Intrusion Detection Method Based on LEGClust Algorithm

Yi Lin Zhao; Qing Lei Zhou

doi:10.4028/www.scientific.net/AMM.263-266.3025

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 263-266Intrusion Detection Method Based on LEGClust...

Intrusion Detection Method Based on LEGClust Algorithm

Abstract:

Clustering analysis is a typical unsupervised learning technology in data mining, which can improve the efficiency of intrusion detection system. LEGClust cluster algorithm is a new clustering analysis technique and it can effectively find the arbitrary shape clusters hidden in the data. We apply this algorithm to the intrusion detection field and present an intrusion detection method. We introduce the real dissimilarity among data into the determination of data connection relationship. Experiment results on KDD CUP1999 Dataset show that LEGClust algorithm is an effective technique for intrusion detection and the improved LEGClust performs even better.

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Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

3025-3033

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.3025

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Online since:

December 2012

Authors:

Yi Lin Zhao, Qing Lei Zhou

Keywords:

Clustering Analysis, Intrusion Detection, Legclust Algorithm, Renyi’s Quadratic Entropy

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