12 Resources for

anomaly

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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
IDGraphs: Intrusion Detection and Analysis Using Histographs: Traffic anomalies and attacks are commonplace in today's networks and identifying them rapidly and accurately is critical for large network operators. For a statistical Intrusion Detection System IDS, it is crucial to detect at the flow-level for accurate detection and mitigation. However, existing IDS systems offer only limited support for...; Tags: Network, Northwestern University, Intrusion Detection System, Analysis, Anomaly, IDGraphs, Intrusion Detection, Network Security, Security, Networking; White papers 2008-01-01
Wi-Fi 101: Multipath environments and how they affect Wi-Fi propagation: Ever wonder why moving your computer or changing the direction of your Wi-Fi antenna can make such a difference in signal strength? In this Wi-Fi 101 lesson, I explain how RF signals-especially Wi-Fi ones-react to real world conditions. RF terminology Before I jump into a discussion on multipath...; Tags: Signal, Environment, Propagation, WLAN, Multipath, Anomaly, RF, Propagation Anomaly, Wireless LANs, LANs, Wi-Fi, Wireless, Networking, Michael Kassner; Blog posts 2007-10-18
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
Compatibility Is Not Transparency: VMM Detection Myths and Realities: Recent work on applications ranging from realistic honeypots to stealthier rootkits has speculated about building transparent VMMs - VMMs that are indistinguishable from native hardware, even to a dedicated adversary. This paper surveys anomalies between real and virtual hardware and consider methods for detecting such anomalies, as well as possible...; Tags: Carnegie-Mellon University, Hardware, Anomaly, Rootkits, Security, Spyware, Adware & Malware; White papers 2007-04-12

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
TCP Anomalies: Identification and Analysis: Passive measurements have recently received large attention from the scientific community as a mean, not only for traffic characterization, but also to infer critical protocol behaviors and network working conditions. This paper focuses on passive measurements of TCP traffic, main component of traffic. In particular, it proposes a heuristic technique...; Tags: TCP, Analysis, Anomaly, Tcp/Ip, Networking; White papers 2007-01-01
Passive Identification and Analysis of TCP Anomalies: This paper focuses on passive measurements of TCP traffic, main component of traffic. It proposes a heuristic technique for the classification of the anomalies that may occur during the lifetime of a TCP flow, such as out-of-sequence and duplicate segments. Since TCP is a closed-loop protocol that infers network conditions...; Tags: TCP, Analysis, Anomaly, Tcp/Ip, Networking; White papers 2006-05-03
Firewall Rules Analysis: This paper proposes a method to analyze the firewall policy or rule-set using Relational Algebra and Raining 2D-Box Model. It can discover all the anomalies in the firewall rule-set in the format that is usually used by many firewall products such as Cisco Access Control List, IPTABLES, IPCHAINS and Check...; Tags: Analysis, Anomaly, Firewalls, Network Security, Security, Networking; White papers 2006-05-02
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
Unreal Tournament 2004 Anomaly mod (exe): Anomaly is a futuristic racing mod for Unreal Tournament 2004. With this mod you can race high speed hovercrafts on various custom speedways. You can customize your hovercraft with various weapons and power ups to give you an edge on the competition. Version 0.6 makes several bug fixes to improve...; Tags: Anomaly; Software downloads 2004-10-12
Deciphering Meaning From Early RFID Signals: Many companies in the consumer goods, retail and pharmaceutical markets have moved into the next phases of their RFID initiatives. This phase involves collecting data being generated from across the supply chain as tagged products move past RFID readers. As supply chain executives begin to investigate this data, they typically...; Tags: Supply Chain, Anomaly, RFID, Supply Chain Management (SCM), Wireless, Security, Biometrics, Enterprise Software, Software; Webcasts

Additional Resources

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
Denial of Service and Distributed Denial of Service Protection: To obtain full protection for DoS attacks, organizations typically need to purchase multiple proxy servers, network security devices, intrusion preventions systems, as well as software packages, updates, and expanded licenses as an organization grows. TippingPoint provides the answer in a single system. The TippingPoint IPS is an easy, affordable, and...; Tags: Denial Of Service, Filter, Distributed Denial Of Service, TippingPoint Technologies, TippingPoint IPS, Anomaly Filter, Intrusion Prevention, Security, Network Security, Networking; White papers 2005-04-15
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
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
Detecting Targeted Attacks Using Shadow Honeypots: This paper presents Shadow Honeypots, a novel hybrid architecture that combines the best features of honeypots and anomaly detection. Traffic that is considered anomalous is processed by a 'Shadow honeypot' to determine the accuracy of the anomaly prediction. The shadow is an instance of the protected software that shares all...; Tags: Shadow, Columbia University, Architecture, Attack, Security, Open Source; White papers 2005-05-13
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

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