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» Using Active Learning in Intrusion Detection
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ICARIS
2007
Springer
15 years 5 months ago
Towards a Novel Immune Inspired Approach to Temporal Anomaly Detection
Abstract. In this conceptual paper, we report on studies and initial definitions of an immune-inspired approach to temporal anomaly detection problems, where there is a strict temp...
Thiago S. Guzella, Tomaz A. Mota-Santos, Walmir M....
CONEXT
2007
ACM
15 years 18 days ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
CCS
2007
ACM
15 years 5 months ago
Network anomaly detection based on TCM-KNN algorithm
Intrusion detection is a critical component of secure information systems. Network anomaly detection has been an active and difficult research topic in the field of Intrusion Dete...
Yang Li, Binxing Fang, Li Guo, You Chen
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 4 months ago
Evolving computer intrusion scripts for vulnerability assessment and log analysis
Evolutionary computation is used to construct undetectable computer attack scripts. Using a simulated operating system, we show that scripts can be evolved to cover their tracks a...
Julien Budynek, Eric Bonabeau, Ben Shargel
SP
2008
IEEE
134views Security Privacy» more  SP 2008»
15 years 5 months ago
Lares: An Architecture for Secure Active Monitoring Using Virtualization
Host-based security tools such as anti-virus and intrusion detection systems are not adequately protected on today’s computers. Malware is often designed to immediately disable ...
Bryan D. Payne, Martim Carbone, Monirul I. Sharif,...