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» Using CLIPS to Detect Network Intrusions
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CONEXT
2007
ACM
13 years 9 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
INFOCOM
2006
IEEE
14 years 1 months ago
Contribution of Anomalies Detection and Analysis on Traffic Engineering
—In this paper we present a methodology for detecting traffic anomalies. To accomplish that, and as a demarcation from similar works, we combine multi-scale and multi-criteria an...
Silvia Farraposo, Philippe Owezarski, Edmundo Mont...
ACSAC
2008
IEEE
14 years 2 months ago
The Evolution of System-Call Monitoring
Computer security systems protect computers and networks from unauthorized use by external agents and insiders. The similarities between computer security and the problem of prote...
Stephanie Forrest, Steven A. Hofmeyr, Anil Somayaj...
DASFAA
2008
IEEE
149views Database» more  DASFAA 2008»
13 years 8 months ago
A Test Paradigm for Detecting Changes in Transactional Data Streams
A pattern is considered useful if it can be used to help a person to achieve his goal. Mining data streams for useful patterns is important in many applications. However, data stre...
Willie Ng, Manoranjan Dash
CN
2007
90views more  CN 2007»
13 years 7 months ago
SweetBait: Zero-hour worm detection and containment using low- and high-interaction honeypots
As next-generation computer worms may spread within minutes to millions of hosts, protection via human intervention is no longer an option. We discuss the implementation of SweetB...
Georgios Portokalidis, Herbert Bos