Robust Intrusion Detection Algorithm Based on K-means and BP

被引：0
|
作者：
Zhong, Yangjun [1 ]
Zhang, Shuiping [1 ]
机构：
[1] Jiangxi Univ Sci & Technol, Fac Informat Engn, Ganzhou 341000, Peoples R China
来源：
INTELLIGENT STRUCTURE AND VIBRATION CONTROL, PTS 1 AND 2 | 2011年 / 50-51卷
关键词：
Intrusion detection; k-means; BP; Abnormal behavior;
D O I：
10.4028/www.scientific.net/AMM.50-51.634
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
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.
引用
收藏
页码：634 / 638
页数：5
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