Analysis and Results of the 1999 DARPA Off-Line Intrusion Detection Evaluation
RAID '00 Proceedings of the Third International Workshop on Recent Advances in Intrusion Detection
Modeling intrusion detection system using hybrid intelligent systems
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
A novel intrusion detection system based on hierarchical clustering and support vector machines
Expert Systems with Applications: An International Journal
Mutual information-based feature selection for intrusion detection systems
Journal of Network and Computer Applications
Decision tree based light weight intrusion detection using a wrapper approach
Expert Systems with Applications: An International Journal
Practical real-time intrusion detection using machine learning approaches
Computer Communications
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The recent research in the wireless network technologies focuses on numerous security threats in a network. Users tend to keep their systems virus free but don't give much focus to online security. The recent trends in intrusion detection have suggested that most of the malicious and abnormal activities can be identified by capturing the network traffic and analyzing them. Many research works in this area address only a particular problem focusing on a network attack or a behavioral pattern of certain kind of worms and Trojans, and propose a solution for that. This gives solution to only a particular type of intrusion detection and leaves the remaining problems apart. There is a need for a kind of system which can handle different types of malicious activities on the wireless local area network. We have developed a traffic analysis tool which focuses on detection of network attacks, fixed signatures, behavioral methods and suspicious packets. Our tool addresses different intrusions pertaining to different detection methods. Its implementation for both LAN and Wireless LAN showed good results on MIT Lincoln DARPA Dataset and also on real time traffic. The scalability of the tool showed it is highly efficient and can be deployed for real time use.