NDLI: A GA-based Solution to an NP-hard Problem of Clustering Security Events

Content Provider	IEEE Xplore Digital Library
Author	Jianxin Wang Hongzhou Wang Geng Zhao
Copyright Year	2006
Description	Author affiliation: Sch. of Inf., Beijing Forestry Univ. (Jianxin Wang)
Abstract	The clustering approach forwarded by Klaus Julisch is considerably effectual in eliminating false positives and finding root causes among huge amount of security events. But the clustering problem was proved to be unfortunately an NP-hard one. In this paper, a GA-based algorithm is forwarded, which is much more effective than the original approximation algorithm by Julisch. The coding scheme and genetic operations including selection, crossover, and mutation are discussed in detail. To validate the quality of the newly-forwarded approach, a tree-version apriori is given, which is quite time-consuming but able to produce absolutely accurate solution used for comparison in a feasible period of time. The results show that the GA-based algorithm is valid and efficient and can find the optimal clusters that are very similar to the absolutely accurate ones
Sponsorship	IEEE Circuits and Syst. Soc. HKUST UESTC City Univ. of Hong Kong
Starting Page	2093
Ending Page	2097
File Size	6182299
Page Count	5
File Format	PDF
ISBN	0780395840
DOI	10.1109/ICCCAS.2006.284911
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	NP-hard problem Data security Genetic mutations Clustering algorithms Intrusion detection Humans Approximation algorithms Encoding Decoding Biological cells
Content Type	Text
Resource Type	Article

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