Detecting novel network attacks with a data field

Authors:
Feng Xie;Shuo Bai
Affiliations:
Software Department, Inst. of Computing Tech., Chinese Academy of Science, Beijing, P.R. China;Software Department, Inst. of Computing Tech., Chinese Academy of Science, Beijing, P.R. China
Venue:
WISI'06 Proceedings of the 2006 international conference on Intelligence and Security Informatics
Year:
2006

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Abstract

With the increased usage of computer networks, network intrusions have greatly threatened the Internet infrastructures. Traditional signature-based intrusion detection often suffers from an ineffectivity to those previously “unseen” attacks. In this paper, we analyze the network intrusions from a new viewpoint based on data field and propose branch and bound tree to lessen computation complexity. Finally, we evaluated our approach over KDD Cup 1999 data set.