Intrusion detection via independent component analysis based on rough fuzzy
Date
2006
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Intrusion detection via independent component analysis based on rough fuzzy
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Abstract
Independent component analysis (ICA) aims at extracting unknown hidden factors/components from multivariate data using only the assumption that unknown factors are mutually independent. In this paper we discuss an intrusion detection method that proposes independent component analysis based feature selection heuristics and using rough fuzzy for clustering data. Rough set has to decrease the amount of data and get rid of redundancy and Fuzzy methods allow objects to belong to several clusters simultaneously, with different degrees of membership. The experimental results on Knowledge Discovery and Data Mining-(KDDCup 1999) dataset.
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WSEAS Transactions on Computers