A Novel Intrusion Detection Method Based on Adaptive Resonance Theory and Principal Component Analysis

Authors:
Junbi Xiao;Hao Song
Affiliations:
-;-
Venue:
CMC '09 Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 03
Year:
2009

Citing 0
Cited 2

The use of artificial-intelligence-based ensembles for intrusion detection: a review

Applied Computational Intelligence and Soft Computing
Neural network Trojan

Journal of Computer Security

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Abstract

A novel intrusion detection approach based on Adaptive Resonance Theory (ART) and Principal Component Analysis (PCA) is put forward according to analyzing now intrusion detection methods. In this model (PCA-MART2), it defines network behaviors relied upon the datagram. PCA is applied to feature selection about input samples and the multi-layered ART2 is designed to subdivide the imprecise clustering. The modified algorithm improved the speed and accuracy of detection. The experimental results show that the intrusion detection system based on PCAMART2 can detect intrusion behavior in network efficiently.