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Agent-Based Network Intrusion Detection System: The paper presents security platform based on agents as an efficient and robust solution for high-performance intrusion detection system designed for deployment on high-speed network links. The proposed detection algorithm is based on extension of trust modeling techniques with representation of uncertain identities, context representation and implicit assumption that significant...; Tags: Network Intrusion Detection System, Network, Agent, Intrusion Detection System, Detection Algorithm, Anomaly Detection Method, Real Estate, Intrusion Detection, Security, Business Operations; White papers 2007-08-17

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Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters: Most current network Intrusion Detection Systems IDSs employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically expensive to produce. Moreover, these methods have difficulty in detecting new types of attack. Using unsupervised anomaly detection techniques, however, the system can be trained...; Tags: Network, Clustering, Australian Computer Society, Network Intrusion Detection, Training, Intrusion Detection, Workforce Management, Training And Certification, Security, Human Resources; White papers 2007-01-01
POSEIDON: A 2-Tier Anomaly-Based Network Intrusion Detection System: Intrusion Detection Systems IDSs were introduced by Anderson and formalized later by Denning. Nowadays, there exist two main types of network intrusion detection methods: anomaly-based and signature-based. In signature-based methods, a characteristic trait of the intrusion is developed off-line, and then loaded in the intrusion database before the system can...; Tags: Network Intrusion Detection System, Network, Intrusion Detection System, Network Intrusion Detection, Anomaly, POSEIDON, Intrusion Detection, Network Security, Security, Networking; White papers 2006-04-01
Kernel Density Estimation for an Anomaly Based Intrusion Detection System: This paper presents a new nonparametric method to simulate probability density functions of some random variables raised in characterizing an Anomaly Based Intrusion Detection System ABIDS. A group of kernel density estimators is constructed and the criterions for bandwidth selection are discussed. In addition, statistical parameters of these distributions are...; Tags: Ohio University, Intrusion Detection System, Research & Development, Intrusion Detection, Network Security, Security, Business Operations, Networking; White papers 2006-04-09
MINDS - Minnesota Intrusion Detection System: This paper introduces the Minnesota Intrusion Detection System MINDS, which uses a suite of data mining techniques to automatically detect attacks against computer networks and systems. While the long-term objective of MINDS is to address all aspects of intrusion detection, this paper focuses on two specific contributions: an unsupervised anomaly...; Tags: Technique, Network, University Of Minnesota, Network Connection, Productivity, Networking; White papers 2008-01-01

Formal Reasoning About Intrusion Detection Systems: Intrusion detection is an appealing approach to improving the security of systems. It involves the runtime gathering of data from system operations, and the subsequent analysis of the data. There are three different kinds of detection models: anomaly detection, misuse detection and specification-based intrusion detection. Anomaly detection compares characteristics of...; Tags: Reasoning Inc., Intrusion Detection System, Specification, Anomaly Detection, Intrusion Detection, Network Security, Security, Networking; White papers 2007-03-01
A Cooperative Intrusion Detection System for Ad Hoc Networks: Mobile Ad hoc NETworking MANET has become an exciting and important technology in recent years because of the rapid proliferation of wireless devices. MANETs are highly vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, lack of centralized monitoring and management point, and lack of...; Tags: Georgia Institute Of Technology, Advertisement, Intrusion Detection System, Attack, MANET, Security; White papers 2008-01-01
Bayesian Event Classification for Intrusion Detection: Intrusion Detection Systems IDSs attempt to identify attacks by comparing collected data to predefined signatures known to be malicious (misuse-based IDSs) or to a model of legal behavior (anomaly-based IDSs). Anomaly-based approaches have the advantage of being able to detect previously unknown attacks, but they suffer from the difficulty of...; Tags: Bayesian, Intrusion Detection System, Anomaly, Intrusion Detection, Network Security, Security, Networking; White papers 2008-01-01
A Bayesian Networks in Intrusion Detection Systems: Intrusion Detection Systems IDSs have been widely used to overcome security threats in computer networks. Anomaly-based approaches have the advantage of being able to detect previously unknown attacks, but they suffer from the difficulty of building robust models of acceptable behaviour which may result in a large number of false...; Tags: Bayesian, Intrusion Detection System, Anomaly, Science Publications, Intrusion Detection, Network Security, Security, Networking; White papers 2007-04-11
An Adaptive Anomaly Detector for Worm Detection: This paper presents an adaptive end-host anomaly detector where a supervised classifier trained as a traffic predictor is used to control a time-varying detection threshold. Training and testing it on real traffic traces collected from a number of end-hosts, it shows the detector dominates an existing fixed threshold detector. This...; Tags: New Jersey, Trace, Performance Management, Workforce Management, Human Resources; White papers 2006-11-29
Anomaly-Based Intrusion Detection in Wireless Networks Using Device and User-Based Profiles: As far as addressing user impersonation, it is feasible to use mobility profiles for Anomaly-Based Intrusion Detection ABID in mobile wireless networks. The challenge is to accurately characterize the mobility behavior of users. One simply strategy, which enhances the characterization of users and increases the detection rate at a minimal...; Tags: Intrusion Detection, Network, Mobility, Wireless Network, Carleton University, Wireless; White papers 2005-09-01
Intrusion Detection Systems and a View to Its Forensic Applications: Traditional computer security has often emphasised prevention, and to a lesser degree, the detection of system security violations. However, it is recognised that the forensic aspect to the overall model of computer security is equally as important. The area of computer forensics lends itself heavily to the response of a...; Tags: Computer Security, University Of Melbourne, Intrusion Detection System, Forensic Application, Computer, Productivity, Intrusion Detection, Network Security, Security, Viruses And Worms, Networking; White papers 2008-01-01
Improving the Efficiency and Robustness of Intrusion Detection Systems: With the increase in the complexity of computer systems, existing security measures are not enough to prevent attacks. Intrusion detection systems have become an integral part of computer security to detect attempted intrusions. Intrusion detection systems need to be fast in order to detect intrusions in real time. Furthermore, intrusion...; Tags: Georgia Institute Of Technology, Intrusion Detection System, Intrusion Detection, Network Security, Security, Networking; White papers 2007-12-01
ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems: This paper presents an architecture1 designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. The technique in this paper is based on a systematic and automatic anomaly-based analysis of the system output, which provides useful context information regarding the network services. The false positives raised by...; Tags: Network Intrusion Detection System, Network, Network Service, Intrusion Detection System, Anomaly, University Of Twente, Intrusion Detection, Network Security, Networking, Security; White papers 2007-09-19
The MINDS - Minnesota Intrusion Detection System: This paper introduces the Minnesota Intrusion Detection System MINDS, which uses a suite of data mining techniques to automatically detect attacks against computer networks and systems. While the long-term objective of MINDS is to address all aspects of intrusion detection, this paper focuses on two specific contributions. First, it shows...; Tags: University Of Minnesota, Data Mining, Productivity, Intrusion Detection, Network Security, Business Intelligence, Networking, Security, Enterprise Software, Software, Data Management; White papers 2008-01-01
Towards NIC-Based Intrusion Detection: This paper presents and evaluates a NIC-based network intrusion detection system. Intrusion detection at the NIC makes the system potentially tamper-proof and is naturally extensible to work in a distributed setting. Simple anomaly detection and signature detection based models have been implemented on the NIC firmware, which has its own...; Tags: Network Interface Card, Networking, Intrusion Detection, Security; White papers 2007-01-01
The Science of Intrusion Detection System: Attack Identification: Among the many vendors of intrusion detection systems IDS, there is marked variation on what constitutes a network intrusion. This has led to many confusing claims by vendors in the IDS market about the best methodologies and solutions. This paper discusses the pros and cons of the various intrusion detection...; Tags: Intrusion Detection System, Cisco Systems Inc., Intrusion Detection, Network Security, Security, Networking; White papers 2003-02-01
Hybrid Intelligent Intrusion Detection System: Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for...; Tags: Network, Intrusion Detection System, Intrusion Detection, Network Security, Productivity, Security, Networking; White papers 2005-06-06
Improved Hybrid Intelligent Intrusion Detection/Prevention System Using AI Technique.: Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for...; Tags: Technique, Network, Intrusion, Universiti Teknologi Malaysia, Intrusion Detection, Productivity, Security, Network Security, Networking; White papers 2007-05-30
Snort (gz): Snort is an open source network intrusion prevention and detection system utilizing a rule-driven language, which combines the benefits of signature, protocol and anomaly based inspection methods. With millions of downloads to date, Snort is the most widely deployed intrusion detection and prevention technology worldwide and has become the de...; Tags: Sourcefire Inc., Snort, Intrusion Prevention, Security; Software downloads 2007-04-28

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