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An Intrusion-Detection Model Based IN php
5.0
As the Internet services spread all over the world,many kinds
and a large number of security threats are increasing. Therefore, intrusion
detection systems, which can effectively detect intrusion accesses, have
attracted attention. This paper describes a novel fuzzy class-associationrule
mining method based on genetic network programming (GNP) for
detecting network intrusions. GNP is an evolutionary optimization technique,
which uses directed graph structures instead of strings in genetic
algorithm or trees in genetic programming, which leads to enhancing the
representation ability with compact programs derived from the reusability
of nodes in a graph structure. By combining fuzzy set theory with GNP,
the proposed method can deal with the mixed database that contains both
discrete and continuous attributes and also extract many important classassociation
rules that contribute to enhancing detection abil
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