Paper Title:
Robust Intrusion Detection Algorithm Based on K-Means and BP
  Abstract

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, 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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