Improved Genetic Algorithm in Intrusion Detection Model Based on Artificial Immune Theory

被引：0

作者：

Jing Xiaopei ^{[1
]}

Wang Houxiang ^{[1
]}

Han Ruofei ^{[1
]}

Li Juan ^{[1
]}

机构：

[1] Naval Univ Engn, Informat & Elect Coll, Wuhan, Peoples R China

来源：

2009 INTERNATIONAL SYMPOSIUM ON COMPUTER NETWORK AND MULTIMEDIA TECHNOLOGY (CNMT 2009), VOLUMES 1 AND 2 | 2009年

关键词：

Artificial Immune; Intrusion detection; Genetic Algorithm; Fitness Function;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

After analysis the characteristics of AIS-based Intrusion Detection System, a new AIS-based intrusion detection model based improved Genetic Algorithm is established. By utilizing prominent characteristics of genetic algorithm, such as automatic optimizing, global researching, and adaptability, the new model uses genetic operator to improve the candidate detectors generating algorithm and reduce detectors redundancy. The detectors generated by new model have good fitness and better detection ability. Experiments show that this model can effectively increase the true positive rate of the IDS.

引用

页码：658 / 661

页数：4

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