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» Outside the Closed World: On Using Machine Learning for Netw...
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JSS
2002
198views more  JSS 2002»
13 years 5 months ago
Automated discovery of concise predictive rules for intrusion detection
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture...
Guy G. Helmer, Johnny S. Wong, Vasant Honavar, Les...
RAID
2000
Springer
13 years 9 months ago
A Real-Time Intrusion Detection System Based on Learning Program Behavior
Abstract. In practice, most computer intrusions begin by misusing programs in clever ways to obtain unauthorized higher levels of privilege. One e ective way to detect intrusive ac...
Anup K. Ghosh, Christoph C. Michael, Michael Schat...
IDEAL
2010
Springer
13 years 4 months ago
Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection
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 l...
Carsten Elfers, Mirko Horstmann, Karsten Sohr, Ott...
FLAIRS
2003
13 years 6 months ago
LIDS: Learning Intrusion Detection System
The detection of attacks against computer networks is becoming a harder problem to solve in the field of network security. The dexterity of the attackers, the developing technolog...
Mayukh Dass, James Cannady, Walter D. Potter
CONEXT
2007
ACM
13 years 7 months 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