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
收藏
页码：1602 / +
页数：2
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