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.
出处
《计算机应用研究》
CSCD
北大核心
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)
关键词
异常入侵检测
误报率
人工免疫
anomaly intrusion detection
false positive rate
artificial immunity
