Intrusion detection using PCASOM neural networks

被引：0

作者：

Liu, Guisong ^{[1
]}

Yi, Zhang ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Computat Intelligence Lab, Sch Comp Sci & Engn, Chengdu 610054, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS | 2006年 / 3973卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a method to detect network intrusions by using the PCASOM (principal components analysis and self-organizing map) neural networks. A modified unsupervised learning algorithm which is more suitable for intrusion detection is presented. Experiments are carried out to illustrate the performance of the proposed method by using DARPA 1998 evaluation data sets. It shows that the proposed method can cluster the network connections into proper clusters with high detection rate and relatively low false alarm rate.

引用

页码：240 / 245

页数：6

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