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

PubMed

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

2016-08-01

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

An 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

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

PubMed

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

2009-01-01

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

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 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.

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

PubMed Central

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

2009-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

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

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.

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

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.

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

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 in Database Systems

NASA Astrophysics Data System (ADS)

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

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

An 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.

Alerts Visualization and Clustering in Network-based Intrusion Detection

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

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

2010-04-01

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

An 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

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.

Design of an Evolutionary Approach for Intrusion Detection

PubMed Central

2013-01-01

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

Intrusion detection using rough set classification.

PubMed

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

2004-09-01

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

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

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.

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

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

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.

A system for distributed intrusion detection

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

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

1991-01-01

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

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.

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

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

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.

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.

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

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.

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.

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.

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...

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.

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

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

An immunity-based anomaly detection system with sensor agents.

PubMed

Okamoto, Takeshi; Ishida, Yoshiteru

2009-01-01

This paper proposes an immunity-based anomaly detection system with sensor agents based on the specificity and diversity of the immune system. Each agent is specialized to react to the behavior of a specific user. Multiple diverse agents decide whether the behavior is normal or abnormal. Conventional systems have used only a single sensor to detect anomalies, while the immunity-based system makes use of multiple sensors, which leads to improvements in detection accuracy. In addition, we propose an evaluation framework for the anomaly detection system, which is capable of evaluating the differences in detection accuracy between internal and external anomalies. This paper focuses on anomaly detection in user's command sequences on UNIX-like systems. In experiments, the immunity-based system outperformed some of the best conventional systems.

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

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

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.

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

Use of behavioral biometrics in intrusion detection and online gaming

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2006-04-01

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

A 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.

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.

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

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.

Towards Reliable Evaluation of Anomaly-Based Intrusion Detection Performance

NASA Technical Reports Server (NTRS)

Viswanathan, Arun

2012-01-01

This report describes the results of research into the effects of environment-induced noise on the evaluation process for anomaly detectors in the cyber security domain. This research was conducted during a 10-week summer internship program from the 19th of August, 2012 to the 23rd of August, 2012 at the Jet Propulsion Laboratory in Pasadena, California. The research performed lies within the larger context of the Los Angeles Department of Water and Power (LADWP) Smart Grid cyber security project, a Department of Energy (DoE) funded effort involving the Jet Propulsion Laboratory, California Institute of Technology and the University of Southern California/ Information Sciences Institute. The results of the present effort constitute an important contribution towards building more rigorous evaluation paradigms for anomaly-based intrusion detectors in complex cyber physical systems such as the Smart Grid. Anomaly detection is a key strategy for cyber intrusion detection and operates by identifying deviations from profiles of nominal behavior and are thus conceptually appealing for detecting "novel" attacks. Evaluating the performance of such a detector requires assessing: (a) how well it captures the model of nominal behavior, and (b) how well it detects attacks (deviations from normality). Current evaluation methods produce results that give insufficient insight into the operation of a detector, inevitably resulting in a significantly poor characterization of a detectors performance. In this work, we first describe a preliminary taxonomy of key evaluation constructs that are necessary for establishing rigor in the evaluation regime of an anomaly detector. We then focus on clarifying the impact of the operational environment on the manifestation of attacks in monitored data. We show how dynamic and evolving environments can introduce high variability into the data stream perturbing detector performance. Prior research has focused on understanding the impact of this

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

NASA Astrophysics Data System (ADS)

Li, Hong; Ding, Xue

2017-03-01

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

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.

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

Realistic computer network simulation for network intrusion detection dataset generation

NASA Astrophysics Data System (ADS)

Payer, Garrett

2015-05-01

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

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

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.

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.

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.

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…

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

Enhanced Deployment Strategy for Role-based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

NASA Astrophysics Data System (ADS)

Gendreau, Audrey

Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing

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.

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.

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…

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.

Smell Detection Agent Based Optimization Algorithm

NASA Astrophysics Data System (ADS)

Vinod Chandra, S. S.

2016-09-01

In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

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.

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

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.

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

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

NASA Astrophysics Data System (ADS)

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

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

A 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.

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

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

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.

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

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

PubMed

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

2015-01-01

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

Intrusion-based reasoning and depression: cross-sectional and prospective relationships.

PubMed

Berle, David; Moulds, Michelle L

2014-01-01

Intrusion-based reasoning refers to the tendency to form interpretations about oneself or a situation based on the occurrence of a negative intrusive autobiographical memory. Intrusion-based reasoning characterises post-traumatic stress disorder, but has not yet been investigated in depression. We report two studies that aimed to investigate this. In Study 1 both high (n = 42) and low (n = 28) dysphoric participants demonstrated intrusion-based reasoning. High-dysphoric individuals engaged in self-referent intrusion-based reasoning to a greater extent than did low-dysphoric participants. In Study 2 there were no significant differences in intrusion-based reasoning between currently depressed (n = 27) and non-depressed (n = 51) participants, and intrusion-based reasoning did not predict depressive symptoms at 6-month follow-up. Interestingly, previously (n = 26) but not currently (n = 27) depressed participants engaged in intrusion-based reasoning to a greater extent than never-depressed participants (n = 25), indicating the possibility that intrusion-based reasoning may serve as a "scar" from previous episodes. The implications of these findings are discussed.

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.

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 Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features.

PubMed

Amudha, P; Karthik, S; Sivakumari, S

2015-01-01

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

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

PubMed Central

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

2015-01-01

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

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

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

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.

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.

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

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.

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.

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.

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

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

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

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 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.

Identification of chemical warfare agents using a portable microchip-based detection device

NASA Astrophysics Data System (ADS)

Petkovic-Duran, K.; Swallow, A.; Sexton, B. A.; Glenn, F.; Zhu, Y.

2011-12-01

Analysis of chemical warfare agents (CWAs) and their degradation products is an important verification component in support of the Chemical Weapons Convention and urgently demanding rapid and reliable analytical methods. A portable microchip electrophoresis (ME) device with contactless conductivity (CCD) detection was developed for the in situ identification of CWA and their degradation products. A 10mM MES/His, 0.4mM CTAB - based separation electrolyte accomplished the analysis of Sarin (GB), Tabun( GA) and Soman (GD) in less than 1 min, which is the fastest screening of nerve agents achieved with portable ME and CCD based detection methods to date. Reproducibility of detection was successfully demonstrated on simultaneous detection of GB (200ppm) and GA (278ppm). Reasonable agreement for the four consecutive runs was achieved with the mean peak time for Sarin of 29.15s, and the standard error of 0.58s or 2%. GD and GA were simultaneously detected with their degradation products methylphosphonic acid (MPA), pinacolyl methylphosphonic acid (PMPA) and O-Ethyl Phosphorocyanidate (GAHP and GAHP1) respectively. The detection limit for Sarin was around 35ppb. To the best of our knowledge this is the best result achieved in microchip electrophoresis and contactless conductivity based detection to date.

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

Tissue-based standoff biosensors for detecting chemical warfare agents

DOEpatents

Greenbaum, Elias; Sanders, Charlene A.

2003-11-18

A tissue-based, deployable, standoff air quality sensor for detecting the presence of at least one chemical or biological warfare agent, includes: a cell containing entrapped photosynthetic tissue, the cell adapted for analyzing photosynthetic activity of the entrapped photosynthetic tissue; means for introducing an air sample into the cell and contacting the air sample with the entrapped photosynthetic tissue; a fluorometer in operable relationship with the cell for measuring photosynthetic activity of the entrapped photosynthetic tissue; and transmitting means for transmitting analytical data generated by the fluorometer relating to the presence of at least one chemical or biological warfare agent in the air sample, the sensor adapted for deployment into a selected area.

A biolayer interferometry-based assay for rapid and highly sensitive detection of biowarfare agents.

PubMed

Mechaly, Adva; Cohen, Hila; Cohen, Ofer; Mazor, Ohad

2016-08-01

Biolayer interferometry (BLI) is an optical technique that uses fiber-optic biosensors for label-free real-time monitoring of protein-protein interactions. In this study, we coupled the advantages of the Octet Red BLI system (automation, fluidics-free, and on-line monitoring) with a signal enhancement step and developed a rapid and sensitive immunological-based method for detection of biowarfare agents. As a proof of concept, we chose to demonstrate the efficacy of this novel assay for the detection of agents representing two classes of biothreats, proteinaceous toxins, and bacterial pathogens: ricin, a lethal plant toxin, and the gram-negative bacterium Francisella tularensis, the causative agent of tularemia. The assay setup consisted of biotinylated antibodies immobilized to the biosensor coupled with alkaline phosphatase-labeled antibodies as the detection moiety to create nonsoluble substrate crystals that precipitate on the sensor surface, thereby inducing a significant wavelength interference. It was found that this BLI-based assay enables sensitive detection of these pathogens (detection limits of 10 pg/ml and 1 × 10(4) pfu/ml ricin and F. tularensis, respectively) within a very short time frame (17 min). Owing to its simplicity, this assay can be easily adapted to detect other analytes in general, and biowarfare agents in particular, in a rapid and sensitive manner. Copyright © 2016 Elsevier Inc. All rights reserved.

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...

MFIRE-2: A Multi Agent System for Flow-Based Intrusion Detection Using Stochastic Search

DTIC Science & Technology

2012-03-01

attacks that are distributed in nature , but may not protect individual systems effectively without incurring large bandwidth penalties while collecting...system-level information to help prepare for more significant attacks. The type of information potentially revealed by footprinting includes account...key areas where MAS may be appropriate: • The environment is open, highly dynamic, uncertain, or complex • Agents are a natural metaphor—Many

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

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

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

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

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

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

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

SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases

NASA Astrophysics Data System (ADS)

Pinzón, Cristian; de Paz, Yanira; Bajo, Javier; Abraham, Ajith; Corchado, Juan M.

One of the main attacks to ubiquitous databases is the structure query language (SQL) injection attack, which causes severe damages both in the commercial aspect and in the user’s confidence. This chapter proposes the SiC architecture as a solution to the SQL injection attack problem. This is a hierarchical distributed multiagent architecture, which involves an entirely new approach with respect to existing architectures for the prevention and detection of SQL injections. SiC incorporates a kind of intelligent agent, which integrates a case-based reasoning system. This agent, which is the core of the architecture, allows the application of detection techniques based on anomalies as well as those based on patterns, providing a great degree of autonomy, flexibility, robustness and dynamic scalability. The characteristics of the multiagent system allow an architecture to detect attacks from different types of devices, regardless of the physical location. The architecture has been tested on a medical database, guaranteeing safe access from various devices such as PDAs and notebook computers.

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

Advances in Magnetic Resonance Imaging Contrast Agents for Biomarker Detection

PubMed Central

Sinharay, Sanhita; Pagel, Mark D.

2016-01-01

Recent advances in magnetic resonance imaging (MRI) contrast agents have provided new capabilities for biomarker detection through molecular imaging. MRI contrast agents based on the T2 exchange mechanism have more recently expanded the armamentarium of agents for molecular imaging. Compared with T1 and T2* agents, T2 exchange agents have a slower chemical exchange rate, which improves the ability to design these MRI contrast agents with greater specificity for detecting the intended biomarker. MRI contrast agents that are detected through chemical exchange saturation transfer (CEST) have even slower chemical exchange rates. Another emerging class of MRI contrast agents uses hyperpolarized 13C to detect the agent with outstanding sensitivity. These hyperpolarized 13C agents can be used to track metabolism and monitor characteristics of the tissue microenvironment. Together, these various MRI contrast agents provide excellent opportunities to develop molecular imaging for biomarker detection. PMID:27049630

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

NASA Astrophysics Data System (ADS)

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

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

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.

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.

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.

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.

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

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.

An ethernet/IP security review with intrusion detection applications

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

Laughter, S. A.; Williams, R. D.

2006-07-01

Supervisory Control and Data Acquisition (SCADA) and automation networks, used throughout utility and manufacturing applications, have their own specific set of operational and security requirements when compared to corporate networks. The modern climate of heightened national security and awareness of terrorist threats has made the security of these systems of prime concern. There is a need to understand the vulnerabilities of these systems and how to monitor and protect them. Ethernet/IP is a member of a family of protocols based on the Control and Information Protocol (CIP). Ethernet/IP allows automation systems to be utilized on and integrated with traditional TCP/IPmore » networks, facilitating integration of these networks with corporate systems and even the Internet. A review of the CIP protocol and the additions Ethernet/IP makes to it has been done to reveal the kind of attacks made possible through the protocol. A set of rules for the SNORT Intrusion Detection software is developed based on the results of the security review. These can be used to monitor, and possibly actively protect, a SCADA or automation network that utilizes Ethernet/IP in its infrastructure. (authors)« less

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

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.

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.

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.

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.

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

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.

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

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)

Using Informatics-, Bioinformatics- and Genomics-Based Approaches for the Molecular Surveillance and Detection of Biothreat Agents

NASA Astrophysics Data System (ADS)

Seto, Donald

The convergence and wealth of informatics, bioinformatics and genomics methods and associated resources allow a comprehensive and rapid approach for the surveillance and detection of bacterial and viral organisms. Coupled with the continuing race for the fastest, most cost-efficient and highest-quality DNA sequencing technology, that is, "next generation sequencing", the detection of biological threat agents by `cheaper and faster' means is possible. With the application of improved bioinformatic tools for the understanding of these genomes and for parsing unique pathogen genome signatures, along with `state-of-the-art' informatics which include faster computational methods, equipment and databases, it is feasible to apply new algorithms to biothreat agent detection. Two such methods are high-throughput DNA sequencing-based and resequencing microarray-based identification. These are illustrated and validated by two examples involving human adenoviruses, both from real-world test beds.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

Chemical and biological threat-agent detection using electrophoresis-based lab-on-a-chip devices.

PubMed

Borowsky, Joseph; Collins, Greg E

2007-10-01

The ability to separate complex mixtures of analytes has made capillary electrophoresis (CE) a powerful analytical tool since its modern configuration was first introduced over 25 years ago. The technique found new utility with its application to the microfluidics based lab-on-a-chip platform (i.e., microchip), which resulted in ever smaller footprints, sample volumes, and analysis times. These features, coupled with the technique's potential for portability, have prompted recent interest in the development of novel analyzers for chemical and biological threat agents. This article will comment on three main areas of microchip CE as applied to the separation and detection of threat agents: detection techniques and their corresponding limits of detection, sampling protocol and preparation time, and system portability. These three areas typify the broad utility of lab-on-a-chip for meeting critical, present-day security, in addition to illustrating areas wherein advances are necessary.

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...

μ-PADs for detection of chemical warfare agents.

PubMed

Pardasani, Deepak; Tak, Vijay; Purohit, Ajay K; Dubey, D K

2012-12-07

Conventional methods of detection of chemical warfare agents (CWAs) based on chromogenic reactions are time and solvent intensive. The development of cost, time and solvent effective microfluidic paper based analytical devices (μ-PADs) for the detection of nerve and vesicant agents is described. The detection of analytes was based upon their reactions with rhodamine hydroxamate and para-nitrobenzyl pyridine, producing red and blue colours respectively. Reactions were optimized on the μ-PADs to produce the limits of detection (LODs) as low as 100 μM for sulfur mustard in aqueous samples. Results were quantified with the help of a simple desktop scanner and Photoshop software. Sarin achieved a linear response in the two concentration ranges of 20-100 mM and 100-500 mM, whereas the response of sulfur mustard was found to be linear in the concentration range of 10-75 mM. Results were precise enough to establish the μ-PADs as a valuable tool for security personnel fighting against chemical terrorism.

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.

TOXICITY-BASED CHEMICAL AGENT DETECTION SYSTEMS: CONTINUOUS MONITOR AND EXPOSURE HISTORY

EPA Science Inventory

This project will develop and characterize chemical agent detection systems that will provide broad toxicological screening information to first responders and building decontamination personnel. The primary goal for this technology is to detect the presence of airborne chemic...

A Multi Agent System for Flow-Based Intrusion Detection

DTIC Science & Technology

2013-03-01

Student t-test, as it is less likely to spuriously indicate significance because of the presence of outliers [128]. We use the MATLAB ranksum function [77...effectiveness of self-organization and “ entangled hierarchies” for accomplishing scenario objectives. One of the interesting features of SOMAS is the ability...cross-validation and automatic model selection. It has interfaces for Java, Python, R, Splus, MATLAB , Perl, Ruby, and LabVIEW. Kernels: linear

Passive Standoff Detection of Chemical Warfare Agents on Surfaces

NASA Astrophysics Data System (ADS)

Thériault, Jean-Marc; Puckrin, Eldon; Hancock, Jim; Lecavalier, Pierre; Lepage, Carmela Jackson; Jensen, James O.

2004-11-01

Results are presented on the passive standoff detection and identification of chemical warfare (CW) liquid agents on surfaces by the Fourier-transform IR radiometry. This study was performed during surface contamination trials at Defence Research and Development Canada-Suffield in September 2002. The goal was to verify that passive long-wave IR spectrometric sensors can potentially remotely detect surfaces contaminated with CW agents. The passive sensor, the Compact Atmospheric Sounding Interferometer, was used in the trial to obtain laboratory and field measurements of CW liquid agents, HD and VX. The agents were applied to high-reflectivity surfaces of aluminum, low-reflectivity surfaces of Mylar, and several other materials including an armored personnel carrier. The field measurements were obtained at a standoff distance of 60 m from the target surfaces. Results indicate that liquid contaminant agents deposited on high-reflectivity surfaces can be detected, identified, and possibly quantified with passive sensors. For low-reflectivity surfaces the presence of the contaminants can usually be detected; however, their identification based on simple correlations with the absorption spectrum of the pure contaminant is not possible.

Joint Chemical Agent Detector (JCAD): the future of chemical agent detection

NASA Astrophysics Data System (ADS)

Laljer, Charles E.; Owen, Jeffery L.

2002-06-01

The Joint Chemical Agent Detector (JCAD) will provide state of the art chemical warfare agent detection capability to ground vehicle operators. Intelligence sources estimate that over twenty counties have active chemical weapons programs. The spread of chemical weapons to third world nations, coupled with the potential for US involvement in these areas in an operational or support capacity, increases the probability that the Joint Services may encounter chemical agents and toxic industrial materials anywhere in the world. Currently, fielded chemical agent detectors are bulky, labor intensive, and subject to false readings. No legacy detector is sensitive enough to provide detection and warning of the low dose hazards associated with miosis contamination. The JCAD will provide a small, lightweight chemical agent detector for vehicle interiors, aircraft, individual personnel, shipboard, and fixed site locations. The system provides a common detection components across multi-service platforms. This common detector system will allow the Joint Services to use the same operational and support concept for more efficient utilization of resources. The JCAD will detect, identify, quantify, and warn of the presence of chemical agents prior to onset of miosis. Upon detection of chemical agents, the detector will provide local and remote audible and visual alarms to the operators. Advance warning will provide the vehicle crew with the time necessary to protect themselves from the lethal effects of chemical agents. The JCAD will also be capable of being upgraded to protect against future chemical agent threats. The JCAD will provide the vehicle operators with the warning necessary to survive and fight in a chemical warfare agent threat environment.

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

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.

SAMPLING-BASED APPROACH TO INVESTIGATING VAPOR INTRUSION

EPA Science Inventory

Vapor intrusion is defined as the migration of volatile organic compounds (VOCs) into occupied buildings from contaminated soil or ground water. EPA recently developed guidance to facilitate assessment of vapor intrusion at sites regulated by RCRA and CERCLA. The EPA guidance e...

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

Joint chemical agent detector (JCAD): the future of chemical agent detection

NASA Astrophysics Data System (ADS)

Laljer, Charles E.

2003-08-01

The Joint Chemical Agent Detector (JCAD) has continued development through 2002. The JCAD has completed Contractor Validation Testing (CVT) that included chemical warfare agent testing, environmental testing, electromagnetic interferent testing, and platform integration validation. The JCAD provides state of the art chemical warfare agent detection capability to military and homeland security operators. Intelligence sources estimate that over twenty countries have active chemical weapons programs. The spread of weapons of mass destruction (and the industrial capability for manufacture of these weapons) to third world nations and terrorist organizations has greatly increased the chemical agent threat to U.S. interests. Coupled with the potential for U.S. involvement in localized conflicts in an operational or support capacity, increases the probability that the military Joint Services may encounter chemical agents anywhere in the world. The JCAD is a small (45 in3), lightweight (2 lb.) chemical agent detector for vehicle interiors, aircraft, individual personnel, shipboard, and fixed site locations. The system provides a common detection component across multi-service platforms. This common detector system will allow the Joint Services to use the same operational and support concept for more efficient utilization of resources. The JCAD detects, identifies, quantifies, and warns of the presence of chemical agents prior to onset of miosis. Upon detection of chemical agents, the detector provides local and remote audible and visual alarms to the operators. Advance warning will provide the vehicle crew and other personnel in the local area with the time necessary to protect themselves from the lethal effects of chemical agents. The JCAD is capable of being upgraded to protect against future chemical agent threats. The JCAD provides the operator with the warning necessary to survive and fight in a chemical warfare agent threat environment.

Tissue-based water quality biosensors for detecting chemical warfare agents

DOEpatents

Greenbaum, Elias [Oak Ridge, TN; Sanders, Charlene A [Knoxville, TN

2003-05-27

A water quality sensor for detecting the presence of at least one chemical or biological warfare agent includes: a cell; apparatus for introducing water into the cell and discharging water from the cell adapted for analyzing photosynthetic activity of naturally occurring, free-living, indigenous photosynthetic organisms in water; a fluorometer for measuring photosynthetic activity of naturally occurring, free-living, indigenous photosynthetic organisms drawn into the cell; and an electronics package that analyzes raw data from the fluorometer and emits a signal indicating the presence of at least one chemical or biological warfare agent in the water.

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

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

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

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

A 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.

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.

Advanced nanoelectronic architectures for THz-based biological agent detection

NASA Astrophysics Data System (ADS)

Woolard, Dwight L.; Jensen, James O.

2009-02-01

The U.S. Army Research Office (ARO) and the U.S. Army Edgewood Chemical Biological Center (ECBC) jointly lead and support novel research programs that are advancing the state-of-the-art in nanoelectronic engineering in application areas that have relevance to national defense and security. One fundamental research area that is presently being emphasized by ARO and ECBC is the exploratory investigation of new bio-molecular architectural concepts that can be used to achieve rapid, reagent-less detection and discrimination of biological warfare (BW) agents, through the control of multi-photon and multi-wavelength processes at the nanoscale. This paper will overview an ARO/ECBC led multidisciplinary research program presently under the support of the U.S. Defense Threat Reduction Agency (DTRA) that seeks to develop new devices and nanoelectronic architectures that are effective for extracting THz signatures from target bio-molecules. Here, emphasis will be placed on the new nanosensor concepts and THz/Optical measurement methodologies for spectral-based sequencing/identification of genetic molecules.

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.

Testing the differential effects of acceptance and attention-based psychological interventions on intrusive thoughts and worry.

PubMed

Ainsworth, B; Bolderston, H; Garner, M

2017-04-01

Worry is a key component of anxiety and may be an effective target for therapeutic intervention. We compared two psychological processes (attention and acceptance) on the frequency of intrusive worrying thoughts in an experimental worry task. 77 participants were randomised across three groups and completed either a 10 min attention or acceptance-based psychological exercise, or progressive muscle relaxation control. We subsequently measured anxiety, and the content and frequency of intrusive thoughts before and after a 'worry induction task'. Groups did not differ in baseline worry, anxiety or thought intrusions. Both attention and acceptance-based groups experienced fewer negative thought intrusions (post-worry) compared to the relaxation control group. The acceptance exercise had the largest effect, preventing 'worry induction'. Increases in negative intrusive thoughts predicted subjective anxiety. We provide evidence that acceptance and attention psychological exercises may reduce anxiety by reducing the negative thought intrusions that characterise worry. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

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.

Online Deception Detection Using BDI Agents

ERIC Educational Resources Information Center

Merritts, Richard A.

2013-01-01

This research has two facets within separate research areas. The research area of Belief, Desire and Intention (BDI) agent capability development was extended. Deception detection research has been advanced with the development of automation using BDI agents. BDI agents performed tasks automatically and autonomously. This study used these…

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.

Detection and identification of alkylating agents by using a bioinspired "chemical nose".

PubMed

Hertzog-Ronen, Carmit; Borzin, Elena; Gerchikov, Yulia; Tessler, Nir; Eichen, Yoav

2009-10-12

Alkylating agents are simple and reactive molecules that are commonly used in many and diverse fields such as organic synthesis, medicine, and agriculture. Some highly reactive alkylating species are also being used as blister chemical-warfare agents. The detection and identification of alkylating agents is not a trivial issue because of their high reactivity and simple structure. Herein, we report on a new multispot luminescence-based approach to the detection and identification of alkylating agents. In order to demonstrate the potential of the approach, seven pi-conjugated oligomers and polymers bearing nucleophilic pyridine groups, 1-7, were adsorbed onto a solid support and exposed to vapors of alkylators 8-15. The alkylation-induced color-shift patterns of the seven-spot array allow clear discrimination of the different alkylators. The spots are sensitive to minute concentrations of alkylators and, because the detection is based on the formation of new covalent bonds, these spots saturate at about 50 ppb.

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

Nucleic acid in-situ hybridization detection of infectious agents

NASA Astrophysics Data System (ADS)

Thompson, Curtis T.

2000-04-01

Limitations of traditional culture methods and newer polymerase chain reaction (PCR)-based methods for detection and speciation of infectious agents demonstrate the need for more rapid and better diagnostics. Nucleic acid hybridization is a detection technology that has gained wide acceptance in cancer and prenatal cytogenetics. Using a modification of the nucleic acid hybridization technique known as fluorescence in-situ hybridization, infectious agents can be detected in a variety of specimens with high sensitivity and specificity. The specimens derive from all types of human and animal sources including body fluids, tissue aspirates and biopsy material. Nucleic acid hybridization can be performed in less than one hour. The result can be interpreted either using traditional fluorescence microscopy or automated platforms such as micro arrays. This paper demonstrates proof of concept for nucleic acid hybridization detection of different infectious agents. Interpretation within a cytologic and histologic context is possible with fluorescence microscopic analysis, thereby providing confirmatory evidence of hybridization. With careful probe selection, nucleic acid hybridization promises to be a highly sensitive and specific practical diagnostic alternative to culture, traditional staining methods, immunohistochemistry and complicated nucleic acid amplification tests.

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

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.

Method and apparatus for enhanced detection of toxic agents

DOEpatents

Greenbaum, Elias; Rodriguez, Jr., Miguel; Wu, Jie Jayne; Qi, Hairong

2013-10-01

A biosensor based detection of toxins includes enhancing a fluorescence signal by concentrating a plurality of photosynthetic organisms in a fluid into a concentrated region using biased AC electro-osmosis. A measured photosynthetic activity of the photosynthetic organisms is obtained in the concentrated region, where chemical, biological or radiological agents reduce a nominal photosynthetic activity of the photosynthetic organisms. A presence of the chemical, biological and/or radiological agents or precursors thereof, is determined in the fluid based on the measured photosynthetic activity of the concentrated plurality of photosynthetic organisms. A lab-on-a-chip system is used for the concentrating step. The presence of agents is determined from feature vectors, obtained from processing a time dependent signal using amplitude statistics and/or time-frequency analysis, relative to a control signal. A linear discriminant method including support vector machine classification (SVM) is used to identify the agents.

Highly Stable Lyophilized Homogeneous Bead-Based Immunoassays for On-Site Detection of Bio Warfare Agents from Complex Matrices.

PubMed

Mechaly, Adva; Marx, Sharon; Levy, Orly; Yitzhaki, Shmuel; Fisher, Morly

2016-06-21

This study shows the development of dry, highly stable immunoassays for the detection of bio warfare agents in complex matrices. Thermal stability was achieved by the lyophilization of the complete, homogeneous, bead-based immunoassay in a special stabilizing buffer, resulting in a ready-to-use, simple assay, which exhibited long shelf and high-temperature endurance (up to 1 week at 100 °C). The developed methodology was successfully implemented for the preservation of time-resolved fluorescence, Alexa-fluorophores, and horse radish peroxidase-based bead assays, enabling multiplexed detection. The multiplexed assay was successfully implemented for the detection of Bacillus anthracis, botulinum B, and tularemia in complex matrices.

Risk-Based Evaluation of Total Petroleum Hydrocarbons in Vapor Intrusion Studies

PubMed Central

Brewer, Roger; Nagashima, Josh; Kelley, Michael; Heskett, Marvin; Rigby, Mark

2013-01-01

This paper presents a quantitative method for the risk-based evaluation of Total Petroleum Hydrocarbons (TPH) in vapor intrusion investigations. Vapors from petroleum fuels are characterized by a complex mixture of aliphatic and, to a lesser extent, aromatic compounds. These compounds can be measured and described in terms of TPH carbon ranges. Toxicity factors published by USEPA and other parties allow development of risk-based, air and soil vapor screening levels for each carbon range in the same manner as done for individual compounds such as benzene. The relative, carbon range makeup of petroleum vapors can be used to develop weighted, site-specific or generic screening levels for TPH. At some critical ratio of TPH to a targeted, individual compound, the overwhelming proportion of TPH will drive vapor intrusion risk over the individual compound. This is particularly true for vapors associated with diesel and other middle distillate fuels, but can also be the case for low-benzene gasolines or even for high-benzene gasolines if an adequately conservative, target risk is not applied to individually targeted chemicals. This necessitates a re-evaluation of the reliance on benzene and other individual compounds as a stand-alone tool to evaluate vapor intrusion risk associated with petroleum. PMID:23765191

Fluctuation-Enhanced Sensing for Biological Agent Detection and Identification

DTIC Science & Technology

2009-01-01

method for bacterium detection published earlier; sensing and evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise...REPORT TYPE 3. DATES COVERED 00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE Fluctuation-Enhanced Sensing for Biological Agent Detection and...evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise in light scattering to identify spores based on their

Rapid detection of biothreat agents based on cellular machinery.

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

Lane, Todd W.; Gantt, Richard W.

This research addresses rapid and sensitive identification of biological agents in a complex background. We attempted to devise a method by which the specificity of the cellular transcriptional machinery could be used to detect and identify bacterial bio-terror agents in a background of other organisms. Bacterial cells contain RNA polymerases and transcription factors that transcribe genes into mRNA for translation into proteins. RNA polymerases in conjunction with transcription factors recognize regulatory elements (promoters) upstream of the gene. These promoters are, in many cases, recognized by the polymerase and transcription factor combinations of one species only. We have engineered a plasmid,more » for Escherichia coli, containing the virA promoter from the target species Shigella flexneri. This promoter was fused to a reporter gene Green Fluorescent Protein (GFP). In theory the indicator strain (carrying the plasmid) is mixed with the target strain and the two are lysed. The cellular machinery from both cells mixes and the GFP is produced. This report details the results of testing this system.« less

High-Accuracy Ultrasound Contrast Agent Detection Method for Diagnostic Ultrasound Imaging Systems.

PubMed

Ito, Koichi; Noro, Kazumasa; Yanagisawa, Yukari; Sakamoto, Maya; Mori, Shiro; Shiga, Kiyoto; Kodama, Tetsuya; Aoki, Takafumi

2015-12-01

An accurate method for detecting contrast agents using diagnostic ultrasound imaging systems is proposed. Contrast agents, such as microbubbles, passing through a blood vessel during ultrasound imaging are detected as blinking signals in the temporal axis, because their intensity value is constantly in motion. Ultrasound contrast agents are detected by evaluating the intensity variation of a pixel in the temporal axis. Conventional methods are based on simple subtraction of ultrasound images to detect ultrasound contrast agents. Even if the subject moves only slightly, a conventional detection method will introduce significant error. In contrast, the proposed technique employs spatiotemporal analysis of the pixel intensity variation over several frames. Experiments visualizing blood vessels in the mouse tail illustrated that the proposed method performs efficiently compared with conventional approaches. We also report that the new technique is useful for observing temporal changes in microvessel density in subiliac lymph nodes containing tumors. The results are compared with those of contrast-enhanced computed tomography. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

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.

An adaptive neural swarm approach for intrusion defense in ad hoc networks

NASA Astrophysics Data System (ADS)

Cannady, James

2011-06-01

Wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are being increasingly deployed in critical applications due to the flexibility and extensibility of the technology. While these networks possess numerous advantages over traditional wireless systems in dynamic environments they are still vulnerable to many of the same types of host-based and distributed attacks common to those systems. Unfortunately, the limited power and bandwidth available in WSNs and MANETs, combined with the dynamic connectivity that is a defining characteristic of the technology, makes it extremely difficult to utilize traditional intrusion detection techniques. This paper describes an approach to accurately and efficiently detect potentially damaging activity in WSNs and MANETs. It enables the network as a whole to recognize attacks, anomalies, and potential vulnerabilities in a distributive manner that reflects the autonomic processes of biological systems. Each component of the network recognizes activity in its local environment and then contributes to the overall situational awareness of the entire system. The approach utilizes agent-based swarm intelligence to adaptively identify potential data sources on each node and on adjacent nodes throughout the network. The swarm agents then self-organize into modular neural networks that utilize a reinforcement learning algorithm to identify relevant behavior patterns in the data without supervision. Once the modular neural networks have established interconnectivity both locally and with neighboring nodes the analysis of events within the network can be conducted collectively in real-time. The approach has been shown to be extremely effective in identifying distributed network attacks.

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

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

Improving Agent Based Models and Validation through Data Fusion.

PubMed

Laskowski, Marek; Demianyk, Bryan C P; Friesen, Marcia R; McLeod, Robert D; Mukhi, Shamir N

2011-01-01

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level.

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.

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.

Fluorescent sensors for the detection of chemical warfare agents.

PubMed

Burnworth, Mark; Rowan, Stuart J; Weder, Christoph

2007-01-01

Along with biological and nuclear threats, chemical warfare agents are some of the most feared weapons of mass destruction. Compared to nuclear weapons they are relatively easy to access and deploy, which makes them in some aspects a greater threat to national and global security. A particularly hazardous class of chemical warfare agents are the nerve agents. Their rapid and severe effects on human health originate in their ability to block the function of acetylcholinesterase, an enzyme that is vital to the central nervous system. This article outlines recent activities regarding the development of molecular sensors that can visualize the presence of nerve agents (and related pesticides) through changes of their fluorescence properties. Three different sensing principles are discussed: enzyme-based sensors, chemically reactive sensors, and supramolecular sensors. Typical examples are presented for each class and different fluorescent sensors for the detection of chemical warfare agents are summarized and compared.

Greyhound meningoencephalitis: PCR-based detection methods highlight an absence of the most likely primary inducing agents.

PubMed

Daly, P; Drudy, D; Chalmers, W S K; Baxendale, W; Fanning, S; Callanan, J J

2006-12-20

Greyhound meningoencephalitis is currently classified as a breed-associated idiopathic central nervous system inflammatory disorder. The non-suppurative inflammatory response can be distinguished from the other breed-associated disorders based on histopathology and lesion topography, however the nature of the response primarily suggests a viral infection. In the present study PCR and RT-PCR technologies were employed on frozen cerebral tissue from confirmed cases of meningoencephalitis to target specific viruses and protozoa likely to be implicated and to exclude the presence of bacterial 16SrRNA. Secondly, degenerate primers were used to detect viruses of the herpesvirus and flavivirus families. In addition cerebral tissues were probed for West Nile Virus. Viral nucleic acid sequences to Borna disease virus, to louping ill, tick borne encephalitis, West Nile and other flaviviruses were not detected. Canine distemper virus was detected in one animal with 97% homology to strain A75/15. Degenerate PCR for herpesviruses detected viral amplification products in one animal with 90% homology to canine herpesvirus DNA polymerase gene. Protozoal amplification products were only detected in a single dog with pathological confirmation of a combination of lesions of greyhound meningoencephalitis and a protozoal encephalomyelitis. Neospora was confirmed with sequence homology to Austrian strain 1. Bacterial 16SrRNA was not detected. The present study supports previous observations that many of the known microbial causes of canine meningoencephalitis are not involved. Findings could reflect that the causal agent was not specifically targeted for detection, or that the agent is at undetectable levels or has been eliminated from brain tissue. The potential roles of genetics and of molecular mimicry also cannot be discounted.

Detection of Alkylating Agents using Electrical and Mechanical Means

NASA Astrophysics Data System (ADS)

Gerchikov, Yulia; Borzin, Elena; Gannot, Yair; Shemesh, Ariel; Meltzman, Shai; Hertzog-Ronen, Carmit; Tal, Shay; Stolyarova, Sara; Nemirovsky, Yael; Tessler, Nir; Eichen, Yoav

2011-08-01

Alkylating agents are reactive molecules having at least one polar bond between a carbon atom and a good leaving group. These often simple molecules are frequently used in organic synthesis, as sterilizing agents in agriculture and even as anticancer agents in medicine. Unfortunately, for over a century, some of the highly reactive alkylating agents are also being used as blister chemical warfare agents. Being relatively simple to make, the risk is that these will be applied by terrorists as poor people warfare agents. The detection and identification of such alkylating agents is not a simple task because of their high reactivity and simple structure of the reactive site. Here we report on new approaches to the detection and identification of such alkylating agents using electrical (organic field effect transistors) and mechanical (microcantilevers) means.

A new intrusion prevention model using planning knowledge graph

NASA Astrophysics Data System (ADS)

Cai, Zengyu; Feng, Yuan; Liu, Shuru; Gan, Yong

2013-03-01

Intelligent plan is a very important research in artificial intelligence, which has applied in network security. This paper proposes a new intrusion prevention model base on planning knowledge graph and discuses the system architecture and characteristics of this model. The Intrusion Prevention based on plan knowledge graph is completed by plan recognition based on planning knowledge graph, and the Intrusion response strategies and actions are completed by the hierarchical task network (HTN) planner in this paper. Intrusion prevention system has the advantages of intelligent planning, which has the advantage of the knowledge-sharing, the response focused, learning autonomy and protective ability.

Improving Agent Based Models and Validation through Data Fusion

PubMed Central

Laskowski, Marek; Demianyk, Bryan C.P.; Friesen, Marcia R.; McLeod, Robert D.; Mukhi, Shamir N.

2011-01-01

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level. PMID:23569606

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.

Detection of electrophilic and nucleophilic chemical agents

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

McElhanon, James R.; Shepodd, Timothy J.

2014-08-12

A "real time" method for detecting chemical agents generally and particularly electrophilic and nucleophilic species by employing tunable, precursor sensor materials that mimic the physiological interaction of these agents to form highly florescent berberine-type alkaloids that can be easily and rapidly detected. These novel precursor sensor materials can be tuned for reaction with both electrophilic (chemical species, toxins) and nucleophilic (proteins and other biological molecules) species. By bonding or otherwise attaching these precursor molecules to a surface or substrate they can be used in numerous applications.

Detecting Biological Warfare Agents

PubMed Central

Song, Linan; Ahn, Soohyoun

2005-01-01

We developed a fiber-optic, microsphere-based, high-density array composed of 18 species-specific probe microsensors to identify biological warfare agents. We simultaneously identified multiple biological warfare agents in environmental samples by looking at specific probe responses after hybridization and response patterns of the multiplexed array. PMID:16318712

Gadolinium-Based Contrast Agents for MR Cancer Imaging

PubMed Central

Zhou, Zhuxian; Lu, Zheng-Rong

2013-01-01

Magnetic resonance imaging (MRI) is a clinical imaging modality effective for anatomical and functional imaging of diseased soft tissues, including solid tumors. MRI contrast agents have been routinely used for detecting tumor at an early stage. Gadolinium based contrast agents are the most commonly used contrast agents in clinical MRI. There have been significant efforts to design and develop novel Gd(III) contrast agents with high relaxivity, low toxicity and specific tumor binding. The relaxivity of the Gd(III) contrast agents can be increased by proper chemical modification. The toxicity of Gd(III) contrast agents can be reduced by increasing the agents’ thermodynamic and kinetic stability, as well as optimizing their pharmacokinetic properties. The increasing knowledge in the field of cancer genomics and biology provides an opportunity for designing tumor-specific contrast agents. Various new Gd(III) chelates have been designed and evaluated in animal models for more effective cancer MRI. This review outlines the design and development, physicochemical properties, and in vivo properties of several classes of Gd(III)-based MR contrast agents for tumor imaging. PMID:23047730

Mass spectrometry for the detection of bioterrorism agents: from environmental to clinical applications.

PubMed

Duriez, Elodie; Armengaud, Jean; Fenaille, François; Ezan, Eric

2016-03-01

In the current context of international conflicts and localized terrorist actions, there is unfortunately a permanent threat of attacks with unconventional warfare agents. Among these, biological agents such as toxins, microorganisms, and viruses deserve particular attention owing to their ease of production and dissemination. Mass spectrometry (MS)-based techniques for the detection and quantification of biological agents have a decisive role to play for countermeasures in a scenario of biological attacks. The application of MS to every field of both organic and macromolecular species has in recent years been revolutionized by the development of soft ionization techniques (MALDI and ESI), and by the continuous development of MS technologies (high resolution, accurate mass HR/AM instruments, novel analyzers, hybrid configurations). New possibilities have emerged for exquisite specific and sensitive detection of biological warfare agents. MS-based strategies for clinical application can now address a wide range of analytical questions mainly including issues related to the complexity of biological samples and their available volume. Multiplexed toxin detection, discovery of new markers through omics approaches, and identification of untargeted microbiological or of novel molecular targets are examples of applications. In this paper, we will present these technological advances along with the novel perspectives offered by omics approaches to clinical detection and follow-up. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Fiber-optic microsphere-based arrays for multiplexed biological warfare agent detection.

PubMed

Song, Linan; Ahn, Soohyoun; Walt, David R

2006-02-15

We report a multiplexed high-density DNA array capable of rapid, sensitive, and reliable identification of potential biological warfare agents. An optical fiber bundle containing 6000 individual 3.1-mum-diameter fibers was chemically etched to yield microwells and used as the substrate for the array. Eighteen different 50-mer single-stranded DNA probes were covalently attached to 3.1-mum microspheres. Probe sequences were designed for Bacillus anthracis, Yersinia pestis, Francisella tularensis, Brucella melitensis, Clostridium botulinum, Vaccinia virus, and one biological warfare agent (BWA) simulant, Bacillus thuringiensis kurstaki. The microspheres were distributed into the microwells to form a randomized multiplexed high-density DNA array. A detection limit of 10 fM in a 50-microL sample volume was achieved within 30 min of hybridization for B. anthracis, Y. pestis, Vaccinia virus, and B. thuringiensis kurstaki. We used both specific responses of probes upon hybridization to complementary targets as well as response patterns of the multiplexed array to identify BWAs with high accuracy. We demonstrated the application of this multiplexed high-density DNA array for parallel identification of target BWAs in spiked sewage samples after PCR amplification. The array's miniaturized feature size, fabrication flexibility, reusability, and high reproducibility may enable this array platform to be integrated into a highly sensitive, specific, and reliable portable instrument for in situ BWA detection.

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.

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.

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.

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

Fe3O4-based PLGA nanoparticles as MR contrast agents for the detection of thrombosis

PubMed Central

Liu, Jia; Xu, Jie; Zhou, Jun; Zhang, Yu; Guo, Dajing; Wang, Zhigang

2017-01-01

Thrombotic disease is a great threat to human health, and early detection is particularly important. Magnetic resonance (MR) molecular imaging provides noninvasive imaging with the potential for early disease diagnosis. In this study, we developed Fe3O4-based poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) surface-modified with a cyclic Arg-Gly-Asp (cRGD) peptide as an MR contrast agent for the detection of thrombosis. The physical and chemical characteristics, biological toxicity, ability to target thrombi, and biodistribution of the NPs were studied. The Fe3O4-PLGA-cRGD NPs were constructed successfully, and hematologic and pathologic assays indicated no in vivo toxicity of the NPs. In a rat model of FeCl3-induced abdominal aorta thrombosis, the NPs readily and selectively accumulated on the surface of the thrombosis and under vascular endothelial cells ex vivo and in vivo. In the in vivo experiment, the biodistribution of the NPs suggested that the NPs might be internalized by the macrophages of the reticuloendothelial system in the liver and the spleen. The T2 signal decreased at the mural thrombus 10 min after injection and then gradually increased until 50 min. These results suggest that the NPs are suitable for in vivo molecular imaging of thrombosis under high shear stress conditions and represent a very promising MR contrast agent for sensitive and specific detection of thrombosis. PMID:28223802

Proximal detection of chemical warfare agents using PMIRRAS

NASA Astrophysics Data System (ADS)

Petryk, Michael W. P.; Marenco, Armando J.

2010-04-01

Non-contact chemical warfare agent detection has been demonstrated on military painted surfaces using polarization modulation infrared reflection-absorption spectroscopy (PMIRRAS). Notably, VX has been detected on chemical agent resistance coating (CARC) paint at a distance of approximately 10 cm. PMIRRAS does not rely on the presence of chemical vapors and is not affected by many common battlefield interferants such as aerosolized dust, water and diesel vapors, etc., making it highly suitable for use in operational environments.

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.

On deception detection in multi-agent systems and deception intent

NASA Astrophysics Data System (ADS)

Santos, Eugene, Jr.; Li, Deqing; Yuan, Xiuqing

2008-04-01

Deception detection plays an important role in the military decision-making process, but detecting deception is a challenging task. The deception planning process involves a number of human factors. It is intent-driven where intentions are usually hidden or not easily observable. As a result, in order to detect deception, any adversary model must have the capability to capture the adversary's intent. This paper discusses deception detection in multi-agent systems and in adversary modeling. We examined psychological and cognitive science research on deception and implemented various theories of deception within our approach. First, in multi-agent expert systems, one detection method uses correlations between agents to predict reasonable opinions/responses of other agents (Santos & Johnson, 2004). We further explore this idea and present studies that show the impact of different factors on detection success rate. Second, from adversary modeling, our detection method focuses on inferring adversary intent. By combining deception "branches" with intent inference models, we can estimate an adversary's deceptive activities and at the same time enhance intent inference. Two major kinds of deceptions are developed in this approach in different fashions. Simulative deception attempts to find inconsistency in observables, while dissimulative deception emphasizes the inference of enemy intentions.

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

NASA Technical Reports Server (NTRS)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Acceptance- and imagery-based strategies can reduce chocolate cravings: A test of the elaborated-intrusion theory of desire.

PubMed

Schumacher, Sophie; Kemps, Eva; Tiggemann, Marika

2017-06-01

The elaborated-intrusion theory of desire proposes that craving is a two-stage process whereby initial intrusions about a desired target are subsequently elaborated with mental imagery. The present study tested whether the craving reduction strategies of cognitive defusion and guided imagery could differentially target the intrusion and elaboration stages, respectively, and thus differentially impact the craving process. Participants were randomly assigned to a cognitive defusion, a guided imagery or a mind-wandering control condition. Pre- and post-intervention chocolate-related thoughts, intrusiveness of thoughts, vividness of imagery, craving intensity, and chocolate consumption were compared. Experiment 1 recruited a general sample of young women (n = 94), whereas Experiment 2 recruited a sample of chocolate cravers who wanted to reduce their chocolate consumption (n = 97). Across both experiments, cognitive defusion lowered intrusiveness of thoughts, vividness of imagery and craving intensity. Guided imagery reduced chocolate-related thoughts, intrusiveness, vividness and craving intensity for chocolate cravers (Experiment 2), but not for the general sample (Experiment 1). There were no group differences in chocolate consumption in either experiment. Results add to existing evidence supporting the elaborated-intrusion theory of desire in the food domain, and suggest that acceptance- and imagery-based techniques have potential for use in combatting problematic cravings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Considerations in detecting CDC select agents under field conditions

NASA Astrophysics Data System (ADS)

Spinelli, Charles; Soelberg, Scott; Swanson, Nathaneal; Furlong, Clement; Baker, Paul

2008-04-01

Surface Plasmon Resonance (SPR) has become a widely accepted technique for real-time detection of interactions between receptor molecules and ligands. Antibody may serve as receptor and can be attached to the gold surface of the SPR device, while candidate analyte fluids contact the detecting antibody. Minute, but detectable, changes in refractive indices (RI) indicate that analyte has bound to the antibody. A decade ago, an inexpensive, robust, miniature and fully integrated SPR chip, called SPREETA, was developed. University of Washington (UW) researchers subsequently developed a portable, temperature-regulated instrument, called SPIRIT, to simultaneously use eight of these three-channel SPREETA chips. A SPIRIT prototype instrument was tested in the field, coupled to a remote reporting system on a surrogate unmanned aerial vehicle (UAV). Two target protein analytes were released sequentially as aerosols with low analyte concentration during each of three flights and were successfully detected and verified. Laboratory experimentation with a more advanced SPIRIT instrument demonstrated detection of very low levels of several select biological agents that might be employed by bioterrorists. Agent detection under field-like conditions is more challenging, especially as analyte concentrations are reduced and complex matricies are introduced. Two different sample preconditioning protocols have been developed for select agents in complex matrices. Use of these preconditioning techniques has allowed laboratory detection in spiked heavy mud of Francisella tularensis at 10 3 CFU/ml, Bacillus anthracis spores at 10 3 CFU/ml, Staphylococcal enterotoxin B (SEB) at 1 ng/ml, and Vaccinia virus (a smallpox simulant) at 10 5 PFU/ml. Ongoing experiments are aimed at simultaneous detection of multiple agents in spiked heavy mud, using a multiplex preconditioning protocol.

Enhanced Detection of Vibrio Cholerae in Oyster Homogenate Based on Centrifugal Removal of Inhibitory Agents

NASA Technical Reports Server (NTRS)

Alexander, Donita; DePaola, Angelo; Young, Ronald B.

1998-01-01

The disease cholera, caused by Vibrio cholerae, has been associated with consumption of contaminated seafood, including raw oysters. Detection of V. cholerae in foods typically involves blending the oysters, diluting the homogenate in alkaline peptone water (APW), overnight enrichment, and isolation on selective agar. Unfortunately, the oyster homogenate must be diluted to large volumes because lower dilutions inhibit the growth of V. cholerae. The goals of this study were to develop an alternative to large dilutions and to evaluate the basis for the inhibition observed in lower dilutions of oyster homogenates. Centrifugation of oyster homogenates at 10,000 x g for 15 min, followed by enrichment of the resulting pellet in APW, was found to eliminate the inhibition of V. cholerae growth. Inhibition appears not to be due to competing microflora but to a component(s) released when V. cholerae grows in the presence of oyster homogenate. The inhibitory component(s) kills the V. cholerae after the cell concentration reaches > 10(exp 8) cells/mL, rather than initially preventing their growth. The pH also declines from 8.0 to 5.5 during this period; however, the pH decline by itself appears not to cause V. cholerae death. Seven strains of V. cholerae (01 and non-01) and two strains of V. vulnificus were susceptible to the inhibitory agent(s). However, other Vibrio and non-Vibrio species tested were not inhibited by the oyster homogenates. Based on digestion of oyster homogenates with pronase, trypsin and lipase, the inhibitory reaction involves a protein(s). In a preliminary trial with oyster homogenate seeded with 1 cfu/g of V. cholerae, the modified centrifugation technique detected a slightly higher percentage of samples at a 1:10 dilution than the standard FDA Bacteriological Analytical Method (BAM) detected in uncentrifuged oyster homogenate at a 1:100 dilution. V. cholerae in seeded samples could also be detected more frequently by the modified centrifugation method

Method for tracking the location of mobile agents using stand-off detection technique

DOEpatents

Schmitt, Randal L [Tijeras, NM; Bender, Susan Fae Ann [Tijeras, NM; Rodacy, Philip J [Albuquerque, NM; Hargis, Jr., Philip J.; Johnson, Mark S [Albuquerque, NM

2006-12-26

A method for tracking the movement and position of mobile agents using light detection and ranging (LIDAR) as a stand-off optical detection technique. The positions of the agents are tracked by analyzing the time-history of a series of optical measurements made over the field of view of the optical system. This provides a (time+3-D) or (time+2-D) mapping of the location of the mobile agents. Repeated pulses of a laser beam impinge on a mobile agent, such as a bee, and are backscattered from the agent into a LIDAR detection system. Alternatively, the incident laser pulses excite fluorescence or phosphorescence from the agent, which is detected using a LIDAR system. Analysis of the spatial location of signals from the agents produced by repeated pulses generates a multidimensional map of agent location.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Recent Advances in the Development of Chromophore-Based Chemosensors for Nerve Agents and Phosgene.

PubMed

Chen, Liyan; Wu, Di; Yoon, Juyoung

2018-01-26

The extreme toxicity and ready accessibility of nerve agents and phosgene has caused an increase in the demand to develop effective systems for the detection of these substances. Among the traditional platforms utilized for this purpose, chemosensors including surface acoustic wave (SAW) sensors, enzymes, carbon nanotubes, nanoparticles, and chromophore based sensors have attracted increasing attention. In this review, we describe in a comprehensive manner recent progress that has been made on the development of chromophore-based chemosensors for detecting nerve agents (mimic) and phosgene. This review comprises two sections focusing on studies of the development of chemosensors for nerve agents (mimic) and phosgene. In each of the sections, the discussion follows a format which concentrates on different reaction sites/mechanisms involved in the sensing processes. Finally, chemosensors uncovered in these efforts are compared with those based on other sensing methods and challenges facing the design of more effective chemosensors for the detection of nerve agents (mimic) and phosgene are discussed.

Detection of Electrophilic and Nucleophilic Chemical Agents

DOEpatents

McElhanon, James R.; Shepodd, Timothy J.

2008-11-11

A "real time" method for detecting electrophilic and nucleophilic species generally by employing tunable, precursor sensor materials that mimic the physiological interaction of these agents to form highly florescent berberine-type alkaloids that can be easily and rapidly detected. These novel precursor sensor materials can be tuned for reaction with both electrophilic (chemical species, toxins) and nucleophilic (proteins and other biological molecules) species.

History and perspectives of bioanalytical methods for chemical warfare agent detection.

PubMed

Black, Robin M

2010-05-15

This paper provides a short historical overview of the development of bioanalytical methods for chemical warfare (CW) agents and their biological markers of exposure, with a more detailed overview of methods for organophosphorus nerve agents. Bioanalytical methods for unchanged CW agents are used primarily for toxicokinetic/toxicodynamic studies. An important aspect of nerve agent toxicokinetics is the different biological activity and detoxification pathways for enantiomers. CW agents have a relatively short lifetime in the human body, and are hydrolysed, metabolised, or adducted to nucleophilic sites on macromolecules such as proteins and DNA. These provide biological markers of exposure. In the past two decades, metabolites, protein adducts of nerve agents, vesicants and phosgene, and DNA adducts of sulfur and nitrogen mustards, have been identified and characterized. Sensitive analytical methods have been developed for their detection, based mainly on mass spectrometry combined with gas or liquid chromatography. Biological markers for sarin, VX and sulfur mustard have been validated in cases of accidental and deliberate human exposures. The concern for terrorist use of CW agents has stimulated the development of higher throughput analytical methods in support of homeland security. Copyright (c) 2010. Published by Elsevier B.V.

Petroleum Vapor Intrusion

EPA Pesticide Factsheets

One type of vapor intrusion is PVI, in which vapors from petroleum hydrocarbons such as gasoline, diesel, or jet fuel enter a building. Intrusion of contaminant vapors into indoor spaces is of concern.

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.

Chemiresistor Devices for Chemical Warfare Agent Detection Based on Polymer Wrapped Single-Walled Carbon Nanotubes

PubMed Central

Fennell, John F.; Hamaguchi, Hitoshi; Yoon, Bora; Swager, Timothy M.

2017-01-01

Chemical warfare agents (CWA) continue to present a threat to civilian populations and military personnel in operational areas all over the world. Reliable measurements of CWAs are critical to contamination detection, avoidance, and remediation. The current deployed systems in United States and foreign militaries, as well as those in the private sector offer accurate detection of CWAs, but are still limited by size, portability and fabrication cost. Herein, we report a chemiresistive CWA sensor using single-walled carbon nanotubes (SWCNTs) wrapped with poly(3,4-ethylenedioxythiophene) (PEDOT) derivatives. We demonstrate that a pendant hexafluoroisopropanol group on the polymer that enhances sensitivity to a nerve agent mimic, dimethyl methylphosphonate, in both nitrogen and air environments to concentrations as low as 5 ppm and 11 ppm, respectively. Additionally, these PEDOT/SWCNT derivative sensor systems experience negligible device performance over the course of two weeks under ambient conditions. PMID:28452929

Chemiresistor Devices for Chemical Warfare Agent Detection Based on Polymer Wrapped Single-Walled Carbon Nanotubes.

PubMed

Fennell, John F; Hamaguchi, Hitoshi; Yoon, Bora; Swager, Timothy M

2017-04-28

Chemical warfare agents (CWA) continue to present a threat to civilian populations and military personnel in operational areas all over the world. Reliable measurements of CWAs are critical to contamination detection, avoidance, and remediation. The current deployed systems in United States and foreign militaries, as well as those in the private sector offer accurate detection of CWAs, but are still limited by size, portability and fabrication cost. Herein, we report a chemiresistive CWA sensor using single-walled carbon nanotubes (SWCNTs) wrapped with poly(3,4-ethylenedioxythiophene) (PEDOT) derivatives. We demonstrate that a pendant hexafluoroisopropanol group on the polymer that enhances sensitivity to a nerve agent mimic, dimethyl methylphosphonate, in both nitrogen and air environments to concentrations as low as 5 ppm and 11 ppm, respectively. Additionally, these PEDOT/SWCNT derivative sensor systems experience negligible device performance over the course of two weeks under ambient conditions.

Three Dimensional Vapor Intrusion Modeling: Model Validation and Uncertainty Analysis

NASA Astrophysics Data System (ADS)

Akbariyeh, S.; Patterson, B.; Rakoczy, A.; Li, Y.

2013-12-01

Volatile organic chemicals (VOCs), such as chlorinated solvents and petroleum hydrocarbons, are prevalent groundwater contaminants due to their improper disposal and accidental spillage. In addition to contaminating groundwater, VOCs may partition into the overlying vadose zone and enter buildings through gaps and cracks in foundation slabs or basement walls, a process termed vapor intrusion. Vapor intrusion of VOCs has been recognized as a detrimental source for human exposures to potential carcinogenic or toxic compounds. The simulation of vapor intrusion from a subsurface source has been the focus of many studies to better understand the process and guide field investigation. While multiple analytical and numerical models were developed to simulate the vapor intrusion process, detailed validation of these models against well controlled experiments is still lacking, due to the complexity and uncertainties associated with site characterization and soil gas flux and indoor air concentration measurement. In this work, we present an effort to validate a three-dimensional vapor intrusion model based on a well-controlled experimental quantification of the vapor intrusion pathways into a slab-on-ground building under varying environmental conditions. Finally, a probabilistic approach based on Monte Carlo simulations is implemented to determine the probability distribution of indoor air concentration based on the most uncertain input parameters.

High-sensitivity, high-selectivity detection of chemical warfare agents

NASA Astrophysics Data System (ADS)

Pushkarsky, Michael B.; Webber, Michael E.; Macdonald, Tyson; Patel, C. Kumar N.

2006-01-01

We report high-sensitivity detection of chemical warfare agents (nerve gases) with very low probability of false positives (PFP). We demonstrate a detection threshold of 1.2ppb (7.7μg/m3 equivalent of Sarin) with a PFP of <1:106 in the presence of many interfering gases present in an urban environment through the detection of diisopropyl methylphosphonate, an accepted relatively harmless surrogate for the nerve agents. For the current measurement time of ˜60s, a PFP of 1:106 corresponds to one false alarm approximately every 23months. The demonstrated performance satisfies most current homeland and military security requirements.

Using Nanotechnology to Detect Nerve Agents

DTIC Science & Technology

2011-01-01

56 | Air & Space Power Journal Air Force Institute of Technology Using Nanotechnology to Detect Nerve Agents Lt Col Mark N. Goltz , PhD, USAF...Retired Dr. Dong Shik Kim Maj LeeAnn Racz, PhD, USAF* *Lieutenant Colonel Goltz and Major Racz are faculty members in the Department of Systems and

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

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.

Nanoparticle-Based Electrochemical Immunosensor for the Detection of Phosphorylated Acetylcholinesterase: An Exposure Biomarker of Organophosphate Pesticides and Nerve AgentsOrganophosphate Pesticides and Nerve Agents

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

Liu, Guodong; Wang, Jun; Barry, Richard C.

A nanoparticle-based electrochemical immunosensor has been developed for the detection of phosphorylated acetylcholinesterase (AChE) adducts, which is a potential exposure biomarker for organophosphate pesticides (OP) and chemical warfare nerve agent exposures. Zirconia nanoparticles (ZrO2 NPs) were used as selective sorbents to capture the phosphorylated AChE adduct, and quantum dots (ZnS@CdS, QDs) were used as tags to label monoclonal anti-AChE antibody to track the immunorecognition events. The sandwich-like immunoreactions were performed among the ZrO2 NPs, which were pre-coated on a screen printed electrode (SPE) by electrodeposition, phosphorylated AChE and QD-anti-AChE. The captured QD tags were determined on the SPE by electrochemicalmore » stripping analysis of its metallic component (cadmium) after an acid-dissolution step. Paraoxon was used as a model OP insecticide to prepare the phosphorylated AChE adduct to demonstrate the proof of principle for this sensor technology. The paraoxon-AChE adduct was characterized by Fourier Transform Infrared Spectrum, and the binding affinity of anti-AChE to the paraoxon-AChE was validated with an enzyme-linked immunosorbent assay. The parameters (e.g., amount of ZrO2 NP, QD-anti-AChE concentration,) that govern the electrochemical response of immunosensors were optimized. The voltammetric response of the immunosensor is highly linear over the range of 10 pM to 4 nM paraoxon-AChE, and the limit of detection is estimated to be 8 pM. This new nanoparticle-based electrochemical immunosensor thus provides a sensitive and quantitative tool for biomonitoring exposure to OP pesticides and nerve agents.« less

An enhanced performance through agent-based secure approach for mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Bisen, Dhananjay; Sharma, Sanjeev

2018-01-01

This paper proposes an agent-based secure enhanced performance approach (AB-SEP) for mobile ad hoc network. In this approach, agent nodes are selected through optimal node reliability as a factor. This factor is calculated on the basis of node performance features such as degree difference, normalised distance value, energy level, mobility and optimal hello interval of node. After selection of agent nodes, a procedure of malicious behaviour detection is performed using fuzzy-based secure architecture (FBSA). To evaluate the performance of the proposed approach, comparative analysis is done with conventional schemes using performance parameters such as packet delivery ratio, throughput, total packet forwarding, network overhead, end-to-end delay and percentage of malicious detection.

Competitive FRET-aptamer-based detection of methylphosphonic acid, a common nerve agent metabolite.

PubMed

Bruno, John G; Carrillo, Maria P; Phillips, Taylor; Vail, Neal K; Hanson, Douglas

2008-09-01

Competitive fluorescence resonance energy transfer (FRET)-aptamer-based assay formats are described for one-step detection of methylphosphonic acid (MPA; a metabolite of several organophosphorus (OP) nerve agents). AminoMPA was attached to tosyl-magnetic beads and used for DNA aptamer selection from which one dominant aptamer sequence emerged. Two different FRET approaches were attempted. In one approach, the complementary DNA sequence was used as a template for labeling the aptamer with Alexa Fluor 546 (AF 546)-14-dUTP by asymmetric PCR. Following 3-dimensional (3-D), molecular modeling of the aptamer-MPA complex, a series of three fluoresceinated aptamers labeled at positions 50, 51, and 52 in the putative optimal binding pocket were synthesized. In both FRET formats, aminoMPA was linked to Black Hole Quencher (BHQ-1 or BHQ-2)-succinimides and allowed to bind the fluorescein or AF 546-labeled MPA aptamer. Following gel filtration to purify the labeled MPA aptamer-BHQ-aminoMPA FRET complexes, the complexes were competed against various concentrations of unlabeled MPA, MPA derivatives, and unrelated compounds in titration and cross-reactivity studies. Both approaches yielded low microgram per milliliter detection limits for MPA with generally low levels of cross-reactivity for unrelated compounds. However, the data suggest a pattern of traits that may effect the direction (lights on or off) and intensity of the FRET.

Reactive chromophores for sensitive and selective detection of chemical warfare agents and toxic industrial chemicals

NASA Astrophysics Data System (ADS)

Frye-Mason, Greg; Leuschen, Martin; Wald, Lara; Paul, Kateri; Hancock, Lawrence F.

2005-05-01

A reactive chromophore developed at MIT exhibits sensitive and selective detection of surrogates for G-class nerve agents. This reporter acts by reacting with the agent to form an intermediate that goes through an internal cyclization reaction. The reaction locks the molecule into a form that provides a strong fluorescent signal. Using a fluorescent sensor platform, Nomadics has demonstrated rapid and sensitive detection of reactive simulants such as diethyl chloro-phosphate (simulant for sarin, soman, and related agents) and diethyl cyanophosphate (simulant for tabun). Since the unreacted chromophore does not fluoresce at the excitation wavelength used for the cyclized reporter, the onset of fluo-rescence can be easily detected. This fluorescence-based detection method provides very high sensitivity and could enable rapid detection at permissible exposure levels. Tests with potential interferents show that the reporter is very selective, with responses from only a few highly toxic, electrophilic chemicals such as phosgene, thionyl chloride, and strong acids such as HF, HCl, and nitric acid. Dimethyl methyl phosphonate (DMMP), a common and inactive simu-lant for other CW detectors, is not reactive enough to generate a signal. The unique selectivity to chemical reactivity means that a highly toxic and hazardous chemical is present when the reporter responds and illustrates that this sensor can provide very low false alarm rates. Current efforts focus on demonstrating the sensitivity and range of agents and toxic industrial chemicals detected with this reporter as well as developing additional fluorescent reporters for a range of chemical reactivity classes. The goal is to produce a hand-held sensor that can sensitively detect a broad range of chemical warfare agent and toxic industrial chemical threats.

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.

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.

Assessment of Mitigation Systems on Vapor Intrusion ...

EPA Pesticide Factsheets

Vapor intrusion is the migration of subsurface vapors, including radon and volatile organic compounds (VOCs), in soil gas from the subsurface to indoor air. Vapor intrusion happens because there are pressure and concentration differentials between indoor air and soil gas. Indoor environments are often negatively pressurized with respect to outdoor air and soil gas (for example, from exhaust fans or the stack effect), and this pressure difference allows soil gas containing subsurface vapors to flow into indoor air through advection. In addition, concentration differentials cause VOCs and radon to migrate from areas of higher to lower concentrations through diffusion, which is another cause of vapor intrusion. Current practice for evaluating the vapor intrusion pathway involves a multiple line of evidence approach based on direct measurements in groundwater, external soil gas, subslab soil gas, and/or indoor air. No single line of evidence is considered definitive, and direct measurements of vapor intrusion can be costly, especially where significant spatial and temporal variability require repeated measurements at multiple locations to accurately assess the chronic risks of long-term exposure to volatile organic compounds (VOCs) like chloroform, perchloroethylene (PCE), and trichloroethylene (TCE).

Is mindfulness-based therapy an effective intervention for obsessive-intrusive thoughts: a case series.

PubMed

Wilkinson-Tough, Megan; Bocci, Laura; Thorne, Kirsty; Herlihy, Jane

2010-01-01

Despite the efficacy of cognitive-behavioural interventions in improving the experience of obsessions and compulsions, some people do not benefit from this approach. The present research uses a case series design to establish whether mindfulness-based therapy could benefit those experiencing obsessive-intrusive thoughts by targeting thought-action fusion and thought suppression. Three participants received a relaxation control intervention followed by a six-session mindfulness-based intervention which emphasized daily practice. Following therapy all participants demonstrated reductions in Yale-Brown Obsessive-Compulsive Scale scores to below clinical levels, with two participants maintaining this at follow-up. Qualitative analysis of post-therapy feedback suggested that mindfulness skills such as observation, awareness and acceptance were seen as helpful in managing thought-action fusion and suppression. Despite being limited by small participant numbers, these results suggest that mindfulness may be beneficial to some people experiencing intrusive unwanted thoughts and that further research could establish the possible efficacy of this approach in larger samples. Copyright (c) 2009 John Wiley & Sons, Ltd.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Sensor Systems for Biological Agent Attacks: Protecting Buildings and Military Bases

DTIC Science & Technology

2004-01-01

simple aerosol detectors, to those that identify an agent based on its genetic, structural, or chemical properties , to so- called "functional...Cytometry, 122 Target Binding That Changes Detectable Properties of Smart Sensor Surfaces, 124 Colorimetric Detection, 124 Fluorescence Detection, 125 One...microscopy. In addition to particles directly derived from living organisms, other particles in air may also share properties with the bioaerosols

Protection of Mobile Agents Execution Using a Modified Self-Validating Branch-Based Software Watermarking with External Sentinel

NASA Astrophysics Data System (ADS)

Tomàs-Buliart, Joan; Fernández, Marcel; Soriano, Miguel

Critical infrastructures are usually controlled by software entities. To monitor the well-function of these entities, a solution based in the use of mobile agents is proposed. Some proposals to detect modifications of mobile agents, as digital signature of code, exist but they are oriented to protect software against modification or to verify that an agent have been executed correctly. The aim of our proposal is to guarantee that the software is being executed correctly by a non trusted host. The way proposed to achieve this objective is by the improvement of the Self-Validating Branch-Based Software Watermarking by Myles et al.. The proposed modification is the incorporation of an external element called sentinel which controls branch targets. This technique applied in mobile agents can guarantee the correct operation of an agent or, at least, can detect suspicious behaviours of a malicious host during the execution of the agent instead of detecting when the execution of the agent have finished.

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

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.

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.

Copper sulfide nanodisk as photoacoustic contrast agent for ovarian tumor detection

NASA Astrophysics Data System (ADS)

Wang, Junxin; Hsu, Su-Wen; Tao, Andrea R.; Jokerst, Jesse V.

2017-03-01

Ultrasound is broadly used in the clinics yet is limited in early cancer detection because of its poor contrast between healthy and diseased tissues. Photoacoustic imaging can improve this limitation and has been extensively studied in pre-clinical models. Contrast agents can help improve the accuracy of diagnosis. We recently reported a novel copper sulfide (CuS) nanodisk with strong directionally-localized surface plasmon resonance in the near infrared region. This plasmonic resonance of nanodisks is tunable by changing the size and aspect ratio of CuS nanodisk. Here, we demonstrate this CuS nanodisk is a strong photoacoustic contrast agent. We prepared CuS nanodisks via a solvent-based synthesis followed by surface modification of poly(ethylene glycol) methyl ether thiol for in vivo applications. These CuS nanodisks can be detected at a concentration as low as 26 pM at 920 nm. Their nanosize and strong photoacoustic response make this novel CuS nanodisk a strong candidate for photoacoustic cancer imaging.

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.

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.

Functionalized gold nanoparticle supported sensory mechanisms applied in detection of chemical and biological threat agents: a review.

PubMed

Upadhyayula, Venkata K K

2012-02-17

There is a great necessity for development of novel sensory concepts supportive of smart sensing capabilities in defense and homeland security applications for detection of chemical and biological threat agents. A smart sensor is a detection device that can exhibit important features such as speed, sensitivity, selectivity, portability, and more importantly, simplicity in identifying a target analyte. Emerging nanomaterial based sensors, particularly those developed by utilizing functionalized gold nanoparticles (GNPs) as a sensing component potentially offer many desirable features needed for threat agent detection. The sensitiveness of physical properties expressed by GNPs, e.g. color, surface plasmon resonance, electrical conductivity and binding affinity are significantly enhanced when they are subjected to functionalization with an appropriate metal, organic or biomolecular functional groups. This sensitive nature of functionalized GNPs can be potentially exploited in the design of threat agent detection devices with smart sensing capabilities. In the presence of a target analyte (i.e., a chemical or biological threat agent) a change proportional to concentration of the analyte is observed, which can be measured either by colorimetric, fluorimetric, electrochemical or spectroscopic means. This article provides a review of how functionally modified gold colloids are applied in the detection of a broad range of threat agents, including radioactive substances, explosive compounds, chemical warfare agents, biotoxins, and biothreat pathogens through any of the four sensory means mentioned previously. Copyright © 2011 Elsevier B.V. All rights reserved.

Detection of ethene and other hydrocarbons in gas turbine engine exhaust using non-intrusive FTIR spectroscopy

NASA Astrophysics Data System (ADS)

Arrigone, Giovanni M.; Welch, Michael A.; Hilton, Moira; Miller, Michael N.; Wilson, Christopher W.

2003-04-01

As part of the EU funded project AEROJET2, a number of gas turbine engine tests were performed in different facilities around Europe. At Farnborough, UK a Spey engine was used to test a suite of prototype optically based instrumentation designed to measure exhaust gas emissions without using extractive probe systems. In addition to the AEROJET 2 prototype instrumentation, a Bruker Equinox 55 Fourier transform infrared (FTIR) spectrometer was used to obtain infrared spectra of the exhaust plume both in emission and absorption mode. The Bruker FTIR spectrometer was fitted with a periscope system so that different lines of sight could be monitored in the plume in a vertical plane 25 cm downstream from the nozzle exit and 20 cm upstream of the center line of sight of the AEROJET 2 prototype instrumentation. DERA (now QinetiQ) provided exhaust gas analysis data for different engine running conditions using samples extracted from the plume with an intrusive probe. The probe sampled along a horizontal plane across the centerline of the engine 45 cm downstream of the nozzle exit. The Bruker spectrometer used both InSb (indium antimonide) and MCT (mercury-cadmium-telluride) detectors to maximize the sensitivity across the IR range 600-4000 cm-1. Typically, CO2 and H2O IR signatures dominate the observed spectra of the plume. However, the engine tests showed that at low power engine conditions spectral features associated with CO around 2147 cm-1 and with hydrocarbons could be observed at around 3000 cm-1. In particular the presence of ethene (C2H2) was detected from observation of its characteristic in and out of plane vibration mode at 949 cm-1. At high engine powers the presence of NO was detected at 1900.3 cm-1. Species concentrations were calculated using a slab model for each line of sight compared against reference spectra. The engine plume was assumed to be symmetric about the centerline. On this basis, data from the extractive sampling gas analysis that had been

Efficient Agent-Based Cluster Ensembles

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Tumer, Kagan

2006-01-01

Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified clustering. Unfortunately current non-agent-based cluster combining methods do not work in a distributed environment, are not robust to corrupted clusterings and require centralized access to all original clusterings. Overcoming these issues will allow cluster ensembles to be used in fundamentally distributed and failure-prone domains such as data acquisition from satellite constellations, in addition to domains demanding confidentiality such as combining clusterings of user profiles. This paper proposes an efficient, distributed, agent-based clustering ensemble method that addresses these issues. In this approach each agent is assigned a small subset of the data and votes on which final cluster its data points should belong to. The final clustering is then evaluated by a global utility, computed in a distributed way. This clustering is also evaluated using an agent-specific utility that is shown to be easier for the agents to maximize. Results show that agents using the agent-specific utility can achieve better performance than traditional non-agent based methods and are effective even when up to 50% of the agents fail.

Measuring indigenous photosynthetic organisms to detect chemical warefare agents in water

DOEpatents

Greenbaum, Elias; Sanders, Charlene A.

2005-11-15

A method of testing water to detect the presence of a chemical or biological warfare agent is disclosed. The method is carried out by establishing control data by providing control water containing indigenous organisms but substantially free of a chemical and a biological warfare agent. Then measuring photosynthetic activity of the control water with a fluorometer to obtain control data to compare with test data to detect the presence of the chemical or agent. The test data is gathered by providing test water comprising the same indigenous organisms as contained in the control water. Further, the test water is suspected of containing the chemical or agent to be tested for. Photosynthetic activity is also measured by fluorescence induction in the test water using a fluorometer.

Beat frequency ultrasonic microsphere contrast agent detection system

NASA Technical Reports Server (NTRS)

Pretlow, Robert A., III (Inventor); Yost, William T. (Inventor); Cantrell, John H., Jr. (Inventor)

1995-01-01

A system for and method of detecting and measuring concentrations of an ultrasonically-reflective microsphere contrast agent involving detecting non-linear sum and difference beat frequencies produced by the microspheres when two impinging signals with non-identical frequencies are combined by mixing. These beat frequencies can be used for a variety of applications such as detecting the presence of and measuring the flow rates of biological fluids and industrial liquids, including determining the concentration level of microspheres in the myocardium.

Beat frequency ultrasonic microsphere contrast agent detection system

NASA Technical Reports Server (NTRS)

Pretlow, III, Robert A. (Inventor); Yost, William T. (Inventor); Cantrell, Jr., John H. (Inventor)

1997-01-01

A system for and method of detecting and measuring concentrations of an ultrasonically-reflective microsphere contrast agent involving detecting non-linear sum and difference beat frequencies produced by the microspheres when two impinging signals with non-identical frequencies are combined by mixing. These beat frequencies can be used for a variety of applications such as detecting the presence of and measuring the flow rates of biological fluids and industrial liquids, including determining the concentration level of microspheres in the myocardium.

Episodic intrusion, internal differentiation, and hydrothermal alteration of the miocene tatoosh intrusive suite south of Mount Rainier, Washington

USGS Publications Warehouse

du Bray, E.A.; Bacon, C.R.; John, D.A.; Wooden, J.L.; Mazdab, F.K.

2011-01-01

The Miocene Tatoosh intrusive suite south of Mount Rainier is composed of three broadly granodioritic plutons that are manifestations of ancestral Cascades arc magmatism. Tatoosh intrusive suite plutons have individually diagnostic characteristics, including texture, mineralogy, and geochemistry, and apparently lack internal contacts. New ion-microprobe U-Pb zircon ages indicate crystallization of the Stevens pluton ca. 19.2 Ma, Reflection-Pyramid pluton ca. 18.5 Ma, and Nisqually pluton ca. 17.5 Ma. The Stevens pluton includes rare, statistically distinct ca. 20.1 Ma zircon antecrysts. Wide-ranging zircon rare earth element (REE), Hf, U, and Th concentrations suggest late crystallization from variably evolved residual liquids. Zircon Eu/Eu*-Hf covariation is distinct for each of the Reflection-Pyramid, Nisqually, and Stevens plutons. Although most Tatoosh intrusive suite rocks have been affected by weak hydrothermal alteration, and sparse mineralized veins cut some of these rocks, significant base or precious metal mineralization is absent. At the time of shallow emplacement, each of these magma bodies was largely homogeneous in bulk composition and petrographic features, but, prior to final solidification, each of the Tatoosh intrusive suite plutons developed internal compositional variation. Geochemical and petrographic trends within each pluton are most consistent with differential loss of residual melt, possibly represented by late aplite dikes or erupted as rhyolite, from crystal-rich magma. Crystal-rich magma that formed each pluton evidently accumulated in reservoirs below the present level of exposure and then intruded to a shallow depth. Assembled by episodic intrusion, the Tatoosh intrusive suite may be representative of midsized composite plutonic complexes beneath arc volcanoes. ?? 2011 Geological Society of America.

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.

Detection of biological warfare agents using ultra violet-laser induced fluorescence LIDAR

NASA Astrophysics Data System (ADS)

Joshi, Deepti; Kumar, Deepak; Maini, Anil K.; Sharma, Ramesh C.

This review has been written to highlight the threat of biological warfare agents, their types and detection. Bacterial biological agent Bacillus anthracis (bacteria causing the disease anthrax) which is most likely to be employed in biological warfare is being discussed in detail. Standoff detection of biological warfare agents in aerosol form using Ultra violet-Laser Induced Fluorescence (UV-LIF) spectroscopy method has been studied. Range-resolved detection and identification of biological aerosols by both nano-second and non-linear femto-second LIDAR is also discussed. Calculated received fluorescence signal for a cloud of typical biological agent Bacillus globigii (Simulants of B. anthracis) at a location of ˜5.0 km at different concentrations in presence of solar background radiation has been described. Overview of current research efforts in internationally available working UV-LIF LIDAR systems are also mentioned briefly.

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

Hand-held analyser based on microchip electrophoresis with contactless conductivity detection for measurement of chemical warfare agent degradation products

NASA Astrophysics Data System (ADS)

Duran, Karolina-Petkovic; Zhu, Yonggang; Chen, Chuanpin; Swallow, Anthony; Stewart, Robert; Hoobin, Pam; Leech, Patrick; Ovenden, Simon

2008-12-01

This paper reports on the development of a hand-held device for on-site detection of organophosphonate nerve agent degradation products. This field-deployable analyzer relies on efficient microchip electrophoresis separation of alkyl methylphosphonic acids and their sensitive contactless conductivity detection. Miniaturized, low-powered design is coupled with promising analytical performance for separating the breakdown products of chemical warfare agents such as Soman, Sarin and VX . The detector has a detection limit of about 10 μg/mL and has a good linear response in the range 10-300 μg/mL concentration range. Applicability to environmental samples is demonstrated .The new hand-held analyzer offers great promise for converting conventional ion chromatography or capillary electrophoresis sophisticated systems into a portable forensic laboratory for faster, simpler and more reliable on-site screening.

Detection of biological warfare agents using ultra violet-laser induced fluorescence LIDAR.

PubMed

Joshi, Deepti; Kumar, Deepak; Maini, Anil K; Sharma, Ramesh C

2013-08-01

This review has been written to highlight the threat of biological warfare agents, their types and detection. Bacterial biological agent Bacillus anthracis (bacteria causing the disease anthrax) which is most likely to be employed in biological warfare is being discussed in detail. Standoff detection of biological warfare agents in aerosol form using Ultra violet-Laser Induced Fluorescence (UV-LIF) spectroscopy method has been studied. Range-resolved detection and identification of biological aerosols by both nano-second and non-linear femto-second LIDAR is also discussed. Calculated received fluorescence signal for a cloud of typical biological agent Bacillus globigii (Simulants of B. anthracis) at a location of ~5.0 km at different concentrations in presence of solar background radiation has been described. Overview of current research efforts in internationally available working UV-LIF LIDAR systems are also mentioned briefly. Copyright © 2013 Elsevier B.V. All rights reserved.

The importance of context: evidence that contextual representations increase intrusive memories.

PubMed

Pearson, David G; Ross, Fiona D C; Webster, Victoria L

2012-03-01

Intrusive memories appear to enter consciousness via involuntary rather than deliberate recollection. Some clinical accounts of PTSD seek to explain this phenomenon by making a clear distinction between the encoding of sensory-based and contextual representations. Contextual representations have been claimed to actively reduce intrusions by anchoring encoded perceptual data for an event in memory. The current analogue trauma study examined this hypothesis by manipulating contextual information independently from encoded sensory-perceptual information. Participants' viewed images selected from the International Affective Picture System that depicted scenes of violence and bodily injury. Images were viewed either under neutral conditions or paired with contextual information. Two experiments revealed a significant increase in memory intrusions for images paired with contextual information in comparison to the same images viewed under neutral conditions. In contrast to the observed increase in intrusion frequency there was no effect of contextual representations on voluntary memory for the images. The vividness and emotionality of memory intrusions were also unaffected. The analogue trauma paradigm may fail to replicate the effect of extreme stress on encoding postulated to occur during PTSD. These findings question the assertion that intrusive memories develop from a lack of integration between sensory-based and contextual representations in memory. Instead it is argued contextual representations play a causal role in increasing the frequency of intrusions by increasing the sensitivity of memory to involuntary retrieval by associated internal and external cues. Copyright © 2011 Elsevier Ltd. All rights reserved.

Characterization of image heterogeneity using 2D Minkowski functionals increases the sensitivity of detection of a targeted MRI contrast agent.

PubMed

Canuto, Holly C; McLachlan, Charles; Kettunen, Mikko I; Velic, Marko; Krishnan, Anant S; Neves, Andre' A; de Backer, Maaike; Hu, D-E; Hobson, Michael P; Brindle, Kevin M

2009-05-01

A targeted Gd(3+)-based contrast agent has been developed that detects tumor cell death by binding to the phosphatidylserine (PS) exposed on the plasma membrane of dying cells. Although this agent has been used to detect tumor cell death in vivo, the differences in signal intensity between treated and untreated tumors was relatively small. As cell death is often spatially heterogeneous within tumors, we investigated whether an image analysis technique that parameterizes heterogeneity could be used to increase the sensitivity of detection of this targeted contrast agent. Two-dimensional (2D) Minkowski functionals (MFs) provided an automated and reliable method for parameterization of image heterogeneity, which does not require prior assumptions about the number of regions or features in the image, and were shown to increase the sensitivity of detection of the contrast agent as compared to simple signal intensity analysis. (c) 2009 Wiley-Liss, Inc.

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.

Building Intrusion Detection with a Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Wälchli, Markus; Braun, Torsten

This paper addresses the detection and reporting of abnormal building access with a wireless sensor network. A common office room, offering space for two working persons, has been monitored with ten sensor nodes and a base station. The task of the system is to report suspicious office occupation such as office searching by thieves. On the other hand, normal office occupation should not throw alarms. In order to save energy for communication, the system provides all nodes with some adaptive short-term memory. Thus, a set of sensor activation patterns can be temporarily learned. The local memory is implemented as an Adaptive Resonance Theory (ART) neural network. Unknown event patterns detected on sensor node level are reported to the base station, where the system-wide anomaly detection is performed. The anomaly detector is lightweight and completely self-learning. The system can be run autonomously or it could be used as a triggering system to turn on an additional high-resolution system on demand. Our building monitoring system has proven to work reliably in different evaluated scenarios. Communication costs of up to 90% could be saved compared to a threshold-based approach without local memory.

Igneous intrusion models for floor fracturing in lunar craters

NASA Technical Reports Server (NTRS)

Wichman, R. W.; Schultz, P. H.

1991-01-01

Lunar floor-fractured craters are primarily located near the maria and frequently contain ponded mare units and dark mantling deposits. Fracturing is confined to the crater interior, often producing a moat-like feature near the floor edge, and crater depth is commonly reduced by uplift of the crater floor. Although viscous relaxation of crater topography can produce such uplift, the close association of modification with surface volcanism supports a model linking floor fracture to crater-centered igneous intrusions. The consequences of two intrusion models for the lunar interior are quantitatively explored. The first model is based on terrestrial laccoliths and describes a shallow intrusion beneath the crater. The second model is based on cone sheet complexes where surface deformation results from a deeper magma chamber. Both models, their fit to observed crater modifications and possible implications for local volcanism are described.

Micromotor-based on-off fluorescence detection of sarin and soman simulants.

PubMed

Singh, Virendra V; Kaufmann, Kevin; Orozco, Jahir; Li, Jinxing; Galarnyk, Michael; Arya, Gaurav; Wang, Joseph

2015-06-30

Self-propelled micromotor-based fluorescent "On-Off" detection of nerve agents is described. The motion-based assay utilizes Si/Pt Janus micromotors coated with fluoresceinamine toward real-time "on-the-fly" field detection of sarin and soman simulants.

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.

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.

10 CFR 63.322 - Human intrusion scenario.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 2 2010-01-01 2010-01-01 false Human intrusion scenario. 63.322 Section 63.322 Energy... REPOSITORY AT YUCCA MOUNTAIN, NEVADA Postclosure Public Health and Environmental Standards Human Intrusion Standard § 63.322 Human intrusion scenario. For the purposes of the analysis of human intrusion, DOE must...

Detection of the agents of human ehrlichioses in ixodid ticks from California.

PubMed

Kramer, V L; Randolph, M P; Hui, L T; Irwin, W E; Gutierrez, A G; Vugia, D J

1999-01-01

A study was conducted in northern California to estimate the prevalence and distribution in ixodid ticks of the rickettsial agents of human monocytic (HME) and human granulocytic (HGE) ehrlichioses. More than 650 ixodid ticks were collected from 17 sites in six California counties over a 15-month period. Ehrlichia chaffeensis, the causative agent of HME, was detected by a nested polymerase chain reaction (PCR) in Ixodes pacificus (minimum infection rate [MIR] = 13.3%) and Dermacentor variabilis (infection rate=20.0%) from a municipal park in Santa Cruz County. The HGE agent was detected by nested PCR in I. pacificus adults from a heavily used recreational area in Alameda County (MIR = 4.7%) and a semirural community in Sonoma County (MIR = 6.7%). Evidence of infection with Ehrlichia spp. was not detected in D. occidentalis adults or I. pacificus nymphs. This study represents the first detection of E. chaffeensis in California ticks and the first report of infection in Ixodes spp. The competency of I. pacificus to be coinfected with and to transmit multiple disease agents, including those of human ehrlichioses and Lyme disease, has yet to be determined.

Detection of human pathogenic Ehrlichia muris-like agent in Peromyscus leucopus.

PubMed

Castillo, Caroline G; Eremeeva, Marina E; Paskewitz, Susan M; Sloan, Lynne M; Lee, Xia; Irwin, William E; Tonsberg, Stefan; Pritt, Bobbi S

2015-03-01

An Ehrlichia muris-like (EML) bacterium was recently detected in humans and Ixodes scapularis ticks in Minnesota and Wisconsin. The reservoir for this agent is unknown. To investigate the occurrence of the EML agent, groEL PCR testing and sequencing was performed on blood from small mammals and white-tailed deer that were collected in areas where human and tick infections were previously demonstrated. DNA of the EML agent was detected in two Peromyscus leucopus of 146 small mammals (1.4%); while 181 O. virginianus tested negative. This report provides the first evidence that DNA from the EML agent is found in P. leucopus, the same animal that is a reservoir for Anaplasma phagocytophilum in this region. The role of white-tailed deer remains inconclusive. Further sampling is warranted to understand the spatial and temporal distribution, transmission and maintenance of this pathogen. Copyright © 2014 Elsevier GmbH. All rights reserved.

CATS-based Agents That Err

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes preliminary research on intelligent agents that make errors. Such agents are crucial to the development of novel agent-based techniques for assessing system safety. The agents extend an agent architecture derived from the Crew Activity Tracking System that has been used as the basis for air traffic controller agents. The report first reviews several error taxonomies. Next, it presents an overview of the air traffic controller agents, then details several mechanisms for causing the agents to err in realistic ways. The report presents a performance assessment of the error-generating agents, and identifies directions for further research. The research was supported by the System-Wide Accident Prevention element of the FAA/NASA Aviation Safety Program.

Hand-Held Devices Detect Explosives and Chemical Agents

NASA Technical Reports Server (NTRS)

2010-01-01

Ion Applications Inc., of West Palm Beach, Florida, partnered with Ames Research Center through Small Business Innovation Research (SBIR) agreements to develop a miniature version ion mobility spectrometer (IMS). While NASA was interested in the instrument for detecting chemicals during exploration of distant planets, moons, and comets, the company has incorporated the technology into a commercial hand-held IMS device for use by the military and other public safety organizations. Capable of detecting and identifying molecules with part-per-billion sensitivity, the technology now provides soldiers with portable explosives and chemical warfare agent detection. The device is also being adapted for detecting drugs and is employed in industrial processes such as semiconductor manufacturing.

Cognitive avoidance of intrusive memories: recall vantage perspective and associations with depression.

PubMed

Williams, Alishia D; Moulds, Michelle L

2007-06-01

Although recent research demonstrates that intrusive memories represent an overlapping cognitive feature of depression and post-traumatic stress disorder (PTSD), there is still a general paucity of research investigating the prevalence and maintenance of intrusive memories in depression. The current study investigated the association between a range of cognitive avoidant mechanisms that characterize PTSD samples (i.e., suppression, rumination, emotional detachment, and an observer vantage perspective) and intrusive memories of negative autobiographical events in relation to dysphoria. Hypotheses were based on the proposition that employment of these cognitive mechanisms would hinder the emotional processing of the negative event, thus contributing to the maintenance of intrusions. Results supported an association between negative intrusive memories, dysphoria, and avoidant mechanisms. Significant differences were also found between field and observer memories and measures of emotional detachment and rumination. Implications relating to intrusive memory maintenance and treatment approaches are discussed.

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.

[Analysis of intrusion errors in free recall].

PubMed

Diesfeldt, H F A

2017-06-01

Extra-list intrusion errors during five trials of the eight-word list-learning task of the Amsterdam Dementia Screening Test (ADST) were investigated in 823 consecutive psychogeriatric patients (87.1% suffering from major neurocognitive disorder). Almost half of the participants (45.9%) produced one or more intrusion errors on the verbal recall test. Correct responses were lower when subjects made intrusion errors, but learning slopes did not differ between subjects who committed intrusion errors and those who did not so. Bivariate regression analyses revealed that participants who committed intrusion errors were more deficient on measures of eight-word recognition memory, delayed visual recognition and tests of executive control (the Behavioral Dyscontrol Scale and the ADST-Graphical Sequences as measures of response inhibition). Using hierarchical multiple regression, only free recall and delayed visual recognition retained an independent effect in the association with intrusion errors, such that deficient scores on tests of episodic memory were sufficient to explain the occurrence of intrusion errors. Measures of inhibitory control did not add significantly to the explanation of intrusion errors in free recall, which makes insufficient strength of memory traces rather than a primary deficit in inhibition the preferred account for intrusion errors in free recall.

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

A novel organophosphorus hydrolase-based biosensor using mesoporous carbons and carbon black for the detection of organophosphate nerve agents.

PubMed

Lee, Joon Hwan; Park, Jae Yeon; Min, Kyoungseon; Cha, Hyung Joon; Choi, Suk Soon; Yoo, Young Je

2010-03-15

To detect organophosphate chemicals, which are used both as pesticides and as nerve agents, a novel biosensor based on organophosphorus hydrolase was developed. By using mesoporous carbon (MC) and carbon black (CB) as an anodic layer, the sensitivity of the sensor to p-nitrophenol (PNP), which is the product of the organophosphorus hydrolase reaction, was greatly improved. The MC/CB/glass carbon (GC) layer exhibited an enhanced amperometric response relative to a carbon nanotube (CNT)-modified electrode because it promoted electron transfer of enzymatically generated phenolic compounds (p-nitrophenol). The well-ordered nanopores, many edge-plane-like defective sites (EDSs), and high surface area of the MC resulted in increased sensitivity, and allowed for nanomolar-range detection of the analyte paraoxon. Thus, MCs are suitable for use in real-time biosensors. Under the optimized experimental conditions, the biosensor had a detection limit of 0.12 microM (36 ppb) and a sensitivity of 198 nA/microM for paraoxon. (c) 2009 Elsevier B.V. All rights reserved.

Imbalance detection in a manufacturing system: An agent-based model usage

NASA Astrophysics Data System (ADS)

Shevchuk, G. K.; Zvereva, O. M.; Medvedev, M. A.

2017-11-01

This paper delivers the results of the research work targeted at communications in a manufacturing system. A computer agent-based model which simulates manufacturing system functioning has been engineered. The system lifecycle consists of two recursively repeated stages: a communication stage and a production stage. Model data sets were estimated with the static Leontief's equilibrium equation usage. In experiments relationships between the manufacturing system lifecycle time and conditions of equilibrium violations have been identified. The research results are to be used to propose violation negative influence compensation methods.

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

Cup-shaped Intrusions, Morphology and Emplacement Mechanism Investigate Through Analogue Modelling

NASA Astrophysics Data System (ADS)

Mathieu, L.; van Wyk de Vries, B.

2007-12-01

We investigate the morphology of large-scale shallow-depth magma intrusions and sub-volcanic complexes with analogue models. Intrusions of analogue magma are done in a granular material that can contain a ductile layer. The model surface is flat to model the formation of plutonic intrusions and it is overlain by a cone when modelling late sub-volcanic complexes. For flat-top models, we obtain cup-shaped intrusions fed by dykes. Cup-shaped intrusions are inverted-cone like bodies. They are different from saucer-shaped intrusions as they possess neither a well developed sill-base, nor an outer rim. However, like saucers, cups are shallow depth intrusions that dome the country rocks. They initiate from an advancing dyke and first develop an inverted-cone like morphology. Then, the central thickness increases and thrusts form at the edge of the domed country rocks. At this stage, the intrusions progressively involve toward a lopolith shape. By using analogue magma of various viscosities we have been able to constrain key relationships: higher intrusion viscosity causes deeper initiation and the deeper they initiate, the larger is the intrusion diameter. A natural example of such intrusion might by the circles of volcanoes like the Azufre-Lastaria (Peru) that might be overlain be a large-scale cup-shaped intrusion. When adding a cone at the surface of the model and, sometimes, a thin ductile layer in the substratum, the morphology of cup-shaped intrusions vary. Note that the ductile layer of our models is not thick enough to induce the gravitational spreading of the cone. Generally, cup-shaped intrusions are asymmetric in cross section and elliptical in plan view. Their formation creates extension structures in the cone (croissant-shaped rift, straight rift or normal fault) and thrusts in some sectors below the cone. Both types of structures are bordered by strike-slip faults. Cups and saucers share many similarities, but differ probably in the fact that saucers are

Rapid polymerase chain reaction-based screening assay for bacterial biothreat agents.

PubMed

Yang, Samuel; Rothman, Richard E; Hardick, Justin; Kuroki, Marcos; Hardick, Andrew; Doshi, Vishal; Ramachandran, Padmini; Gaydos, Charlotte A

2008-04-01

To design and evaluate a rapid polymerase chain reaction (PCR)-based assay for detecting Eubacteria and performing early screening for selected Class A biothreat bacterial pathogens. The authors designed a two-step PCR-based algorithm consisting of an initial broad-based universal detection step, followed by specific pathogen identification targeted for identification of the Class A bacterial biothreat agents. A region in the bacterial 16S rRNA gene containing a highly variable sequence flanked by clusters of conserved sequences was chosen as the target for the PCR assay design. A previously described highly conserved region located within the 16S rRNA amplicon was selected as the universal probe (UniProbe, Integrated DNA Technology, Coralville, IA). Pathogen-specific TaqMan probes were designed for Bacillus anthracis, Yersinia pestis, and Francisella tularensis. Performance of the assay was assessed using genomic DNA extracted from the aforementioned biothreat-related organisms (inactivated or surrogate) and other common bacteria. The UniProbe detected the presence of all tested Eubacteria (31/31) with high analytical sensitivity. The biothreat-specific probes accurately identified organisms down to the closely related species and genus level, but were unable to discriminate between very close surrogates, such as Yersinia philomiragia and Bacillus cereus. A simple, two-step PCR-based assay proved capable of both universal bacterial detection and identification of select Class A bacterial biothreat and biothreat-related pathogens. Although this assay requires confirmatory testing for definitive species identification, the method has great potential for use in ED-based settings for rapid diagnosis in cases of suspected Category A bacterial biothreat agents.

Standoff detection of explosives and chemical agents using broadly tuned external-cavity quantum cascade lasers (EC-QCLs)

NASA Astrophysics Data System (ADS)

Takeuchi, Eric B.; Rayner, Timothy; Weida, Miles; Crivello, Salvatore; Day, Timothy

2007-10-01

Civilian soft targets such as transportation systems are being targeted by terrorists using IEDs and suicide bombers. Having the capability to remotely detect explosives, precursors and other chemicals would enable these assets to be protected with minimal interruption of the flow of commerce. Mid-IR laser technology offers the potential to detect explosives and other chemicals in real-time and from a safe standoff distance. While many of these agents possess "fingerprint" signatures in the mid-IR (i.e. in the 3-20 micron regime), their effective interrogation by a practical, field-deployable system has been limited by size, complexity, reliability and cost constraints of the base laser technology. Daylight Solutions has addressed these shortcomings by developing compact, portable, broadly tunable mid-IR laser sources based upon external-cavity quantum cascade technology. This technology is now being applied by Daylight in system level architectures for standoff and remote detection of explosives, precursors and chemical agents. Several of these architectures and predicted levels of performance will be presented.

An international perspective on Facebook intrusion.

PubMed

Błachnio, Agata; Przepiorka, Aneta; Benvenuti, Martina; Cannata, Davide; Ciobanu, Adela Magdalena; Senol-Durak, Emre; Durak, Mithat; Giannakos, Michail N; Mazzoni, Elvis; Pappas, Ilias O; Popa, Camelia; Seidman, Gwendolyn; Yu, Shu; Wu, Anise M S; Ben-Ezra, Menachem

2016-08-30

Facebook has become one of the most popular social networking websites in the world. The main aim of the study was to present an international comparison of Facebook intrusion and Internet penetration while examining possible gender differences. The study consisted of 2589 participants from eight countries: China, Greece, Israel, Italy, Poland, Romania, Turkey, USA. Facebook intrusion and Internet penetration were taken into consideration. In this study the relationship between Facebook intrusion and Internet penetration was demonstrated. Facebook intrusion was slightly negatively related to Internet penetration in each country. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rapid dike intrusion into Sakurajima volcano on August 15, 2015, as detected by multi-parameter ground deformation observations

NASA Astrophysics Data System (ADS)

Hotta, Kohei; Iguchi, Masato; Tameguri, Takeshi

2016-04-01

We present observations of ground deformation at Sakurajima in August 2015 and model the deformation using a combination of GNSS, tilt and strain data in order to interpret a rapid deformation event on August 15, 2015. The pattern of horizontal displacement during the period from August 14 to 16, 2015, shows a WNW-ESE extension, which suggests the opening of a dike. Using a genetic algorithm, we obtained the position, dip, strike length, width and opening of a dislocation source based on the combined data. A nearly vertical dike with a NNE-SSW strike was found at a depth of 1.0 km below sea level beneath the Showa crater. The length and width are 2.3 and 0.6 km, respectively, and a dike opening of 1.97 m yields a volume increase of 2.7 × 106 m3. 887 volcano-tectonic (VT) earthquakes beside the dike suggest that the rapid opening of the dike caused an accumulation of strain in the surrounding rocks, and the VT earthquakes were generated to release this strain. Half of the total amount of deformation was concentrated between 10:27 and 11:54 on August 15. It is estimated that the magma intrusion rate was 1 × 106 m3/h during this period. This is 200 times larger than the magma intrusion rate prior to one of the biggest eruptions at the summit crater of Minami-dake on July 24, 2012, and 2200 times larger than the average magma intrusion rate during the period from October 2011 to March 2012. The previous Mogi-type ground deformation is considered to be a process of magma accumulation in preexisting spherical reservoirs. Conversely, the August 2015 event was a dike intrusion and occurred in a different location to the preexisting reservoirs. The direction of the opening of the dike coincides with the T-axes and direction of faults creating a graben structure.

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

PubMed

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

2017-01-01

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

[Simultaneous intrusion and retraction of the anterior teeth using a three-piece base arch].

PubMed

Liu, D; Bai, D; Wang, C; Sun, W; Guo, J; Xi, R

2000-06-01

To evaluate the effects of the three-piece base arch on overbite correction of Class II malocclusion. 20 patients with high angle, flared incisors were treated using a three-piece base arch appliance. The intrusion force of four upper incisors was adjusted to approximately 50 g. The line of force action was 2 mm distally to the resistant center(RC) and the retraction force was 20 g, the right and left posterior segments were joined by a palatal bar. Cephalograms were taken before treatment (T1) and six months after treatment (T2). The upper molars moved mesially 0.60 +/- 0.35 mm and the distance of the vertical extrusion was 0.80 +/- 0.52 mm. The distances of the upper central incisor retraction and intrusion were -4.20 +/- 2.12 mm and 3.10 +/- 0.54 mm respectively. The RC of the central incisor retracted -4.12 +/- 1.96 mm and intruded 3.20 +/- 0.66 mm. The axial inclination of the upper incisor-palatal plane changed from 123.21 degrees +/- 4.26 degrees to 116.00 degrees +/- 3.96 degrees. The three-piece segmented approach can effectively intrude and retract the upper anterior teeth for flared incisors and deep overbite.

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

NASA Astrophysics Data System (ADS)

Rustam, Z.; Talita, A. S.

2017-07-01

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

Spin-lock imaging of exogenous exchange-based contrast agents to assess tissue pH.

PubMed

Zu, Zhongliang; Li, Hua; Jiang, Xiaoyu; Gore, John C

2018-01-01

Some X-ray contrast agents contain exchangeable protons that give rise to exchange-based effects on MRI, including chemical exchange saturation transfer (CEST). However, CEST has poor specificity to explicit exchange parameters. Spin-lock sequences at high field are also sensitive to chemical exchange. Here, we evaluate whether spin-locking techniques can detect the contrast agent iohexol in vivo after intravenous administration, and their potential for measuring changes in tissue pH. Two metrics of contrast based on R 1ρ , the spin lattice relaxation rate in the rotating frame, were derived from the behavior of R 1ρ at different locking fields. Solutions containing iohexol at different concentrations and pH were used to evaluate the ability of the two metrics to quantify exchange effects. Images were also acquired from rat brains bearing tumors before and after intravenous injections of iohexol to evaluate the potential of spin-lock techniques for detecting the agent and pH variations. The two metrics were found to depend separately on either agent concentration or pH. Spin-lock imaging may therefore provide specific quantification of iohexol concentration and the iohexol-water exchange rate, which reports on pH. Spin-lock techniques may be used to assess the dynamics of intravenous contrast agents and detect extracellular acidification. Magn Reson Med 79:298-305, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Detection of warfare agents in liquid foods using the brine shrimp lethality assay.

PubMed

Lumor, Stephen E; Diez-Gonzalez, Francisco; Labuza, Theodore P

2011-01-01

The brine shrimp lethality assay (BSLA) was used for rapid and non-specific detection of biological and chemical warfare agents at concentrations considerably below that which will cause harm to humans. Warfare agents detected include T-2 toxin, trimethylsilyl cyanide, and commercially available pesticides such as dichlorvos, diazinon, dursban, malathion, and parathion. The assay was performed by introducing 50 μL of milk or orange juice contaminated with each analyte into vials containing 10 freshly hatched brine shrimp nauplii in seawater. This was incubated at 28 °C for 24 h, after which mortality was determined. Mortality was converted to probits and the LC(50) was determined for each analyte by plotting probits of mortality against analyte concentration (log(10)). Our findings were the following: (1) the lethal effects of toxins dissolved in milk were observed, with T-2 toxin being the most lethal and malathion being the least, (2) except for parathion, the dosage (based on LC(50)) of analyte in a cup of milk (200 mL) consumed by a 6-y-old (20 kg) was less than the respective published rat LD(50) values, and (3) the BSLA was only suitable for detecting toxins dissolved in orange juice if incubation time was reduced to 6 h. Our results support the application of the BSLA for routine, rapid, and non-specific prescreening of liquid foods for possible sabotage by an employee or an intentional bioterrorist act. Practical Application: The findings of this study strongly indicate that the brine shrimp lethality assay can be adapted for nonspecific detection of warfare agents or toxins in food at any point during food production and distribution.

9 CFR 113.43 - Detection of chlamydial agents.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Detection of chlamydial agents. 113.43 Section 113.43 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE, DEPARTMENT OF... in a filed Outline of Production. (a) The yolk sac of 6-day-old chicken embryos shall be injected...

Ultrasensitive detection of explosives and chemical warfare agents by low-pressure photoionization mass spectrometry.

PubMed

Sun, Wanqi; Liang, Miao; Li, Zhen; Shu, Jinian; Yang, Bo; Xu, Ce; Zou, Yao

2016-08-15

On-spot monitoring of threat agents needs high sensitive instrument. In this study, a low-pressure photoionization mass spectrometer (LPPI-MS) was employed to detect trace amounts of vapor-phase explosives and chemical warfare agent mimetics under ambient conditions. Under 10-s detection time, the limits of detection of 2,4-dinitrotoluene, nitrotoluene, nitrobenzene, and dimethyl methyl phosphonate were 30, 0.5, 4, and 1 parts per trillion by volume, respectively. As compared to those obtained previously with PI mass spectrometric techniques, an improvement of 3-4 orders of magnitude was achieved. This study indicates that LPPI-MS will open new opportunities for the sensitive detection of explosives and chemical warfare agents. Copyright © 2016 Elsevier B.V. All rights reserved.

Method for improved selectivity in photo-activation and detection of molecular diagnostic agents

DOEpatents

Wachter, Eric A.; Fisher, Walter G.; Dees, H. Craig

1998-01-01

A method for the imaging of a particular volume of plant or animal tissue, wherein the plant or animal tissue contains at least one photo-active molecular agent. The method includes the steps of treating the particular volume of the plant or animal tissue with light sufficient to promote a simultaneous two-photon excitation of the photo-active molecular agent contained in the particular volume of the plant or animal tissue, photo-activating at least one of the at least one photo-active molecular agent in the particular volume of the plant or animal tissue, thereby producing at least one photo-activated molecular agent, wherein the at least one photo-activated molecular agent emits energy, detecting the energy emitted by the at least one photo-activated molecular agent, and producing a detected energy signal which is characteristic of the particular volume of plant or animal tissue. The present invention is also a method for the imaging of a particular volume of material, wherein the material contains at least one photo-active molecular agent.

Method for improved selectivity in photo-activation and detection of molecular diagnostic agents

DOEpatents

Wachter, E.A.; Fisher, W.G.; Dees, H.C.

1998-11-10

A method for the imaging of a particular volume of plant or animal tissue, wherein the plant or animal tissue contains at least one photo-active molecular agent. The method includes the steps of treating the particular volume of the plant or animal tissue with light sufficient to promote a simultaneous two-photon excitation of the photo-active molecular agent contained in the particular volume of the plant or animal tissue, photo-activating at least one of the at least one photo-active molecular agent in the particular volume of the plant or animal tissue, thereby producing at least one photo-activated molecular agent, wherein the at least one photo-activated molecular agent emits energy, detecting the energy emitted by the at least one photo-activated molecular agent, and producing a detected energy signal which is characteristic of the particular volume of plant or animal tissue. The present invention is also a method for the imaging of a particular volume of material, wherein the material contains at least one photo-active molecular agent. 13 figs.

Methods for improved selectivity in photo-activation and detection of molecular diagnostic agents

DOEpatents

Wachter, Eric A [Oak Ridge, TN; Fisher, Walter G [Knoxville, TN; Dees, H Craig [Knoxville, TN

2008-03-18

A method for the imaging of a particular volume of plant or animal tissue, wherein the plant or animal tissue contains at least one photo-active molecular agent. The method comprises the steps of treating the particular volume of the plant or animal tissue with light sufficient to promote a simultaneous two-photon excitation of the photo-active molecular agent contained in the particular volume of the plant or animal tissue, photo-activating at least one of the at least one photo-active molecular agent in the particular volume of the plant or animal tissue, thereby producing at least one photo-activated molecular agent, wherein the at least one photo-activated molecular agent emits energy, detecting the energy emitted by the at least one photo-activated molecular agent, and producing a detected energy signal which is characteristic of the particular volume of plant or animal tissue. The present invention also provides a method for the imaging of a particular volume of material, wherein the material contains at least one photo-active molecular agent.

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

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

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

2010-07-15

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

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

DTIC Science & Technology

2011-03-01

the actions of malicious and benign users of the Internet, as well as the engi- neering decisions giving rise to observed network topologies. Say and...with resilience, which is particularly important in the domain of quickly-evolving cyber threats. “Self-organization,” says Meadows, “is basically the...system design paradigm is to leverage the advantages of a distributed approach? What is meant by saying the witness conceptually rates the target

Sensitive detection of chemical agents and toxic industrial chemicals using active open-path FTIRs

NASA Astrophysics Data System (ADS)

Walter, William T.

2004-03-01

Active open-path FTIR sensors provide more sensitive detection of chemical agents than passive FTIRs, such as the M21 RSCAAL and JSLSCAD, and at the same time identify and quantify toxic industrial chemicals (TIC). Passive FTIRs are bistatic sensors relying on infrared sources of opportunity. Utilization of earth-based sources of opportunity limits the source temperatures available for passive chemical-agent FTIR sensors to 300° K. Active FTIR chemical-agent sensors utilize silicon carbide sources, which can be operated at 1500° K. The higher source temperature provides more than an 80-times increase in the infrared radiant flux emitted per unit area in the 7 to 14 micron spectral fingerprint region. Minimum detection limits are better than 5 μgm/m3 for GA, GB, GD, GF and VX. Active FTIR sensors can (1) assist first responders and emergency response teams in their assessment of and reaction to a terrorist threat, (2) provide information on the identification of the TIC present and their concentrations and (3) contribute to the understanding and prevention of debilitating disorders analogous to the Gulf War Syndrome for military and civilian personnel.

Individual differences in spatial configuration learning predict the occurrence of intrusive memories.

PubMed

Meyer, Thomas; Smeets, Tom; Giesbrecht, Timo; Quaedflieg, Conny W E M; Girardelli, Marta M; Mackay, Georgina R N; Merckelbach, Harald

2013-03-01

The dual-representation model of posttraumatic stress disorder (PTSD; Brewin, Gregory, Lipton, & Burgess, Psychological Review, 117, 210-232 2010) argues that intrusions occur when people fail to construct context-based representations during adverse experiences. The present study tested a specific prediction flowing from this model. In particular, we investigated whether the efficiency of temporal-lobe-based spatial configuration learning would account for individual differences in intrusive experiences and physiological reactivity in the laboratory. Participants (N = 82) completed the contextual cuing paradigm, which assesses spatial configuration learning that is believed to depend on associative encoding in the parahippocampus. They were then shown a trauma film. Afterward, startle responses were quantified during presentation of trauma reminder pictures versus unrelated neutral and emotional pictures. PTSD symptoms were recorded in the week following participation. Better configuration learning performance was associated with fewer perceptual intrusions, r = -.33, p < .01, but was unrelated to physiological responses to trauma reminder images (ps > .46) and had no direct effect on intrusion-related distress and overall PTSD symptoms, rs > -.12, ps > .29. However, configuration learning performance tended to be associated with reduced physiological responses to unrelated negative images, r = -.20, p = .07. Thus, while spatial configuration learning appears to be unrelated to affective responding to trauma reminders, our overall findings support the idea that the context-based memory system helps to reduce intrusions.

Multispectral photoacoustic decomposition with localized regularization for detecting targeted contrast agent

NASA Astrophysics Data System (ADS)

Tavakoli, Behnoosh; Chen, Ying; Guo, Xiaoyu; Kang, Hyun Jae; Pomper, Martin; Boctor, Emad M.

2015-03-01

Targeted contrast agents can improve the sensitivity of imaging systems for cancer detection and monitoring the treatment. In order to accurately detect contrast agent concentration from photoacoustic images, we developed a decomposition algorithm to separate photoacoustic absorption spectrum into components from individual absorbers. In this study, we evaluated novel prostate-specific membrane antigen (PSMA) targeted agents for imaging prostate cancer. Three agents were synthesized through conjugating PSMA-targeting urea with optical dyes ICG, IRDye800CW and ATTO740 respectively. In our preliminary PA study, dyes were injected in a thin wall plastic tube embedded in water tank. The tube was illuminated with pulsed laser light using a tunable Q-switch ND-YAG laser. PA signal along with the B-mode ultrasound images were detected with a diagnostic ultrasound probe in orthogonal mode. PA spectrums of each dye at 0.5 to 20 μM concentrations were estimated using the maximum PA signal extracted from images which are obtained at illumination wavelengths of 700nm-850nm. Subsequently, we developed nonnegative linear least square optimization method along with localized regularization to solve the spectral unmixing. The algorithm was tested by imaging mixture of those dyes. The concentration of each dye was estimated with about 20% error on average from almost all mixtures albeit the small separation between dyes spectrums.

Organization of the secure distributed computing based on multi-agent system

NASA Astrophysics Data System (ADS)

Khovanskov, Sergey; Rumyantsev, Konstantin; Khovanskova, Vera

2018-04-01

Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.

Saltwater intrusion monitoring in Florida

USGS Publications Warehouse

Prinos, Scott T.

2016-01-01

Florida's communities are largely dependent on freshwater from groundwater aquifers. Existing saltwater in the aquifers, or seawater that intrudes parts of the aquifers that were fresh, can make the water unusable without additional processing. The quality of Florida's saltwater intrusion monitoring networks varies. In Miami-Dade and Broward Counties, for example, there is a well-designed network with recently constructed short open-interval monitoring wells that bracket the saltwater interface in the Biscayne aquifer. Geochemical analyses of water samples from the network help scientists evaluate pathways of saltwater intrusion and movement of the saltwater interface. Geophysical measurements, collected in these counties, aid the mapping of the saltwater interface and the design of monitoring networks. In comparison, deficiencies in the Collier County monitoring network include the positioning of monitoring wells, reliance on wells with long open intervals that when sampled might provide questionable results, and the inability of existing analyses to differentiate between multiple pathways of saltwater intrusion. A state-wide saltwater intrusion monitoring network is being planned; the planned network could improve saltwater intrusion monitoring by adopting the applicable strategies of the networks of Miami-Dade and Broward Counties, and by addressing deficiencies such as those described for the Collier County network.

Layered intrusions of the Duluth Complex, Minnesota, USA

USGS Publications Warehouse

Miller, J.D.; Ripley, E.M.; ,

1996-01-01

The Duluth Complex and associated subvolcanic intrusions comprise a large (5000 km2) intrusive complex in northeastern Minnesota that was emplaced into comagmatic volcanics during the development of the 1.1 Ga Midcontinent rift in North America. In addition to anorthositic and felsic intrusions, the Duluth Complex is composed of many individual mafic layered intrusions of tholeiitic affinity. The cumulate stratigraphies and cryptic variations of six of the better exposed and better studied intrusions are described here to demonstrate the variability in their cumulus mineral paragenesis.

Love-Wave Sensors Combined with Microfluidics for Fast Detection of Biological Warfare Agents

PubMed Central

Matatagui, Daniel; Fontecha, José Luis; Fernández, María Jesús; Gràcia, Isabel; Cané, Carles; Santos, José Pedro; Horrillo, María Carmen

2014-01-01

The following paper examines a time-efficient method for detecting biological warfare agents (BWAs). The method is based on a system of a Love-wave immunosensor combined with a microfluidic chip which detects BWA samples in a dynamic mode. In this way a continuous flow-through of the sample is created, promoting the reaction between antigen and antibody and allowing a fast detection of the BWAs. In order to prove this method, static and dynamic modes have been simulated and different concentrations of BWA simulants have been tested with two immunoreactions: phage M13 has been detected using the mouse monoclonal antibody anti-M13 (AM13), and the rabbit immunoglobulin (Rabbit IgG) has been detected using the polyclonal antibody goat anti-rabbit (GAR). Finally, different concentrations of each BWA simulants have been detected with a fast response time and a desirable level of discrimination among them has been achieved. PMID:25029282

IMS software developments for the detection of chemical warfare agent

NASA Technical Reports Server (NTRS)

Klepel, ST.; Graefenhain, U.; Lippe, R.; Stach, J.; Starrock, V.

1995-01-01

Interference compounds like gasoline, diesel, burning wood or fuel, etc. are presented in common battlefield situations. These compounds can cause detectors to respond as a false positive or interfere with the detector's ability to respond to target compounds such as chemical warfare agents. To ensure proper response of the ion mobility spectrometer to chemical warfare agents, two special software packages were developed and incorporated into the Bruker RAID-1. The programs suppress interferring signals caused by car exhaust or smoke gases resulting from burning materials and correct the influence of variable sample gas humidity which is important for detection and quantification of blister agents like mustard gas or lewisite.

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.

Sulfide intrusion in the tropical seagrasses Thalassia testudinum and Syringodium filiforme

NASA Astrophysics Data System (ADS)

Holmer, Marianne; Pedersen, Ole; Krause-Jensen, Dorte; Olesen, Birgit; Hedegård Petersen, Malene; Schopmeyer, Stephanie; Koch, Marguerite; Lomstein, Bente Aa.; Jensen, Henning S.

2009-11-01

Sulfur and oxygen dynamics in the seagrasses Thalassia testudinum and Syringodium filiforme and their sediments were studied in the US Virgin Islands (USVI) in order to explore sulfide intrusion into tropical seagrasses. Four study sites were selected based on the iron concentration in sediments and on proximity to anthropogenic nutrient sources. Meadow characteristics (shoot density, above- and below-ground biomass, nutrient content) were sampled along with sediment biogeochemistry. Sulfide intrusion was high in T. testudinum, as up to 96% of total sulfur in the plant was derived from sediment-derived sulfides. The sulfide intrusion was negatively correlated to the turnover of sulfides in the sediments regulated by both plant parameters and sediment sulfur pools. Sediment iron content played an indirect role by affecting sulfide turnover rates. Leaf production was negatively correlated with sulfide intrusion suggesting that active growth reduced sulfide intrusion. Sulfide intrusion was lower in S. filiforme (up to 44%) compared to T. testudinum consistent with a higher internal nighttime oxygen concentrations found for S. filiforme. When S. filiforme can take advantage of its ability to maintain high internal oxygen concentrations, as was the case on the USVI, it could increase its success in colonizing unvegetated disturbed sediments with potentially high sulfide concentrations.

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

Setting up a mobile Lidar (DIAL) system for detecting chemical warfare agents

NASA Astrophysics Data System (ADS)

Kavosh Tehrani, M.; Mohammad, M. Malek; Jaafari, E.; Mobashery, A.

2015-03-01

The mobile light detection and ranging DIAL system of Malek Ashtar University of Technology has been developed for the detection of chemical warfare agents whose absorption wavelengths are in the range of 9.2-10.8 μm tunable CO2 lasers of the system. In this paper, this system is first described and then ammonia detection is analyzed experimentally. Also, experimental results of detecting a sarin agent simulant, dimethyl-methyl phosphonate (DMMP), are presented. The power levels received from different ranges to detect specific concentrations of NH3 and DMMP have been measured and debated. The primary test results with a 150 ns clipped pulse width by passive pinhole plasma shutter indicate that the system is capable of monitoring several species of pollutants in the range of about 1 km, with a 20 m spatial and 2 min temporal resolution.

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Norman Steve; Christie, William

2014-01-01

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

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

Enhanced situational awareness in the maritime domain: an agent-based approach for situation management

NASA Astrophysics Data System (ADS)

Brax, Christoffer; Niklasson, Lars

2009-05-01

Maritime Domain Awareness is important for both civilian and military applications. An important part of MDA is detection of unusual vessel activities such as piracy, smuggling, poaching, collisions, etc. Today's interconnected sensorsystems provide us with huge amounts of information over large geographical areas which can make the operators reach their cognitive capacity and start to miss important events. We propose and agent-based situation management system that automatically analyse sensor information to detect unusual activity and anomalies. The system combines knowledge-based detection with data-driven anomaly detection. The system is evaluated using information from both radar and AIS sensors.

From intrusive to oscillating thoughts.

PubMed

Peirce, Anne Griswold

2007-10-01

This paper focused on the possibility that intrusive thoughts (ITs) are a form of an evolutionary, adaptive, and complex strategy to prepare for and resolve stressful life events through schema formation. Intrusive thoughts have been studied in relation to individual conditions, such as traumatic stress disorder and obsessive-compulsive disorder. They have also been documented in the average person experiencing everyday stress. In many descriptions of thought intrusion, it is accompanied by thought suppression. Several theories have been put forth to describe ITs, although none provides a satisfactory explanation as to whether ITs are a normal process, a normal process gone astray, or a sign of pathology. There is also no consistent view of the role that thought suppression plays in the process. I propose that thought intrusion and thought suppression may be better understood by examining them together as a complex and adaptive mechanism capable of escalating in times of need. The ability of a biological mechanism to scale up in times of need is one hallmark of a complex and adaptive system. Other hallmarks of complexity, including self-similarity across scales, sensitivity to initial conditions, presence of feedback loops, and system oscillation, are also discussed in this article. Finally, I propose that thought intrusion and thought suppression are better described together as an oscillatory cycle.

Method and apparatus for enhanced detection of toxic agents

DOEpatents

Greenbaum, Elias [Knoxville, TN; Rodriguez, Jr., Miguel; Wu, Jie Jayne [Knoxville, TN; Qi, Hairong [Knoxville, TN

2012-06-12

A water quality analyzer for real-time detection according to the invention comprises a biased AC electro-osmosis (ACEO) cell for receiving a fluid to be analyzed having a plurality photosynthetic organisms therein, and concentrating the plurality photosynthetic organisms into at least one concentrated region. A photodetector is provided for obtaining a measured photosynthetic activity of the plurality of photosynthetic organisms in the concentrated region, wherein chemical, biological or radiological agents reduce a nominal photosynthetic activity of the photosynthetic organisms. An electronics package analyzes the measured photosynthetic activity to indicate a presence of the chemical, biological or radiological agents in the fluid.

Vapor Intrusion

EPA Pesticide Factsheets

Vapor intrusion occurs when there is a migration of volatile chemicals from contaminated groundwater or soil into an overlying building. Volatile chemicals can emit vapors that may migrate through subsurface soils and into indoor air spaces.

Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring.

PubMed

Alcalá, José M; Ureña, Jesús; Hernández, Álvaro; Gualda, David

2017-02-11

The ageing of the population, and their increasing wish of living independently, are motivating the development of welfare and healthcare models. Existing approaches based on the direct heath-monitoring using body sensor networks (BSN) are precise and accurate. Nonetheless, their intrusiveness causes non-acceptance. New approaches seek the indirect monitoring through monitoring activities of daily living (ADLs), which proves to be a suitable solution. ADL monitoring systems use many heterogeneous sensors, are less intrusive, and are less expensive than BSN, however, the deployment and maintenance of wireless sensor networks (WSN) prevent them from a widespread acceptance. In this work, a novel technique to monitor the human activity, based on non-intrusive load monitoring (NILM), is presented. The proposal uses only smart meter data, which leads to minimum intrusiveness and a potential massive deployment at minimal cost. This could be the key to develop sustainable healthcare models for smart homes, capable of complying with the elderly people' demands. This study also uses the Dempster-Shafer theory to provide a daily score of normality with regard to the regular behavior. This approach has been evaluated using real datasets and, additionally, a benchmarking against a Gaussian mixture model approach is presented.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Distributed Intrusion Detection for Computer Systems Using Communicating Agents

DTIC Science & Technology

2000-01-01

Log for a variety of suspicious events (like repeated failed login attempts), and alerts the IDAgent processes immediately via pipes when it finds...UX, IBM LAN Server, Raptor Eagle Firewalls, ANS Interlock Firewalls, and SunOS BSM. This program appears to be robust across many platforms. EMERALD ...Neumann, 1999] is a system developed by SRI International with research funding from DARPA. The EMERALD project will be the successor to Next

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.

WISESight : a multispectral smart video-track intrusion monitor.

DOT National Transportation Integrated Search

2015-05-01

International Electronic Machines : Corporation (IEM) developed, tested, and : validated a unique smart video-based : intrusion monitoring system for use at : highway-rail grade crossings. The system : used both thermal infrared (IR) and : visible/ne...

AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

PubMed Central

Bruch, Elizabeth; Atwell, Jon

2014-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

Metal cation detection in positive ion mode electrospray ionization mass spectrometry using a tetracationic salt as a gas-phase ion-pairing agent: evaluation of the effect of chelating agents on detection sensitivity.

PubMed

Xu, Chengdong; Dodbiba, Edra; Padivitage, Nilusha L T; Breitbach, Zachary S; Armstrong, Daniel W

2012-12-30

The detection of metal cations continues to be essential in many scientific and industrial areas of interest. The most common electrospray ionization mass spectrometry (ESI-MS) approach involves chelating the metal ions and detecting the organometallic complex in the negative ion mode. However, it is well known that negative ion mode ESI-MS is generally less sensitive than the positive ion mode. To achieve greater sensitivity, it is necessary to examine the feasibility of detecting the chelated metal cations in positive ion mode ESI-MS. Since highly solvated native metal cations have relatively low ionization efficiency in ESI-MS, and can be difficult to detect in the positive ion mode, a tetracationic ion-pairing agent was added to form a complex with the negatively charged metal chelate. The use of the ion-pairing agent leads to the generation of an overall positively charged complex, which can be detected at higher m/z values in the positive ion mode by electrospray ionization linear quadrupole ion trap mass spectrometry. Thirteen chelating agents with diverse structures were evaluated in this study. The nature of the chelating agent played as important a role as was previously determined for cationic pairing agents. The detection limits of six metal cations reached sub-picogram levels and significant improvements were observed when compared to negative ion mode detection where the metal-chelates were monitored without adding the ion-pairing reagent (IPR). Also, selective reaction monitoring (SRM) analyses were performed on the ternary complexes, which improved detection limits by one to three orders of magnitude. With this method it was possible to analyze the metal cations in the positive ion mode ESI-MS with the advantage of speed, sensitivity and selectivity. The optimum solution pH for this type of analysis is 5-7. Tandem mass spectrometry (MS/MS) further increases the sensitivity. Speciation is straightforward making this a broadly useful approach for the

Detection of chemical agent aerosols

NASA Astrophysics Data System (ADS)

Fox, Jay A.; Ahl, Jeffrey L.; D'Amico, Francis M.; Vanderbeek, Richard G.; Moon, Raphael; Swim, Cynthia R.

1999-05-01

One of the major threats presented by a chemical agent attack is that of a munition exploding overhead and 'raining' aerosols which can contaminate surfaces when they impact. Since contact with these surfaces can be fatal, it is imperative to know when such an attack has taken place and the likely threat density and location. We present the results of an experiment designed to show the utility of a CO2 lidar in detecting such an attack. Testing occurred at Dugway Proving Grounds, Utah and involved the simulation of an explosive airburst chemical attack. Explosions occurred at a height of 30 m and liquid droplets from two chemicals, PEG-200 (polyethylene glycol 200) and TEP (triethylphosphate), were expelled and fell to the ground. The munition was the U.S. Army M9 Simulator, Projectile, Airburst, Liquid (SPAL) system that is designed for chemical warfare training exercises. The instrument that was used to detect the presence of the aerosols was the Laser Standoff Chemical Detector (LSCD) which is a light detection and ranging (LIDAR) system that utilizes a rapidly tunable, pulsed CO2 laser. The LIDAR scanned a horizontal path approximately 5 - 8 m above the ground in order to measure the concentration of liquid deposition. The LIDAR data were later correlated with card data to determine how well the system could predict the location and quantity of liquid deposition on the ground.

An Excel®-based visualization tool of 2-D soil gas concentration profiles in petroleum vapor intrusion

PubMed Central

Verginelli, Iason; Yao, Yijun; Suuberg, Eric M.

2017-01-01

In this study we present a petroleum vapor intrusion tool implemented in Microsoft® Excel® using Visual Basic for Applications (VBA) and integrated within a graphical interface. The latter helps users easily visualize two-dimensional soil gas concentration profiles and indoor concentrations as a function of site-specific conditions such as source strength and depth, biodegradation reaction rate constant, soil characteristics and building features. This tool is based on a two-dimensional explicit analytical model that combines steady-state diffusion-dominated vapor transport in a homogeneous soil with a piecewise first-order aerobic biodegradation model, in which rate is limited by oxygen availability. As recommended in the recently released United States Environmental Protection Agency's final Petroleum Vapor Intrusion guidance, a sensitivity analysis and a simplified Monte Carlo uncertainty analysis are also included in the spreadsheet. PMID:28163564

An Excel®-based visualization tool of 2-D soil gas concentration profiles in petroleum vapor intrusion.

PubMed

Verginelli, Iason; Yao, Yijun; Suuberg, Eric M

2016-01-01

In this study we present a petroleum vapor intrusion tool implemented in Microsoft ® Excel ® using Visual Basic for Applications (VBA) and integrated within a graphical interface. The latter helps users easily visualize two-dimensional soil gas concentration profiles and indoor concentrations as a function of site-specific conditions such as source strength and depth, biodegradation reaction rate constant, soil characteristics and building features. This tool is based on a two-dimensional explicit analytical model that combines steady-state diffusion-dominated vapor transport in a homogeneous soil with a piecewise first-order aerobic biodegradation model, in which rate is limited by oxygen availability. As recommended in the recently released United States Environmental Protection Agency's final Petroleum Vapor Intrusion guidance, a sensitivity analysis and a simplified Monte Carlo uncertainty analysis are also included in the spreadsheet.

[Interference for Various Quench Agents of Chemical Disinfectants on Detection of Endotoxin Activities in Water].

PubMed

Zhang, Can; Liu, Wen-jun; Shi, Yun; An, Dai-zhi; Bai, Miao; Xu, Wen

2015-05-01

The quenching agents such as histidine, glycine, ascorbic acid, Tween-80, sodium sulfite and sodium hyposulfite are commonly used for quenching the residual disinfectant in water. In this paper, in order to select the optimal type and concentration range of quenching agents prior to the Limulus assays, the interference effects of each quenching agent at different concentrations on endotoxin detection were investigated by the Limulus assays of kinetic-turbidity. Our results identified that, as for 0-1.0% concentration of histidine, ascorbic acid, Tween-80, sodium sulfite (pH unadjusted and pH neutral), interference on the Limulus assays was existed. Hence, these quenching agents could not be applied as neutralizers prior to Limulus assays. Although, there was no interference on endotoxin detection for the glycine, a yellow color, developed by the quenching products of glycine and glutaric dialdehyde, contributed to false positive results. Hence, glycine should not be used as quenching agents in Limulus assays for samples containing glutaric dialdehyde. Compared with other quenching agents as histidine, glycine, ascorbic acid, Tween-80, sodium sulfite, 0-1.0% concentration of sodium hyposulfite elicited no obvious interference, while 1.0%-5.0% concentration of sodium hyposulfite illustrated exhibition effect for endotoxin detection. All in all, compared with other quenching agents as histidine, glycine, ascorbic acid, Tween-80 and sodium sulfite, sodium hyposulfite is suitable for quenching chemicals prior to endotoxin detection and less than 0.5% of concentration is allowable.

Laser Based Stand-Off Detection of Biological Agents (detection a distance des agents biologiques a l’aide du laser)

DTIC Science & Technology

2010-02-01

overview of their respective national up-date. Dr. Roy presented a new technique for evaluating the bioaerosol particle size based on a multiple...Field-of-View LIDAR technique . Mr. Levesque from INO gave an overview of their expertise in LIDAR and biophotonics. Dr. Chin from Laval University gave... techniques have the potential to detect particulate aerosols remotely at distances of many kilometres [1]. They can provide spatially resolved

Laser based in-situ and standoff detection of chemical warfare agents and explosives

NASA Astrophysics Data System (ADS)

Patel, C. Kumar N.

2009-09-01

Laser based detection of gaseous, liquid and solid residues and trace amounts has been developed ever since lasers were invented. However, the lack of availability of reasonably high power tunable lasers in the spectral regions where the relevant targets can be interrogated as well as appropriate techniques for high sensitivity, high selectivity detection has hampered the practical exploitation of techniques for the detection of targets important for homeland security and defense applications. Furthermore, emphasis has been on selectivity without particular attention being paid to the impact of interfering species on the quality of detection. Having high sensitivity is necessary but not a sufficient condition. High sensitivity assures a high probability of detection of the target species. However, it is only recently that the sensor community has come to recognize that any measure of probability of detection must be associated with a probability of false alarm, if it is to have any value as a measure of performance. This is especially true when one attempts to compare performance characteristics of different sensors based on different physical principles. In this paper, I will provide a methodology for characterizing the performance of sensors utilizing optical absorption measurement techniques. However, the underlying principles are equally application to all other sensors. While most of the current progress in high sensitivity, high selectivity detection of CWAs, TICs and explosives involve identifying and quantifying the target species in-situ, there is an urgent need for standoff detection of explosives from safe distances. I will describe our results on CO2 and quantum cascade laser (QCL) based photoacoustic sensors for the detection of CWAs, TICs and explosives as well the very new results on stand-off detection of explosives at distances up to 150 meters. The latter results are critically important for assuring safety of military personnel in battlefield

Development of electrochemical sensors for trace detection of explosives and for the detection of chemical warfare agents

NASA Astrophysics Data System (ADS)

Berger, T.; Ziegler, H.; Krausa, Michael

2000-08-01

A huge number of chemical sensors are based on electrochemical measurement methods. Particularly amperometric sensorsystems are employed for the fast detection of pollutants in industry and environment as well as for analytic systems in the medical diagnosis. The large number of different applications of electrochemical sensors is based on the high sensitivity of electrochemical methods and on the wide of possibilities to enhance the selectivity by variation of electrochemical and chemical parameters. Besides this, electrochemical sensorsystems are frequently simple to operate, transportable and cheap. Up to now the electrochemical method of cyclic voltammetry is used only seldom for sensors. Clearly the efficiency of cyclic voltammetry can be seen at the sensorsystem for the detection of nitro- and aminotoluenes in solids and waters as presented here. The potentiodynamic sensors system can be employed for the fast and easy risk estimation of contaminated areas. Because of the high sensitivity of electrochemical methods the detection of chemical substances with a low vapor pressure is possible also. The vapor pressure of TNT at room temperature is 7 ppb for instances. With a special electrochemical set-up we were able to measure TNT approximately 10 cm above a TNT-sample. In addition we were able to estimate TNT in the gaseous phase approximately 10 cm above a real plastic mine. Therefore it seems to be possible to develop an electrochemical mien detection. Moreover, we present that the electrochemical detection of RDX, HMX and chemical warfare agents is also possible.

Ecology Based Decentralized Agent Management System

NASA Technical Reports Server (NTRS)

Peysakhov, Maxim D.; Cicirello, Vincent A.; Regli, William C.

2004-01-01

The problem of maintaining a desired number of mobile agents on a network is not trivial, especially if we want a completely decentralized solution. Decentralized control makes a system more r e bust and less susceptible to partial failures. The problem is exacerbated on wireless ad hoc networks where host mobility can result in significant changes in the network size and topology. In this paper we propose an ecology-inspired approach to the management of the number of agents. The approach associates agents with living organisms and tasks with food. Agents procreate or die based on the abundance of uncompleted tasks (food). We performed a series of experiments investigating properties of such systems and analyzed their stability under various conditions. We concluded that the ecology based metaphor can be successfully applied to the management of agent populations on wireless ad hoc networks.

Non-Intrusive Impedance-Based Cable Tester

NASA Technical Reports Server (NTRS)

Medelius, Pedro J. (Inventor); Simpson, Howard J. (Inventor)

1999-01-01

A non-intrusive electrical cable tester determines the nature and location of a discontinuity in a cable through application of an oscillating signal to one end of the cable. The frequency of the oscillating signal is varied in increments until a minimum, close to zero voltage is measured at a signal injection point which is indicative of a minimum impedance at that point. The frequency of the test signal at which the minimum impedance occurs is then employed to determine the distance to the discontinuity by employing a formula which relates this distance to the signal frequency and the velocity factor of the cable. A numerically controlled oscillator is provided to generate the oscillating signal, and a microcontroller automatically controls operation of the cable tester to make the desired measurements and display the results. The device is contained in a portable housing which may be hand held to facilitate convenient use of the device in difficult to access locations.

Fronts and intrusions in the upper Deep Polar Water of the Eurasian and Makarov basins

NASA Astrophysics Data System (ADS)

Kuzmina, Natalia; Rudels, Bert; Zhurbas, Natalia; Lyzhkov, Dmitry

2013-04-01

CTD data obtained in the Arctic Basin are analyzed to describe structural features of intrusive layers and fronts encountered in the upper Deep Polar Water. This work is an extension of Arctic intrusions studies by Rudels et al. (1999) and Kuzmina et al. (2011). Numerous examples of fronts and intrusions observed in a deep layer (depth range of 600-1300 m) in the Eurasian and Makarov basins where salinity is increasing, and temperature is decreasing with depth (stable-stable thermohaline stratification), are described. The data are used to estimate hydrological parameters capable of determining different types of fronts and characterizing intrusive layers depending on the front structure. Coherence of intrusive layers is shown to get broken with the change of front structure. An evidence is found that enhanced turbulent mixing above local bottom elevations can prevent from intrusive layering. A linear stability model description of the observed intrusions is developed based on the Merryfield's (2000) assumption that interleaving is caused by differential mixing. Theoretical analysis is focused on prediction of the slopes of unstable modes at baroclinic and thermohaline fronts. Apparent vertical diffusivity due to turbulent mixing at baroclinic and thermohaline fronts is estimated on the basis of comparison of observed intrusion slopes with modeled slopes of the most unstable modes. Apparent lateral diffusivity is estimated too, based on Joyce (1980) approach. These estimates show that intrusive instability of fronts caused by differential mixing can result in sizable values of apparent lateral heat diffusivity in the deep Arctic layer that are quite comparable with those of the upper and intermediate Arctic layers (Walsh, Carmack, 2003; Kuzmina et al., 2011).

Nanostructured thermites based on iodine pentoxide for bio agent defeat systems.

NASA Astrophysics Data System (ADS)

Hobosyan, Mkhitar; Kazansky, Alexander; Martirosyan, Karen

2011-10-01

The risk for bioterrorist events involving the intentional airborne release of contagious agents has led to development of new approaches for bio agent defeat technologies both indoors and outdoors. Novel approaches to defeat harmful biological agents have generated a strong demand for new active materials. The preferred solutions are to neutralize the biological agents within the immediate target area by using aerosolized biocidal substances released in situ by high energetic reactions. By using nano-thermite reactions, with energy release up to 25 kJ/cc, based on I2O5/Al nanoparticles we intend to generate high quantity of vaporized iodine for spatial deposition onto harmful bacteria for their destruction. In this report, the effect of reaction product on growth and survival of Escherichia coli (E-coli) expressing GFP (Green Fluorescent Protein) was investigated. Moreover, we developed an approach to increase sensitivity of the detection. The study has shown that I2O5/Al nanosystem is extremely effective to disinfect harmful biological agents such (E-coli) bacteria in seconds.

Detection/classification/quantification of chemical agents using an array of surface acoustic wave (SAW) devices

NASA Astrophysics Data System (ADS)

Milner, G. Martin

2005-05-01

ChemSentry is a portable system used to detect, identify, and quantify chemical warfare (CW) agents. Electro chemical (EC) cell sensor technology is used for blood agents and an array of surface acoustic wave (SAW) sensors is used for nerve and blister agents. The combination of the EC cell and the SAW array provides sufficient sensor information to detect, classify and quantify all CW agents of concern using smaller, lighter, lower cost units. Initial development of the SAW array and processing was a key challenge for ChemSentry requiring several years of fundamental testing of polymers and coating methods to finalize the sensor array design in 2001. Following the finalization of the SAW array, nearly three (3) years of intensive testing in both laboratory and field environments were required in order to gather sufficient data to fully understand the response characteristics. Virtually unbounded permutations of agent characteristics and environmental characteristics must be considered in order to operate against all agents and all environments of interest to the U.S. military and other potential users of ChemSentry. The resulting signal processing design matched to this extensive body of measured data (over 8,000 agent challenges and 10,000 hours of ambient data) is considered to be a significant advance in state-of-the-art for CW agent detection.

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...

Insect-gene-activity detection system for chemical and biological warfare agents and toxic industrial chemicals

NASA Astrophysics Data System (ADS)

Mackie, Ryan S.; Schilling, Amanda S.; Lopez, Arturo M.; Rayms-Keller, Alfredo

2002-02-01

Detection of multiple chemical and biological weapons (CBW) agents and/or complex mixtures of toxic industrial chemicals (TIC) is imperative for both the commercial and military sectors. In a military scenario, a multi-CBW attack would create confusion, thereby delaying decontamination and therapeutic efforts. In the commercial sector, polluted sites invariably contain a mixture of TIC. Novel detection systems capable of detecting CBW and TIC are sorely needed. While it may be impossible to build a detector capable of discriminating all the possible combinations of CBW, a detection system capable of statistically predicting the most likely composition of a given mixture is within the reach of current emerging technologies. Aquatic insect-gene activity may prove to be a sensitive, discriminating, and elegant paradigm for the detection of CBW and TIC. We propose to systematically establish the expression patterns of selected protein markers in insects exposed to specific mixtures of chemical and biological warfare agents to generate a library of biosignatures of exposure. The predicting capabilities of an operational library of biosignatures of exposures will allow the detection of emerging novel or genetically engineered agents, as well as complex mixtures of chemical and biological weapons agents. CBW and TIC are discussed in the context of war, terrorism, and pollution.

Reassessment of the volume of the Las Aguilas mafic-ultramafic intrusives, San Luis, Argentina, based on an alternative geophysical model

NASA Astrophysics Data System (ADS)

Claudia, Zaffarana; Silvana, Geuna; Stella, Poma; Alberto, Patiño Douce

2011-10-01

In the Sierra de San Luis, Central Argentina, a belt of small and discontinuous lenses of mafic-ultramafic rocks intrude a polydeformed basement and are thought to be the cause of a local increase of the metamorphic grade from amphibolite to granulite facies conditions. This assumption was especially based on forward modelling of a huge gravity anomaly centered over the Sierra de San Luis, which lead some workers to think that a vast volume of mafic-ultramafic rocks lay in shallow levels. Here, we propose an alternative model to explain this anomaly, in which the mafic-ultramafic intrusion is not the ultimate source. Therefore, there is no need to propose a bigger size than that observed in outcrops for the mafic-ultramafic bodies. The thermal effect of the emplacement of mafic-ultramafic sills and dikes on the host rocks was estimated applying a simple analytical solution (error function) for heating of a semi-infinite half space (the country rocks) in contact with a hotter sheet of finite thickness (the mafic-ultramafic intrusion). Results indicate that the effect of the intrusion of these hot mafic magmas is local, because beyond a few hundred meters from the contact zone temperatures never exceed 600 °C, and a few km from the intrusion they barely increase 50 °C relative to the initial temperature. These results, together with the preservation of primary igneous characteristics (such as rhythmic layering) being overprinted by metamorphic textural changes, indicate that the intrusion occurred before regional deformation. It is suggested that the thermal anomaly in the Pringles Metamorphic Complex could have been mainly caused by factors inherent to their geodynamic setting.

Evaluation of Transabdominal Ultrasound with Oral Cellulose-Based Contrast Agent in the Detection and Surveillance of Gastric Ulcer.

PubMed

Liu, Zhijun; Guo, Jintao; Wang, Shupeng; Zhao, Ying; Liu, Zhining; Li, Jing; Ren, Weidong; Tang, Shaoshan; Xie, Limei; Huang, Ying; Sun, Siyu; Huang, Liping

2017-07-01

The aim of this study was to assess the role of transabdominal ultrasound with cellulose-based oral contrast agent (TUS-OCCA) in the detection and surveillance of gastric ulcer. The study was approved by the institutional review board at Shengjing Hospital of China Medical University. A total of 124 consecutive patients with benign gastric ulcer diagnosed by gastroscopy and biopsy were enrolled. Serial TUS-OCCA (approximately 1 exam every 2 wk) was performed to monitor the effects of treatment, and additional interventions were planned according to the results. TUS-OCCA detected gastric ulcer in 76% of patients (94 of 124). The detection rates for lesions of ≤5 mm, lesions of 5-10 mm, lesions of 10-15 mm and lesions >15 mm were 32% (10 of 31), 77% (27 of 35), 96% (25 of 26) and 100% (32 of 32), respectively. The detection rates for lesions located in the antrum, angle and body were 70%, 84% and 85%, respectively. Among 30 undetected lesions, which ranged 2-13 mm in size, 11 were at the antrum, 9 at the angle, 3 in the body, 6 at the cardia and 1 at the fundus. During the follow-up period, patients underwent a mean of 3.8 TUS-OCCA examinations (range 2-7), and ulcers were healed after 8 wk (range 2-12 wk) of standard therapy in 76 patients. Eighteen patients who did not show improvement after standard therapy underwent repeat gastroscopy with biopsy. Repeat biopsy was positive for gastric cancer in 4 of these: 2 of the remaining 14 were diagnosed with gastric cancer at gastrectomy, and 12 were diagnosed with chronic benign ulcer. These results indicate that serial TUS-OCCA can be used for close monitoring during routine treatment of gastric ulcers that are detectable by TUS-OCCA and that monitoring by TUS-OCCA can guide additional interventions. A non-invasive follow-up program based on TUS-OCCA can also help to detect gastric cancers that have been misdiagnosed as benign ulcers at the initial endoscopic biopsy. Copyright © 2017 The Authors. Published by

Surface-enhanced Raman detection of CW agents in water using gold sol gel substrates

NASA Astrophysics Data System (ADS)

Premasiri, W. Ranjith; Clarke, Richard H.; Womble, M. Edward

2002-02-01

The development of a water analysis system capable of detecting both inanimate trace chemical contaminants and viable microbial contaminants has long been a project of interest to our group. The capability of detecting both chemical and biological agent sources in a single device configuration would clearly add to the value of such a product. In the present work, we describe results with chemical warfare agents from our efforts to produce a Raman system for the detection of both chemical and biological warfare agents in water. We utilize laser Raman light scattering and employ Surface Enhanced Raman Spectroscopy (SERS)on solid state gold sol-gel detectors combined with fiber optic collection of the enhanced light signal in the sampling system to augment the normally low intensity Raman Scattering signal from trace materials.

Stand-off spectroscopy for the detection of chemical warfare agents

NASA Astrophysics Data System (ADS)

Clewes, Rhea J.; Howle, Chris R.; Stothard, David J. M.; Dunn, Malcolm H.; Robertson, Gordon; Miller, William; Malcolm, Graeme; Maker, Gareth; Cox, Rick; Williams, Brad; Russell, Matt

2012-10-01

The most desirable configuration for detection of toxic chemicals utilises the maximum distance between detector and hazard. This approach minimises the contamination of equipment or personnel. Where the target chemical is an involatile liquid, indirect detection of the liquid contamination is made difficult by inherently low vapour pressure. In this instance, direct detection of the chemical hazard is the best approach. Recent technology developments have allowed spectroscopic systems to provide multiple options for the stand-off detection of involatile chemical warfare agents (CWAs). Two different stand-off spectroscopic systems, based upon IR absorption and Raman spectroscopic techniques are described here. The Negative Contrast Imager (NCI) is based upon an optical parametric oscillator (OPO) source comprising a Q-switched intracavity MgO:PPLN crystal. This crystal has a fanned grating design and wavelength tuning is achieved by translating the PPLN crystal within the 1064 nm pump beam. This approach enables the production of shortwave and midwave IR radiation (1.5 - 1.8 μm and 2.6 - 3.8 μm, respectively), which is scanned across the scene of interest. Target materials that have an absorption feature commensurate with the wavelength of incoming radiation reduce the intensity of returned signal, resulting in dark pixels in the acquired image. This method enables location and classification of the target material. Stand-off Raman spectroscopy allows target chemicals to be identified at range through comparison of the acquired signature relative to a spectral database. In this work, we used a Raman system based upon a 1047 nm Nd:YLF laser source and a proprietary InGaAsP camera system. Utilisation of a longer excitation wavelength than most conventional stand-off detection systems (e.g. 532 or 785 nm) enables reduction of fluorescence from both the surface and the deposited chemicals, thereby revealing the Raman spectrum. NCI and Raman spectroscopy are able to

Enhancement of the conductivity detection signal in capillary electrophoresis systems using neutral cyclodextrins as sweeping agents.

PubMed

Boublík, Milan; Riesová, Martina; Dubský, Pavel; Gaš, Bohuslav

2018-06-01

Conductivity detection is a universal detection technique often encountered in electrophoretic separation systems, especially in modern chip-electrophoresis based devices. On the other hand, it is sparsely combined with another contemporary trend of enhancing limits of detection by means of various preconcentration strategies. This can be attributed to the fact that a preconcentration experimental setup usually brings about disturbances in a conductivity baseline. Sweeping with a neutral sweeping agent seems a good candidate for overcoming this problem. A neutral sweeping agent does not hinder the conductivity detection while a charged analyte may preconcentrate on its boundary due to a decrease in its effective mobility. This study investigates such sweeping systems theoretically, by means of computer simulations, and experimentally. A formula is provided for the reliable estimation of the preconcentration factor. Additionally, it is demonstrated that the conductivity signal can significantly benefit from slowing down the analyte and thus the overall signal enhancement can easily overweight amplification caused solely by the sweeping process. The overall enhancement factor can be deduced a priori from the linearized theory of electrophoresis implemented in the PeakMaster freeware. Sweeping by neutral cyclodextrin is demonstrated on an amplification of a conductivity signal of flurbiprofen in a real drug sample. Finally, a possible formation of unexpected system peaks in systems with a neutral sweeping agent is revealed by the computer simulation and confirmed experimentally. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Anabolic agents: recent strategies for their detection and protection from inadvertent doping

PubMed Central

Geyer, Hans; Schänzer, Wilhelm; Thevis, Mario

2014-01-01

According to the World Anti-Doping Agency (WADA) Prohibited List, anabolic agents consist of exogenous anabolic androgenic steroids (AAS), endogenous AAS and other anabolic agents such as clenbuterol and selective androgen receptor modulators (SARMs). Currently employed strategies for their improved detection include the prolongation of the detection windows for exogenous AAS, non-targeted and indirect analytical approaches for the detection of modified steroids (designer steroids), the athlete’s biological passport and isotope ratio mass spectrometry for the detection of the misuse of endogenous AAS, as well as preventive doping research for the detection of SARMs. The recent use of these strategies led to 4–80-fold increases of adverse analytical findings for exogenous AAS, to the detection of the misuse of new designer steroids, to adverse analytical findings of different endogenous AAS and to the first adverse analytical findings of SARMs. The strategies of the antidoping research are not only focused on the development of methods to catch the cheating athlete but also to protect the clean athlete from inadvertent doping. Within the past few years several sources of inadvertent doping with anabolic agents have been identified. Among these are nutritional supplements adulterated with AAS, meat products contaminated with clenbuterol, mycotoxin (zearalenone) contamination leading to zeranol findings, and natural products containing endogenous AAS. The protection strategy consists of further investigations in case of reasonable suspicion of inadvertent doping, publication of the results, education of athletes and development of methods to differentiate between intentional and unintentional doping. PMID:24632537

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

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.

Rapid laccolith intrusion driven by explosive volcanic eruption

NASA Astrophysics Data System (ADS)

Castro, Jonathan M.; Cordonnier, Benoit; Schipper, C. Ian; Tuffen, Hugh; Baumann, Tobias S.; Feisel, Yves

2016-11-01

Magmatic intrusions and volcanic eruptions are intimately related phenomena. Shallow magma intrusion builds subsurface reservoirs that are drained by volcanic eruptions. Thus, the long-held view is that intrusions must precede and feed eruptions. Here we show that explosive eruptions can also cause magma intrusion. We provide an account of a rapidly emplaced laccolith during the 2011 rhyolite eruption of Cordón Caulle, Chile. Remote sensing indicates that an intrusion began after eruption onset and caused severe (>200 m) uplift over 1 month. Digital terrain models resolve a laccolith-shaped body ~0.8 km3. Deformation and conduit flow models indicate laccolith depths of only ~20-200 m and overpressures (~1-10 MPa) that likely stemmed from conduit blockage. Our results show that explosive eruptions may rapidly force significant quantities of magma in the crust to build laccoliths. These iconic intrusions can thus be interpreted as eruptive features that pose unique and previously unrecognized volcanic hazards.

Rapid laccolith intrusion driven by explosive volcanic eruption.

PubMed

Castro, Jonathan M; Cordonnier, Benoit; Schipper, C Ian; Tuffen, Hugh; Baumann, Tobias S; Feisel, Yves

2016-11-23

Magmatic intrusions and volcanic eruptions are intimately related phenomena. Shallow magma intrusion builds subsurface reservoirs that are drained by volcanic eruptions. Thus, the long-held view is that intrusions must precede and feed eruptions. Here we show that explosive eruptions can also cause magma intrusion. We provide an account of a rapidly emplaced laccolith during the 2011 rhyolite eruption of Cordón Caulle, Chile. Remote sensing indicates that an intrusion began after eruption onset and caused severe (>200 m) uplift over 1 month. Digital terrain models resolve a laccolith-shaped body ∼0.8 km 3 . Deformation and conduit flow models indicate laccolith depths of only ∼20-200 m and overpressures (∼1-10 MPa) that likely stemmed from conduit blockage. Our results show that explosive eruptions may rapidly force significant quantities of magma in the crust to build laccoliths. These iconic intrusions can thus be interpreted as eruptive features that pose unique and previously unrecognized volcanic hazards.

Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring

PubMed Central

Alcalá, José M.; Ureña, Jesús; Hernández, Álvaro; Gualda, David

2017-01-01

The ageing of the population, and their increasing wish of living independently, are motivating the development of welfare and healthcare models. Existing approaches based on the direct heath-monitoring using body sensor networks (BSN) are precise and accurate. Nonetheless, their intrusiveness causes non-acceptance. New approaches seek the indirect monitoring through monitoring activities of daily living (ADLs), which proves to be a suitable solution. ADL monitoring systems use many heterogeneous sensors, are less intrusive, and are less expensive than BSN, however, the deployment and maintenance of wireless sensor networks (WSN) prevent them from a widespread acceptance. In this work, a novel technique to monitor the human activity, based on non-intrusive load monitoring (NILM), is presented. The proposal uses only smart meter data, which leads to minimum intrusiveness and a potential massive deployment at minimal cost. This could be the key to develop sustainable healthcare models for smart homes, capable of complying with the elderly people’ demands. This study also uses the Dempster-Shafer theory to provide a daily score of normality with regard to the regular behavior. This approach has been evaluated using real datasets and, additionally, a benchmarking against a Gaussian mixture model approach is presented. PMID:28208672

Species-Specific Detection of Mycosphaerella polygoni-cuspidati as a Biological Control Agent for Fallopia japonica by PCR Assay.

PubMed

Kurose, Daisuke; Furuya, Naruto; Saeki, Tetsuya; Tsuchiya, Kenichi; Tsushima, Seiya; Seier, Marion K

2016-10-01

The ascomycete fungus Mycosphaerella polygoni-cuspidati has been undergoing evaluation as a potential classical biological control agent for the invasive weed Fallopia japonica (Japanese knotweed), which has become troublesome in Europe and North America. In advance of the potential release of a biocontrol agent into a new environment, it is crucial to develop an effective monitoring system to enable the evaluation of agent establishment and dispersal within the target host population, as well as any potential attacks on non-target species. Therefore, a primer pair was designed for direct, rapid, and specific detection of the Japanese knotweed pathogen M. polygoni-cuspidati based on the sequences of the internal transcribed spacer regions including the 5.8S rDNA. A PCR product of approximately 298 bp was obtained only when the DNA extracted from mycelial fragments of M. polygoni-cuspidati was used. The lower limit of detection of the PCR method was 100 fg of genomic DNA. Using the specific primer pair, M. polygoni-cuspidati could be detected from both naturally and artificially infected Japanese knotweed plants. No amplification was observed for other Mycosphaerella spp. or fungal endophytes isolated from F. japonica. The designed primer pair is thus effective for the specific detection of M. polygoni-cuspidati in planta.

Miniaturized low-cost ion mobility spectrometer for fast detection of chemical warfare agents.

PubMed

Zimmermann, Stefan; Barth, Sebastian; Baether, Wolfgang K M; Ringer, Joachim

2008-09-01

Ion mobility spectrometry (IMS) is a well-known method for detecting hazardous compounds in air. Typical applications are the detection of chemical warfare agents, highly toxic industrial compounds, explosives, and drugs of abuse. Detection limits in the low part per billion range, fast response times, and simple instrumentation make this technique more and more popular. In particular, there is an increasing demand for miniaturized low-cost IMS for hand-held devices and air monitoring of public areas by sensor networks. In this paper, we present a miniaturized aspiration condenser type ion mobility spectrometer for fast detection of chemical warfare agents. The device is easy to manufacture and allows single substance identification down to low part per billion-level concentrations within seconds. The improved separation power results from ion focusing by means of geometric constraints and fluid dynamics. A simple pattern recognition algorithm is used for the identification of trained substances in air. The device was tested at the German Armed Forces Scientific Institute for Protection Technologies-NBC-Protection. Different chemical warfare agents, such as sarin, tabun, soman, US-VX, sulfur mustard, nitrogen mustard, and lewisite were tested. The results are presented here.

Sensitive and comprehensive detection of chemical warfare agents in air by atmospheric pressure chemical ionization ion trap tandem mass spectrometry with counterflow introduction.

PubMed

Seto, Yasuo; Sekiguchi, Hiroshi; Maruko, Hisashi; Yamashiro, Shigeharu; Sano, Yasuhiro; Takayama, Yasuo; Sekioka, Ryoji; Yamaguchi, Shintaro; Kishi, Shintaro; Satoh, Takafumi; Sekiguchi, Hiroyuki; Iura, Kazumitsu; Nagashima, Hisayuki; Nagoya, Tomoki; Tsuge, Kouichiro; Ohsawa, Isaac; Okumura, Akihiko; Takada, Yasuaki; Ezawa, Naoya; Watanabe, Susumu; Hashimoto, Hiroaki

2014-05-06

A highly sensitive and specific real-time field-deployable detection technology, based on counterflow air introduction atmospheric pressure chemical ionization, has been developed for a wide range of chemical warfare agents (CWAs) comprising gaseous (two blood agents, three choking agents), volatile (six nerve gases and one precursor agent, five blister agents), and nonvolatile (three lachrymators, three vomiting agents) agents in air. The approach can afford effective chemical ionization, in both positive and negative ion modes, for ion trap multiple-stage mass spectrometry (MS(n)). The volatile and nonvolatile CWAs tested provided characteristic ions, which were fragmented into MS(3) product ions in positive and negative ion modes. Portions of the fragment ions were assigned by laboratory hybrid mass spectrometry (MS) composed of linear ion trap and high-resolution mass spectrometers. Gaseous agents were detected by MS or MS(2) in negative ion mode. The limits of detection for a 1 s measurement were typically at or below the microgram per cubic meter level except for chloropicrin (submilligram per cubic meter). Matrix effects by gasoline vapor resulted in minimal false-positive signals for all the CWAs and some signal suppression in the case of mustard gas. The moisture level did influence the measurement of the CWAs.

A new physical barrier system for seawater intrusion control

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Evolutionary game theory using agent-based methods.

PubMed

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Improved agar diffusion method for detecting residual antimicrobial agents.

PubMed

Tsai, C E; Kondo, F

2001-03-01

The improved agar diffusion method for determination of residual antimicrobial agents was investigated, and the sensitivities of various combinations of test organisms and assay media were determined using 7 organisms, 5 media, and 31 antimicrobial agents. Bacillus stearothermophilus and synthetic assay medium (SAM) showed the greatest sensitivity for screening penicillins (penicillin G and ampicillin). The combination of Bacillus subtilis and minimum medium (MM) was the most sensitive for tetracyclines (oxytetracycline and chlortetracycline), B. stearothermophilus and SAM or Micrococcus luteus and Mueller-Hinton agar (MHA) for detecting tylosin and erythromycin, B. subtilis and MHA for aminoglycosides (streptomycin, kanamycin, gentamicin, and dihydrostreptomycin), B. stearothermophilus and SAM for polyethers (salinomycin and lasalocid), and B. subtilis and MM or Clostridium perfringens and GAM for polypeptides (thiopeptin, enramycin, virginiamycin, and bacitracin). However, gram-negative bacterium Escherichia coli ATCC 27166 and MM were better for screening for colistin and polymixin-B. For detecting the synthetic drugs tested, the best combination was B. subtilis and MM for sulfonamides, E. coli 27166 and MM for quinolones (oxolinic acid and nalidixic acid), B. subtilis and MM for furans (furazolidone), and the bioluminescent bacterium Photobacterium phosphoreum and luminescence assay medium for chloramphenicol and oxolinic acid. The results showed that the use of four assay plates, B. stearothermophilus and SAM, B. subtilis and MM, M. luteus and MHA, and E. coli 27166 and MM, was superior to the currently available techniques for screening for residual antimicrobial agents in edible animal tissues.

Nanodiamond-Manganese dual mode MRI contrast agents for enhanced liver tumor detection.

PubMed

Hou, Weixin; Toh, Tan Boon; Abdullah, Lissa Nurrul; Yvonne, Tay Wei Zheng; Lee, Kuan J; Guenther, Ilonka; Chow, Edward Kai-Hua

2017-04-01

Contrast agent-enhanced magnetic resonance (MR) imaging is critical for the diagnosis and monitoring of a number of diseases, including cancer. Certain clinical applications, including the detection of liver tumors, rely on both T1 and T2-weighted images even though contrast agent-enhanced MR imaging is not always reliable. Thus, there is a need for improved dual mode contrast agents with enhanced sensitivity. We report the development of a nanodiamond-manganese dual mode contrast agent that enhanced both T1 and T2-weighted MR imaging. Conjugation of manganese to nanodiamonds resulted in improved longitudinal and transverse relaxivity efficacy over unmodified MnCl 2 as well as clinical contrast agents. Following intravenous administration, nanodiamond-manganese complexes outperformed current clinical contrast agents in an orthotopic liver cancer mouse model while also reducing blood serum concentration of toxic free Mn 2+ ions. Thus, nanodiamond-manganese complexes may serve as more effective dual mode MRI contrast agent, particularly in cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Young women's experiences of intrusive behavior in 12 countries.

PubMed

Sheridan, Lorraine; Scott, Adrian J; Roberts, Karl

2016-01-01

The present study provides international comparisons of young women's (N = 1,734) self-reported experiences of intrusive activities enacted by men. Undergraduate psychology students from 12 countries (Armenia, Australia, England, Egypt, Finland, India, Indonesia, Italy, Japan, Portugal, Scotland, and Trinidad) indicated which of 47 intrusive activities they had personally experienced. Intrusive behavior was not uncommon overall, although large differences were apparent between countries when women's personal experiences of specific intrusive activities were compared. Correlations were carried out between self-reported intrusive experiences, the Gender Empowerment Measure (GEM), and Hofstede's dimensions of national cultures. The primary associations were between women's experiences of intrusive behavior and the level of power they are afforded within the 12 countries. Women from countries with higher GEM scores reported experiencing more intrusive activities relating to courtship and requests for sex, while the experiences of women from countries with lower GEM scores related more to monitoring and ownership. Intrusive activities, many of them constituent of harassment and stalking, would appear to be widespread and universal, and their incidence and particular form reflect national level gender inequalities. © 2015 Wiley Periodicals, Inc.

New method for comprehensive detection of chemical warfare agents using an electron-cyclotron-resonance ion-source mass spectrometer

NASA Astrophysics Data System (ADS)

Kidera, Masanori; Seto, Yasuo; Takahashi, Kazuya; Enomoto, Shuichi; Kishi, Shintaro; Makita, Mika; Nagamatsu, Tsuyoshi; Tanaka, Tatsuhiko; Toda, Masayoshi

2011-03-01

We developed a detection technology for vapor forms of chemical warfare agents (CWAs) with an element analysis system using an electron cyclotron resonance ion source. After the vapor sample was introduced directly into the ion source, the molecular material was decomposed into elements using electron cyclotron resonance plasma and ionized. The following CWAs and stimulants were examined: diisopropyl fluorophosphonate (DFP), 2-chloroethylethylsulfide (2CEES), cyanogen chloride (CNCl), and hydrogen cyanide (HCN). The type of chemical warfare agents, specifically, whether it was a nerve agent, blister agent, blood agent, or choking agent, could be determined by measuring the quantities of the monatomic ions or CN + using mass spectrometry. It was possible to detect gaseous CWAs that could not be detected by a conventional mass spectrometer. The distribution of electron temperature in the plasma could be closely controlled by adjusting the input power of the microwaves used to generate the electron cyclotron resonance plasma, and the target compounds could be detected as molecular ions or fragment ions, enabling identification of the target agents.

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.

Agent Based Modeling Applications for Geosciences

NASA Astrophysics Data System (ADS)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

Motion-based video monitoring for early detection of livestock diseases: The case of African swine fever

PubMed Central

Martínez-Avilés, Marta; Ivorra, Benjamin; Martínez-López, Beatriz; Ramos, Ángel Manuel; Sánchez-Vizcaíno, José Manuel

2017-01-01

Early detection of infectious diseases can substantially reduce the health and economic impacts on livestock production. Here we describe a system for monitoring animal activity based on video and data processing techniques, in order to detect slowdown and weakening due to infection with African swine fever (ASF), one of the most significant threats to the pig industry. The system classifies and quantifies motion-based animal behaviour and daily activity in video sequences, allowing automated and non-intrusive surveillance in real-time. The aim of this system is to evaluate significant changes in animals’ motion after being experimentally infected with ASF virus. Indeed, pig mobility declined progressively and fell significantly below pre-infection levels starting at four days after infection at a confidence level of 95%. Furthermore, daily motion decreased in infected animals by approximately 10% before the detection of the disease by clinical signs. These results show the promise of video processing techniques for real-time early detection of livestock infectious diseases. PMID:28877181

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.…

Cultural syndromes and age moderate the emotional impact of illness intrusiveness in rheumatoid arthritis.

PubMed

Devins, Gerald M; Gupta, Anita; Cameron, Jill; Woodend, Kirsten; Mah, Kenneth; Gladman, Dafna

2009-02-01

The authors investigated cultural syndromes (multidimensional vectors comprising culturally based attitudes, values, and beliefs) and age as moderators of the emotional impact of illness intrusiveness--illness-induced lifestyle disruptions--in rheumatoid arthritis (RA) and examined illness intrusiveness effects in total and separately for three life domains (relationships and personal development, intimacy, and instrumental). People with RA (n = 105) completed the Illness Intrusiveness Ratings, Individualism-Collectivism, and Center for Epidemiologic Studies--Depression scales in a one-on-one interview. Controlling for disease and background characteristics, the association between illness intrusiveness (total score and the Relationships and Personal Development subscale) and distress was inverse when young adults with RA endorsed high horizontal individualism. Illness intrusiveness into intimacy was associated with increased distress, and this intensified when respondents endorsed high vertical individualism, horizontal collectivism, vertical collectivism, or low horizontal individualism. The negative emotional impact of illness intrusiveness into intimacy diminished with increasing age. Given an aging and increasingly pluralistic society, diversity can no longer be ignored in addressing the psychosocial impact of chronic, disabling disease.

Fracturing of doleritic intrusions and associated contact zones: Implications for fluid flow in volcanic basins

NASA Astrophysics Data System (ADS)

Senger, Kim; Buckley, Simon J.; Chevallier, Luc; Fagereng, Åke; Galland, Olivier; Kurz, Tobias H.; Ogata, Kei; Planke, Sverre; Tveranger, Jan

2015-02-01

Igneous intrusions act as both carriers and barriers to subsurface fluid flow and are therefore expected to significantly influence the distribution and migration of groundwater and hydrocarbons in volcanic basins. Given the low matrix permeability of igneous rocks, the effective permeability in- and around intrusions is intimately linked to the characteristics of their associated fracture networks. Natural fracturing is caused by numerous processes including magma cooling, thermal contraction, magma emplacement and mechanical disturbance of the host rock. Fracturing may be locally enhanced along intrusion-host rock interfaces, at dyke-sill junctions, or at the base of curving sills, thereby potentially enhancing permeability associated with these features. In order to improve our understanding of fractures associated with intrusive bodies emplaced in sedimentary host rocks, we have investigated a series of outcrops from the Karoo Basin of the Eastern Cape province of South Africa, where the siliciclastic Burgersdorp Formation has been intruded by various intrusions (thin dykes, mid-sized sheet intrusions and thick sills) belonging to the Karoo dolerite. We present a quantified analysis of fracturing in- and around these igneous intrusions based on five outcrops at three individual study sites, utilizing a combination of field data, high-resolution lidar virtual outcrop models and image processing. Our results show a significant difference between the three sites in terms of fracture orientation. The observed differences can be attributed to contrasting intrusion geometries, outcrop geometry (for lidar data) and tectonic setting. Two main fracture sets were identified in the dolerite at two of the sites, oriented parallel and perpendicular to the contact respectively. Fracture spacing was consistent between the three sites, and exhibits a higher degree of variation in the dolerites compared to the host rock. At one of the study sites, fracture frequency in the

A new interpretation of the structure of the Sept Iles Intrusive suite, Canada

NASA Astrophysics Data System (ADS)

Higgins, Michael D.

2005-08-01

The layered mafic intrusion at Sept Iles, Canada, is one of the largest intrusions in the world. A new interpretation of its structure is proposed, based on a review of its geology and a comparison with the Skaergaard intrusion, Greenland. Several different magmatic components are recognized; hence the name Sept Iles Intrusive suite (SIIS) is proposed. Emplacement of the suite may have been preceded by eruption of flood basalts. The first magmas of the suite rose in the crust to accumulate beneath the density filter afforded by the basalts. The largest component is the Sept Iles Mafic intrusion (SIMI). The Lower series of the SIMI is dominated by leucotroctolites and leucogabbros. Above it lie the Layered series, which is largely comprised of gabbro and troctolite. Both these units are unchanged from earlier interpretations. The anorthosites (s.l.), gabbros and monzogabbros, formerly called the Transitional series, are now considered to be the Upper Border series, developed by floatation of plagioclase. Common autoliths in the Layered series are parts of the hydrothermally altered Upper Border series from towards the interior of the intrusion, which have foundered and settled through the magma. The contamination of the magma that accompanied this event oxidised iron in the magma and led to the precipitation of magnetite around the periphery of the intrusion. The subsequent depletion of Fe 3+ and/or increase in SiO 2, CaO and P 2O 5 may have induced apatite saturation and accumulation to form two layers rich in apatite, near the base and at top of the Layered series. Granitic magma was developed by fractional crystallisation and was emplaced along the roof of the chamber, where it acquired large quantities of xenoliths. These were probably derived from the flood basalts, their evolved members and fragments of mafic dykes chilled by the granitic magma. Accumulations of monzonite pillows in this unit testify to another magmatic event and a floor to the granitic magma

Melanin-Based Contrast Agents for Biomedical Optoacoustic Imaging and Theranostic Applications.

PubMed

Longo, Dario Livio; Stefania, Rachele; Aime, Silvio; Oraevsky, Alexander

2017-08-07

Optoacoustic imaging emerged in early 1990s as a new biomedical imaging technology that generates images by illuminating tissues with short laser pulses and detecting resulting ultrasound waves. This technique takes advantage of the spectroscopic approach to molecular imaging, and delivers high-resolution images in the depth of tissue. Resolution of the optoacoustic imaging is scalable, so that biomedical systems from cellular organelles to large organs can be visualized and, more importantly, characterized based on their optical absorption coefficient, which is proportional to the concentration of absorbing chromophores. Optoacoustic imaging was shown to be useful in both preclinical research using small animal models and in clinical applications. Applications in the field of molecular imaging offer abundant opportunities for the development of highly specific and effective contrast agents for quantitative optoacoustic imaging. Recent efforts are being made in the direction of nontoxic biodegradable contrast agents (such as nanoparticles made of melanin) that are potentially applicable in clinical optoacoustic imaging. In order to increase the efficiency and specificity of contrast agents and probes, they need to be made smart and capable of controlled accumulation in the target cells. This review was written in recognition of the potential breakthroughs in medical optoacoustic imaging that can be enabled by efficient and nontoxic melanin-based optoacoustic contrast agents.

Melanin-Based Contrast Agents for Biomedical Optoacoustic Imaging and Theranostic Applications

PubMed Central

Longo, Dario Livio; Aime, Silvio

2017-01-01

Optoacoustic imaging emerged in early 1990s as a new biomedical imaging technology that generates images by illuminating tissues with short laser pulses and detecting resulting ultrasound waves. This technique takes advantage of the spectroscopic approach to molecular imaging, and delivers high-resolution images in the depth of tissue. Resolution of the optoacoustic imaging is scalable, so that biomedical systems from cellular organelles to large organs can be visualized and, more importantly, characterized based on their optical absorption coefficient, which is proportional to the concentration of absorbing chromophores. Optoacoustic imaging was shown to be useful in both preclinical research using small animal models and in clinical applications. Applications in the field of molecular imaging offer abundant opportunities for the development of highly specific and effective contrast agents for quantitative optoacoustic imaging. Recent efforts are being made in the direction of nontoxic biodegradable contrast agents (such as nanoparticles made of melanin) that are potentially applicable in clinical optoacoustic imaging. In order to increase the efficiency and specificity of contrast agents and probes, they need to be made smart and capable of controlled accumulation in the target cells. This review was written in recognition of the potential breakthroughs in medical optoacoustic imaging that can be enabled by efficient and nontoxic melanin-based optoacoustic contrast agents. PMID:28783106

Rapid laccolith intrusion driven by explosive volcanic eruption

PubMed Central

Castro, Jonathan M.; Cordonnier, Benoit; Schipper, C. Ian; Tuffen, Hugh; Baumann, Tobias S.; Feisel, Yves

2016-01-01

Magmatic intrusions and volcanic eruptions are intimately related phenomena. Shallow magma intrusion builds subsurface reservoirs that are drained by volcanic eruptions. Thus, the long-held view is that intrusions must precede and feed eruptions. Here we show that explosive eruptions can also cause magma intrusion. We provide an account of a rapidly emplaced laccolith during the 2011 rhyolite eruption of Cordón Caulle, Chile. Remote sensing indicates that an intrusion began after eruption onset and caused severe (>200 m) uplift over 1 month. Digital terrain models resolve a laccolith-shaped body ∼0.8 km3. Deformation and conduit flow models indicate laccolith depths of only ∼20–200 m and overpressures (∼1–10 MPa) that likely stemmed from conduit blockage. Our results show that explosive eruptions may rapidly force significant quantities of magma in the crust to build laccoliths. These iconic intrusions can thus be interpreted as eruptive features that pose unique and previously unrecognized volcanic hazards. PMID:27876800

Effects of intrusions on grades and contents of gold and other metals in volcanogenic massive sulfide deposits

USGS Publications Warehouse

Singer, Donald A.; Berger, Vladimir; Mosier, Dan L.

2011-01-01

The reason some VMS deposits contain more gold or other metals than others might be due to the influence of intrusions. A new approach examining this possibility is based on examining the information about many VMS deposits to test statistically if those with associated intrusions have significantly different grades or amounts of metals. A set of 632 VMS deposits with reported grades, tonnages, and information about the observed presence or absence of subvolcanic or plutonic intrusive bodies emplaced at or after VMS mineralization is statistically analyzed.Deposits with syn-mineralization or post-mineralization intrusions nearby have higher tonnages than deposits without reported intrusions, but the differences are not statistically significant. When both kinds of intrusions are reported, VMS deposit sizes are significantly higher than in the deposits without any intrusions. Gold, silver, zinc, lead, and copper average grades are not significantly different in the VMS deposits with nearby intrusions compared to deposits without regardless of relative age of intrusive. Only zinc and copper contents are significantly higher in VMS deposits with both kinds of intrusive reported. These differences in overall metal content are due to significantly larger deposit sizes of VMS deposits where both intrusive kinds are observed and reported, rather than any difference in metal grades.

Multi-issue Agent Negotiation Based on Fairness

NASA Astrophysics Data System (ADS)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

Natural tooth intrusion and reversal in implant-assisted prosthesis: evidence of and a hypothesis for the occurrence.

PubMed

Sheets, C G; Earthmann, J C

1993-12-01

Based on clinical observation, a hypothesis of the mechanism of intrusion of natural teeth in an implant-assisted prosthesis is suggested. Engineering principles are presented that establish an energy absorption model as it relates to the implant-assisted prosthesis. In addition, in the course of patient treatment it has been discovered that the intrusion of natural teeth can be reversed. Patient histories that demonstrate intrusion reversal are reviewed. The possible mechanisms for the intrusion/reversal phenomenon are presented and preventative recommendations are given.

Fluorescence/depolarization lidar for mid-range stand-off detection of biological agents

NASA Astrophysics Data System (ADS)

Mierczyk, Z.; Kopczyński, K.; Zygmunt, M.; Wojtanowski, J.; Młynczak, J.; Gawlikowski, A.; Młodzianko, A.; Piotrowski, W.; Gietka, A.; Knysak, P.; Drozd, T.; Muzal, M.; Kaszczuk, M.; Ostrowski, R.; Jakubaszek, M.

2011-06-01

LIDAR system for real-time standoff detection of bio-agents is presented and preliminary experimental results are discussed. The detection approach is based on two independent physical phenomena: (1) laser induced fluorescence (LIF), (2) depolarization resulting from elastic scattering on non-spherical particles. The device includes three laser sources, two receiving telescopes, depolarization component and spectral signature analyzing spectrograph. It was designed to provide the stand-off detection capability at ranges from 200 m up to several kilometers. The system as a whole forms a mobile platform for vehicle or building installation. Additionally, it's combined with a scanning mechanics and advanced software, which enable to conduct the semi-automatic monitoring of a specified space sector. For fluorescence excitation, 3-rd (355 nm) and 4-th (266 nm) harmonics of Nd:YAG pulsed lasers are used. They emit short (~6 ns) pulses with the repetition rate of 20 Hz. Collecting optics for fluorescence echo detection and spectral content analysis includes 25 mm diameter f/4 Newton telescope, Czerny Turner spectrograph and 32-channel PMT. Depending on the grating applied, the spectral resolution from 20 nm up to 3 nm per channel can be achieved. The system is also equipped with an eye-safe (1.5 μm) Nd:YAG OPO laser for elastic backscattering/depolarization detection. The optical echo signal is collected by Cassegrain telescope with aperture diameter of 12.5 mm. Depolarization detection component based on polarizing beam-splitter serves as the stand-off particle-shape analyzer, which is very valuable in case of non-spherical bio-aerosols sensing.

An Agent-Based Cockpit Task Management System

NASA Technical Reports Server (NTRS)

Funk, Ken

1997-01-01

An agent-based program to facilitate Cockpit Task Management (CTM) in commercial transport aircraft is developed and evaluated. The agent-based program called the AgendaManager (AMgr) is described and evaluated in a part-task simulator study using airline pilots.

Nano-sized Contrast Agents to Non-Invasively Detect Renal Inflammation by Magnetic Resonance Imaging

PubMed Central

Thurman, Joshua M.; Serkova, Natalie J.

2013-01-01

Several molecular imaging methods have been developed that employ nano-sized contrast agents to detect markers of inflammation within tissues. Renal inflammation contributes to disease progression in a wide range of autoimmune and inflammatory diseases, and a biopsy is currently the only method of definitively diagnosing active renal inflammation. However, the development of new molecular imaging methods that employ contrast agents capable of detecting particular immune cells or protein biomarkers will allow clinicians to evaluate inflammation throughout the kidneys, and to assess a patient's response to immunomodulatory drugs. These imaging tools will improve our ability to validate new therapies and to optimize the treatment of individual patients with existing therapies. This review describes the clinical need for new methods of monitoring renal inflammation, and recent advances in the development of nano-sized contrast agents for detection of inflammatory markers of renal disease. PMID:24206601

Assessment of groundwater vulnerability to anthropogenic pollution and seawater intrusion in a small tropical island using index-based methods.

PubMed

Kura, Nura Umar; Ramli, Mohammad Firuz; Ibrahim, Shaharin; Sulaiman, Wan Nor Azmin; Aris, Ahmad Zaharin; Tanko, Adamu Idris; Zaudi, Muhammad Amar

2015-01-01

In this work, the DRASTIC and GALDIT models were employed to determine the groundwater vulnerability to contamination from anthropogenic activities and seawater intrusion in Kapas Island. In addition, the work also utilized sensitivity analysis to evaluate the influence of each individual parameter used in developing the final models. Based on these effects and variation indices of the said parameters, new effective weights were determined and were used to create modified DRASTIC and GALDIT models. The final DRASTIC model classified the island into five vulnerability classes: no risk (110-140), low (140-160), moderate (160-180), high (180-200), and very high (>200), covering 4, 26, 59, 4, and 7 % of the island, respectively. Likewise, for seawater intrusion, the modified GALDIT model delineates the island into four vulnerability classes: very low (<90), low (90-110), moderate (110-130), and high (>130) covering 39, 33, 18, and 9 % of the island, respectively. Both models show that the areas that are likely to be affected by anthropogenic pollution and seawater intrusion are within the alluvial deposit at the western part of the island. Pearson correlation was used to verify the reliability of the two models in predicting their respective contaminants. The correlation matrix showed a good relationship between DRASTIC model and nitrate (r = 0.58). In a similar development, the correlation also reveals a very strong negative relationship between GALDIT model and seawater contaminant indicator (resistivity Ωm) values (r = -0.86) suggesting that the model predicts more than 86 % of seawater intrusion. In order to facilitate management strategy, suitable areas for artificial recharge were identified through modeling. The result suggested some areas within the alluvial deposit at the western part of the island as suitable for artificial recharge. This work can serve as a guide for a full vulnerability assessment to anthropogenic pollution and seawater intrusion

Vapor Intrusion Characterization Report (Revision 1.0)

EPA Pesticide Factsheets

Vapor Intrusion Characterization Report (Revision 1) - February 5, 2015: This report, which was approved by the EPA on February 18, 2015, documents the results from implementation of the Final Vapor Intrusion Characterization Work Plan.

Accounting for intrusive thoughts in PTSD: Contributions of cognitive control and deliberate regulation strategies.

PubMed

Bomyea, Jessica; Lang, Ariel J

2016-03-01

Persistent, trauma-related intrusive thoughts are common in individuals with posttraumatic stress disorder (PTSD). Automatic aspects of cognitive functioning (including executive functioning) and maladaptive deliberate attempts at cognitive regulation have been proposed as individual difference factors that may perpetuate intrusive thoughts. The current study sought to examine the joint contribution of these two factors on intrusive thoughts in PTSD. Forty-two women with PTSD completed an executive functioning assessment followed by a thought suppression task. Intrusive thoughts (frequency and duration), as well as participants' use of specific cognitive regulation strategies (avoidance-based thought regulation strategies; TRS), were measured during the task. Hierarchical linear regression was used to examine the interaction of executive functioning and TRS on intrusive thoughts. Greater use of TRS was associated with greater intrusive thought persistence for those with low executive functioning, but not those with high executive functioning. Data was collected cross-sectionally and the laboratory thought suppression task may not correspond to naturalistic thought regulation. Results are consistent with prior literature suggesting that certain responses deployed by individuals to control intrusive thoughts may be unhelpful, but that a higher level of cognitive capacity may mitigate this effect. Implications of these findings for recent models of cognition in PTSD are discussed. Published by Elsevier B.V.

Intrusive Memories of Distressing Information: An fMRI Study

PubMed Central

Battaglini, Eva; Liddell, Belinda; Das, Pritha; Malhi, Gin; Felmingham, Kim

2016-01-01

Although intrusive memories are characteristic of many psychological disorders, the neurobiological underpinning of these involuntary recollections are largely unknown. In this study we used functional magentic resonance imaging (fMRI) to identify the neural networks associated with encoding of negative stimuli that are subsequently experienced as intrusive memories. Healthy partipants (N = 42) viewed negative and neutral images during a visual/verbal processing task in an fMRI context. Two days later they were assessed on the Impact of Event Scale for occurrence of intrusive memories of the encoded images. A sub-group of participants who reported significant intrusions (n = 13) demonstrated stronger activation in the amygdala, bilateral ACC and parahippocampal gyrus during verbal encoding relative to a group who reported no intrusions (n = 13). Within-group analyses also revealed that the high intrusion group showed greater activity in the dorsomedial (dmPFC) and dorsolateral prefrontal cortex (dlPFC), inferior frontal gyrus and occipital regions during negative verbal processing compared to neutral verbal processing. These results do not accord with models of intrusions that emphasise visual processing of information at encoding but are consistent with models that highlight the role of inhibitory and suppression processes in the formation of subsequent intrusive memories. PMID:27685784

Agent Based Fault Tolerance for the Mobile Environment

NASA Astrophysics Data System (ADS)

Park, Taesoon

This paper presents a fault-tolerance scheme based on mobile agents for the reliable mobile computing systems. Mobility of the agent is suitable to trace the mobile hosts and the intelligence of the agent makes it efficient to support the fault tolerance services. This paper presents two approaches to implement the mobile agent based fault tolerant service and their performances are evaluated and compared with other fault-tolerant schemes.

Optical detection of chemical warfare agents and toxic industrial chemicals

NASA Astrophysics Data System (ADS)

Webber, Michael E.; Pushkarsky, Michael B.; Patel, C. Kumar N.

2004-12-01

We present an analytical model evaluating the suitability of optical absorption based spectroscopic techniques for detection of chemical warfare agents (CWAs) and toxic industrial chemicals (TICs) in ambient air. The sensor performance is modeled by simulating absorption spectra of a sample containing both the target and multitude of interfering species as well as an appropriate stochastic noise and determining the target concentrations from the simulated spectra via a least square fit (LSF) algorithm. The distribution of the LSF target concentrations determines the sensor sensitivity, probability of false positives (PFP) and probability of false negatives (PFN). The model was applied to CO2 laser based photoacosutic (L-PAS) CWA sensor and predicted single digit ppb sensitivity with very low PFP rates in the presence of significant amount of interferences. This approach will be useful for assessing sensor performance by developers and users alike; it also provides methodology for inter-comparison of different sensing technologies.

The practice of agent-based model visualization.

PubMed

Dorin, Alan; Geard, Nicholas

2014-01-01

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

Different blocking agents cause variation in the immunologic detection of proteins transferred to nitrocellulose membranes.

PubMed

Spinola, S M; Cannon, J G

1985-07-16

We compared bovine serum albumin, commercial non-fat dry milk, and Tween 20 as blocking agents for immunologic probing of bacterial proteins transferred to nitrocellulose sheets. There were quantitative and qualitative differences in antigens detected that depended on which blocking agents were used. We suggest that several methods for blocking and washing nitrocellulose should be compared when Western blotting is used to detect immunologically reactive proteins.

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

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

NASA Astrophysics Data System (ADS)

Hao, Xiaohong; Zhang, Xiaofeng

2018-01-01

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

Development and Application of a Three-Dimensional Finite Element Vapor Intrusion Model

PubMed Central

Pennell, Kelly G.; Bozkurt, Ozgur; Suuberg, Eric M.

2010-01-01

Details of a three-dimensional finite element model of soil vapor intrusion, including the overall modeling process and the stepwise approach, are provided. The model is a quantitative modeling tool that can help guide vapor intrusion characterization efforts. It solves the soil gas continuity equation coupled with the chemical transport equation, allowing for both advective and diffusive transport. Three-dimensional pressure, velocity, and chemical concentration fields are produced from the model. Results from simulations involving common site features, such as impervious surfaces, porous foundation sub-base material, and adjacent structures are summarized herein. The results suggest that site-specific features are important to consider when characterizing vapor intrusion risks. More importantly, the results suggest that soil gas or subslab gas samples taken without proper regard for particular site features may not be suitable for evaluating vapor intrusion risks; rather, careful attention needs to be given to the many factors that affect chemical transport into and around buildings. PMID:19418819

Differential mobility spectroscopy for chemical agent detection

NASA Astrophysics Data System (ADS)

Griffin, M. Todd

2006-05-01

General Dynamics ATP (GDATP) and Sionex Corporation (Sionex) are carrying out a cooperative development for a handheld chemical agent detector, being called JUNO TM, which will have lower false positives, higher sensitivity, and improved interference rejection compared with presently available detectors. This enhanced performance is made possible by the use of a new principle of ion separation called Differential Mobility Spectrometry (DMS). The enhanced selectivity is provided by the field tunable nature of the Sionex differential mobility technology (microDMxTM) which forms the analytical heart of the JUNO system and enables fingerprinting of molecules by characterization of the ionized molecular behavior under multiple electric field conditions. This enhanced selectivity is valuable in addressing not only the traditional list of chemical warfare agents (CWA) but also the substantial list of Toxic Industrial Compounds (TICs) and Toxic Industrial Materials (TIMs) which may be released in warfare or terrorist situations. Experimental results showing the ability of the microDMx to reject interferences, detect and resolve live agents are presented. An additional breakthrough in the technology was realized by operating the device at a reduced pressure of around 0.5 atmospheres. This reduced pressure operation resulted in roughly doubling the spectrometers resolution over what has previously been reported [1]. Advances have also been made in power consumption and packaging leading to a device suitable for portable, handheld, applications. Experimental results illustrating the performance of the microDMx technology employed in JUNO are highlighted.

Technological advancements for the detection of and protection against biological and chemical warfare agents.

PubMed

Eubanks, Lisa M; Dickerson, Tobin J; Janda, Kim D

2007-03-01

There is a growing need for technological advancements to combat agents of chemical and biological warfare, particularly in the context of the deliberate use of a chemical and/or biological warfare agent by a terrorist organization. In this tutorial review, we describe methods that have been developed both for the specific detection of biological and chemical warfare agents in a field setting, as well as potential therapeutic approaches for treating exposure to these toxic species. In particular, nerve agents are described as a typical chemical warfare agent, and the two potent biothreat agents, anthrax and botulinum neurotoxin, are used as illustrative examples of potent weapons for which countermeasures are urgently needed.

Attenuating fearful memories: effect of cued extinction on intrusions.

PubMed

Marks, Elizabeth H; Zoellner, Lori A

2014-12-01

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

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.

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

USGS Publications Warehouse

Francy, Donna S.; Bushon, Rebecca N.; Brady, Amie M.G.; Bertke, Erin E.; Kephart, Christopher M.; Likirdopulos, Christina A.; Mailot, Brian E.; Schaefer, Frank W.; Lindquist, H.D. Alan

2009-01-01

To reduce the impact from a possible bioterrorist attack on drinking-water supplies, analytical methods are needed to rapidly detect the presence of biological agents in water. To this end, 13 drinking-water samples were collected at 9 water-treatment plants in Ohio to assess the performance of a molecular method in comparison to traditional analytical methods that take longer to perform. Two 100-liter samples were collected at each site during each sampling event; one was seeded in the laboratory with six biological agents - Bacillus anthracis (B. anthracis), Burkholderia cepacia (as a surrogate for Bu. pseudomallei), Francisella tularensis (F. tularensis), Salmonella Typhi (S. Typhi), Vibrio cholerae (V. cholerae), and Cryptospordium parvum (C. parvum). The seeded and unseeded samples were processed by ultrafiltration and analyzed by use of quantiative polymerase chain reaction (qPCR), a molecular method, and culture methods for bacterial agents or the immunomagnetic separation/fluorescent antibody (IMS/FA) method for C. parvum as traditional methods. Six replicate seeded samples were also processed and analyzed. For traditional methods, recoveries were highly variable between samples and even between some replicate samples, ranging from below detection to greater than 100 percent. Recoveries were significantly related to water pH, specific conductance, and dissolved organic carbon (DOC) for all bacteria combined by culture methods, but none of the water-quality characteristics tested were related to recoveries of C. parvum by IMS/FA. Recoveries were not determined by qPCR because of problems in quantifying organisms by qPCR in the composite seed. Instead, qPCR results were reported as detected, not detected (no qPCR signal), or +/- detected (Cycle Threshold or 'Ct' values were greater than 40). Several sample results by qPCR were omitted from the dataset because of possible problems with qPCR reagents, primers, and probes. For the remaining 14 qPCR results

Microfluidic chip with optical sensor for rapid detection of nerve agent Sarin in water samples

NASA Astrophysics Data System (ADS)

Tan, Hsih Yin; Nguyen, Nam-Trung; Loke, Weng Keong; Tan, Yong Teng

2007-12-01

The chemical warfare agent Sarin is an organophosphate that is highly toxic to humans as they can act as cholinesterase inhibitors, that disrupts neuromuscular transmission. As these nerve agents are colorless, odorless and highly toxic, they can be introduced into drinking water as a means of terrorist sabotage. Hence, numerous innovative devices and methods have been developed for rapid detection of these organophosphates. Microfluidic technology allows the implementation of fast and sensitive detection of Sarin. In this paper, a micro-total analysis systems (TAS), also known as Lab-on-a-chip, fitted with an optical detection system has been developed to analyze the presence of the nerve agent sarin in water samples. In the present set-up, inhibition of co-introduced cholinesterase and water samples containing trace amounts of nerve agent sarin into the microfluidic device was used as the basis for selective detection of sarin. The device was fabricated using polymeric micromachining with PMMA (poly (methymethacrylate)) as the substrate material. A chromophore was utilized to measure the activity of remnant cholinesterase activity, which is inversely related to the amount of sarin present in the water samples. Comparisons were made between two different optical detection techniques and the findings will be presented in this paper. The presented measurement method is simple, fast and as sensitive as Gas Chromatography.

Development of biosensors for the detection of biological warfare agents: its issues and challenges.

PubMed

Kumar, Harish; Rani, Renu

2013-01-01

This review discusses current development in biosensors for the detection of biological warfare agents (BWAs). BWAs include bacteria, virus and toxins that are added deliberately into air water and food to spread terrorism and cause disease or death. The rapid and unambiguous detection and identification of BWAs with early warning signals for detecting possible biological attack is a major challenge for government agencies particularly military and health. The detection devices--biosensors--can be classified (according to their physicochemical transducers) into four types: electrochemical, nucleic acid, optical and piezoelectric. Advantages and limitations of biosensors are discussed in this review followed by an assessment of the current state of development of different types of biosensors. The research and development in biosensors for biological warfare agent detection is of great interest for the public as well as for governments.

An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

PubMed

Bongiorno, Christian; Miccichè, Salvatore; Mantegna, Rosario N

2017-01-01

We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast.

An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management

PubMed Central

Bongiorno, Christian; Mantegna, Rosario N.

2017-01-01

We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers’ operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast. PMID:28419160

Development of a HIV-1 Virus Detection System Based on Nanotechnology.

PubMed

Lee, Jin-Ho; Oh, Byung-Keun; Choi, Jeong-Woo