Some aspects of neural network approach for intrusion detection

被引：0

作者：

Golovko, V ^{[1
]}

Kochurko, P ^{[1
]}

机构：

[1] Brest State Tech Univ, Brest 224017, BELARUS

来源：

CYBERSPACE SECURITY AND DEFENSE: RESEARCH ISSUES | 2005年 / 196卷

关键词：

neural networks; intrusion detection systems; PCA; network attacks; attack recognition and identification;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Intrusion detection techniques are of great importance for computer network protecting because of increasing the number of remote attack using TCP/IP protocols. There exist a number of intrusion detection systems, which are based on different approaches for anomalous behavior detection. This paper focuses on applying neural networks for intrusion detection and recognition. It is based on nonlinear PCA network and multilayer perceptron. The 1999 KDD Cup data set is used for F training and testing neural networks. The results of experiments are discussed in the paper.

引用

页码：367 / 382

页数：16

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