Artificial immune theory based network intrusion detection system and the algorithms design

被引：0
|
作者：
Yang, XR [1 ]
Shen, JY [1 ]
Wang, R [1 ]
机构：
[1] Xi An Jiao Tong Univ, Dept Comp Sci & Technol, Xian, Peoples R China
来源：
2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS | 2002年
关键词：
data mining; network intrusion detection(NID); artificial immune system (AIS); genetic algorithm;
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：
A network intrusion detection model based on artificial immune theory is proposed in this paper. In this model, self patterns and non-self patterns are built upon frequent behaviors sequences, then a simple but efficient algorithm for encoding patterns is proposed. Based on the result of encoding, another algorithm for detectors creating is presented, which integrates negative selection with clonal selection. The algorithm performance is analyzed in the end, which shows that this method can shrink each generation scale greatly and create a good niche for patterns evolving.
引用
收藏
页码：73 / 77
页数：5
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