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计算机工程 ›› 2008, Vol. 34 ›› Issue (13): 166-168,. doi: 10.3969/j.issn.1000-3428.2008.13.060

• 人工智能及识别技术 • 上一篇    下一篇

基于粗粒度遗传算法的网络入侵检测系统

李 甦,罗安坤   

  1. (云南大学信息学院,昆明 650091)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-07-05 发布日期:2008-07-05

Network Intrusion Detection System Based on Coarse-grained Model Genetic Algorithm

LI Su, LUO An-kun   

  1. (College of Information, Yunnan University, Kunming 650091)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-07-05 Published:2008-07-05

摘要: 分析遗传算法在入侵检测系统中的可应用情况,提出一种基于粗粒度模型遗传算法的网络入侵检测系统。通过对协议特征的分析,找出有可能被非法利用和更改的特征属性,经过组合和编码后构成系统的初始种群,在各个处理器(终端点)并行地进行遗传算法的操作,使种群的进化在所有检测点同时进行,通过迁移相互交流,合理地设计适应度函数,使遗传“基因”的取舍和利用更加合理。实验数据表明,系统的检测率达到90%以上。

关键词: 网络入侵检测系统, 遗传算法, 种群, 适应度函数, 粗粒度模型

Abstract: This paper puts forward a Network Intrusion Detection System(NIDS) based on coarse-grained model genetic algorithm, after analysing the application of genetic algorithm in intrusion detection system. By analysing the protocol’s property, finds out some characteristics which are often lawlessly changed and used, forms the original chromosome by assembling and coding, makes all processor(terminal points)carry genetic process by attributed manner, makes the evolution of chromosomes prosecute in all detection points simultaneity, and all processor can intercommunacate by transplanting too. At the same time, redesign a reasonable fitness function, to let the use of “gene” be more reasonable. Experimental data shows the system’s detection ability is above 90%.

Key words: Network Intrusion Detection System(NIDS), Genetic Algorithm(GA), chromosomes, fitness function, coarse-grained model

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