undesirable executable binary on our system? What about something less malicious such as a software installation by a user? What about the user who decides to install a newer version of mod_perl or PHP on your web server without letting you know beforehand? Or even something as simple as when an undocumented config file change is made by another member of the admin group? Do you even want to know about all the changes that happen on a daily basis on your server? The purpose of an intrusion detection systemmore » (IDS) is to detect unauthorized, possibly malicious activity. The purpose of a host-based IDS, or file integrity checker, is check for unauthorized changes to key system files, binaries, libraries, and directories on the system. AIDE is an Open Source file and directory integrity checker. AIDE will let you know when a file or directory has been added, deleted, modified. It is included with the Red Hat Enterprise 6. It is available for other Linux distros. This is a case study describing the process of configuring AIDE on an out of the box RHEL6 installation. Its goal is to illustrate the thinking and the process by which a useful AIDE configuration is built.« less

Non-contact arrhythmia assessment in natural settings: a step toward preventive cardiac care

NASA Astrophysics Data System (ADS)

Amelard, Robert; Hughson, Richard L.; Clausi, David A.; Wong, Alexander

2017-02-01

Cardiovascular disease is a major contributor to US morbidity. Taking preventive action can greatly reduce or eliminate the impact on quality of life. However, many issues often go undetected until the patient presents a physical symptom. Non-intrusive continuous cardiovascular monitoring systems may make detecting and monitoring abnormalities earlier feasible. One candidate system is photoplethysmographic imaging (PPGI), which is able to assess arterial blood pulse characteristics in one or multiple individuals remotely from a distance. In this case study, we showed that PPGI can be used to detect cardiac arrhythmia that would otherwise require contact-based monitoring techniques. Using a novel system, coded hemodynamic imaging (CHI), strong temporal blood pulse waveform signals were extracted at a distance of 1.5 m from the participant using 850-1000 nm diffuse illumination for deep tissue penetration. Data were recorded at a sampling rate of 60 Hz, providing a temporal resolution of 17 ms. The strong fidelity of the signal allowed for both temporal and spectral assessment of abnormal blood pulse waveforms, ultimately to detect the onset of abnormal cardiac events. Data from a participant with arrhythmia was analyzed and compared against normal blood pulse waveform data to validate CHI's ability to assess cardiac arrhythmia. Results indicate that CHI can be used as a non-intrusive continuous cardiac monitoring system.

Extending the life of mature basins in the North Sea and imaging sub-basalt and sub-intrusive structures using seismic intensity monitoring.

NASA Astrophysics Data System (ADS)

De Siena, Luca; Rawlinson, Nicholas

2016-04-01

Non-standard seismic imaging (velocity, attenuation, and scattering tomography) of the North Sea basins by using unexploited seismic intensities from previous passive and active surveys are key for better imaging and monitoring fluid under the subsurface. These intensities provide unique solutions to the problem of locating/tracking gas/fluid movements in the crust and depicting sub-basalt and sub-intrusives in volcanic reservoirs. The proposed techniques have been tested in volcanic Islands (Deception Island) and have been proved effective at monitoring fracture opening, imaging buried fluid-filled bodies, and tracking water/gas interfaces. These novel seismic attributes are modelled in space and time and connected with the lithology of the sampled medium, specifically density and permeability with as key output a novel computational code with strong commercial potential.

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

NASA Technical Reports Server (NTRS)

West, Thomas K., IV; Gumbert, Clyde

2017-01-01

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

Mathematical analysis of a sharp-diffuse interfaces model for seawater intrusion

NASA Astrophysics Data System (ADS)

Choquet, C.; Diédhiou, M. M.; Rosier, C.

2015-10-01

We consider a new model mixing sharp and diffuse interface approaches for seawater intrusion phenomena in free aquifers. More precisely, a phase field model is introduced in the boundary conditions on the virtual sharp interfaces. We thus include in the model the existence of diffuse transition zones but we preserve the simplified structure allowing front tracking. The three-dimensional problem then reduces to a two-dimensional model involving a strongly coupled system of partial differential equations of parabolic type describing the evolution of the depths of the two free surfaces, that is the interface between salt- and freshwater and the water table. We prove the existence of a weak solution for the model completed with initial and boundary conditions. We also prove that the depths of the two interfaces satisfy a coupled maximum principle.

A Non-Intrusive Pressure Sensor by Detecting Multiple Longitudinal Waves

PubMed Central

Zhou, Hongliang; Lin, Weibin; Ge, Xiaocheng; Zhou, Jian

2016-01-01

Pressure vessels are widely used in industrial fields, and some of them are safety-critical components in the system—for example, those which contain flammable or explosive material. Therefore, the pressure of these vessels becomes one of the critical measurements for operational management. In the paper, we introduce a new approach to the design of non-intrusive pressure sensors, based on ultrasonic waves. The model of this sensor is built based upon the travel-time change of the critically refracted longitudinal wave (LCR wave) and the reflected longitudinal waves with the pressure. To evaluate the model, experiments are carried out to compare the proposed model with other existing models. The results show that the proposed model can improve the accuracy compared to models based on a single wave. PMID:27527183

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

NASA Astrophysics Data System (ADS)

Ahmed, Farid; Johnson, Tommy; Tsui, Sonia

2012-06-01

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

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

DTIC Science & Technology

2015-09-17

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

Evaluation of a Cyber Security System for Hospital Network.

PubMed

Faysel, Mohammad A

2015-01-01

Most of the cyber security systems use simulated data in evaluating their detection capabilities. The proposed cyber security system utilizes real hospital network connections. It uses a probabilistic data mining algorithm to detect anomalous events and takes appropriate response in real-time. On an evaluation using real-world hospital network data consisting of incoming network connections collected for a 24-hour period, the proposed system detected 15 unusual connections which were undetected by a commercial intrusion prevention system for the same network connections. Evaluation of the proposed system shows a potential to secure protected patient health information on a hospital network.

El Ruido: Un Problema para la Salud (Noise: A Health Problem).

ERIC Educational Resources Information Center

Environmental Protection Agency, Washington, DC. Office of Noise Abatement and Control.

This booklet contains nine sections describing ways in which noise may endanger health and well-being. Sections are included on: (1) hearing loss; (2) heart disease; (3) other reactions by the body; (4) effects on the unborn; (5) special effects on children; (6) intrusion at home and work; (7) mental and social well-being; and (8) danger to life…

AMDIS Case Conference

PubMed Central

Graham, J.; Levick, D.; Schreiber, R.

2010-01-01

Clinical decision support that provides enhanced patient safety at the point of care frequently encounters significant pushback from clinicians who find the process intrusive or time-consuming. We present a hypothetical medical center’s dilemma about its allergy alerting system and discuss similar problems faced by real hospitals. We then share some lessons learned and best practices for institutions who wish to implement these tools themselves. PMID:23616828