基于免疫克隆与差分进化的入侵检测方法  

Intrusion Detection Method Based on Immune Cloning and Differential Evolution

作　　者：边根庆[1] 赵宏[1] 张维琪[1] 孙继武[1] 

机构地区：[1]西安建筑科技大学信息与控制工程学院,陕西西安710055

出　　处：《微电子学与计算机》2012年第5期124-128,共5页Microelectronics & Computer

基　　金：国家自然科学基金(61073196);陕西省自然科学基金(2011JM8026);陕西省教育厅自然科学专项基金(11JK0982)

摘　　要：随着网络技术的飞速发展,信息安全变得越来越重要.入侵检测方法已经成为信息安全领域的热门研究方向之一.入侵检测实质上是一个分类的问题,对于提高分类精度是十分关键的.免疫克隆算法和差分进化算法都是用于解决分类问题的比较有效的方法.结合先前免疫克隆算法和差分进化算法分别在入侵检测中所取得的良好效果,在对差分进化算法改进的基础上,提出了一种基于免疫克隆和差分进化的混合入侵检测方法.仿真实验结果表明,该方法比文献中提出的方法具有更高的检测率和更低的误检率,能使检测系统在一定程度上有效的识别未知入侵.With the rapid development of network, information security has become more and more important. Intrusion detection method has become one of research direction in the field of information security. Intrusion detection is essentially a classification problem. It is very critical to increase the classification accuracy. Immune cloning algorithm and differential evolution algorithm are both effective methods to solve classification problems. Combined with previous good effect of intrusion detection in which immune cloning algorithm and differential evolution algorithm were used respectively. This paper proposes one intrusion detection method based on the improvement of differential evolution algorithm which includes immune cloning algorithm and differential evolution algorithm. Simulation experiments show that this method has higher detecting rate and lower error detecting rate than the method of literature, it can make the intrusion detection system recognition unknown intrusion effectively in certain extent.

关 键 词：免疫克隆算法 差分进化算法 入侵检测 检测率 误检率 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]