一种异常入侵检测系统误报率抑制方法  

Reduction on false positive rate of anomaly IDS

作　　者：刘双强[1] 孙泽宇[2] 

机构地区：[1]湖南工业大学科技学院,湖南株洲412008 [2]洛阳理工学院计算机信息与工程系,河南洛阳471023

出　　处：《计算机应用研究》2009年第11期4322-4324,共3页Application Research of Computers

基　　金：河南省自然科学基金资助项目(0820440628)

摘　　要：抑制入侵检测系统(IDS)的误报率是提高其检测结果可信性的重要途径。通过分析异常入侵检测系统的误报率问题,提出了基于人工免疫思想,动态构建正常系统轮廓,抑制误报率的方法。建立了自体、抗原、抗体的动态变化模型和演化机制,并进行了仿真实验。结果表明该方法可以有效降低异常入侵检测系统误报率。The reduction on the false positive rate of intrusion detection systems （IDS） is one of the important ways to improve detection creditability. After analyzing false positive rate of anomaly IDS, presented methods to reduce the false positive rate. The method was constructing normal profile dynamically based on artificial immunity to restrain false positive rate. At the same time, the dynamical model and evolution of self, Ag were constructed then simulation experiment was done. The results show that the method can reduce the false positive rate efficiently.

关 键 词：异常入侵检测 误报率 人工免疫 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]