Robust Intrusion Detection Algorithm Based on K-Means and BP

Abstract:

Article Preview

Nowadays the traditional intrusion detection models have two disadvantages:low work efficiency and high false positive.Considering these disadvantages,this paper proposes a new intrusion detection method combining k-means clustering algorithm and BP neural network.The experimental results show that the improved intrusion detection model in this paper can save the calculation time significantly with same detection capabilities for the abnormal behavior.

Info:

Periodical:

Edited by:

Shaobo Zhong, Yimin Cheng and Xilong Qu

Pages:

634-638

DOI:

10.4028/www.scientific.net/AMM.50-51.634

Citation:

Y. J. Zhong and S. P. Zhang, "Robust Intrusion Detection Algorithm Based on K-Means and BP", Applied Mechanics and Materials, Vols. 50-51, pp. 634-638, 2011

Online since:

February 2011

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Price:

$35.00

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