A novel method of intrusion detection based on artificial immune system

被引：0

作者：

Zhang, Yu-Fang ^{[1
]}

Sun, Gui-Hua ^{[1
]}

Xiong, Zhong-Yang ^{[1
]}

机构：

[1] Chongqing Univ, Coll Comp, Chongqing 400044, Peoples R China

来源：

PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年

关键词：

antigen-antibody; constraint-based detectors; any-r intervals matching rule; self-pattern class;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a novel method of intrusion detection based on artificial immune system. Adopting the constraint-based detectors and any-r intervals matching rule, a novel solution is presented to encode the antibody-antigen. Some immune related concepts are introduced. In order to accelerate the accessing of the normal IP packets, the self-pattern class is proposed. Using the data sets of KDD CUP1999, the experiment results show that the proposed method can achieve a faster running speed band better detecting rates. It also can adapt to dynamically changing environments.

引用

页码：1602 / +

页数：2

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