基于模糊遗传学习的入侵检测方法  

Intrusion Detection Method Based on Fuzzy Rules

作　　者：黄铁[1] 刘巧梅[2] 

机构地区：[1]湖南文理学院计算机系,湖南常德415000 [2]成都信息工程学院计算科学系,四川成都610225

出　　处：《计算技术与自动化》2008年第3期60-62,共3页Computing Technology and Automation

摘　　要：提出一种基于模糊遗传学习的入侵检测方法。该方法利用SRPP拟合函数算法,通过初始规则的选择操作完成对已有知识的继承,通过相似度计算进行规则变异操作。该算法可以有效控制规则数,加速检测过程,并且由于变异会产生新的规则。实验表明提出的方法能够加快入侵检测过程,减轻检测负载,提高检测效率,降低误报率、漏报率。In this paper, an intrusion detection method based on fuzzy genetics is presented. This method can compete mastered knowledge inheriting by selection operation to former rules, can perform rules mutation operation by resemble degree computation. This method can effectively control rule number and accelerate intrusion detection process with SRPP fitness function, also can produce new rules with mutation. Experimental results demonstrate the proposed method can accelerate the intrusion process, relieve detection load , improve detection rate, decrease false positive and false negative rate .

关 键 词：模糊遗传 入侵检测 变异 检测率 误报率 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]