数据挖掘在协同入侵检测系统中的应用研究

Research on Application of Data Mining in Cooperative Intrusion Detection System

随着网络安全问题的日益重要,入侵检测领域的研究越来越深入,但目前IDS的误报和漏报不能使人满意。该文提出了一种基于数据挖掘方法的协同入侵检测系统(CoIDS)框架。文章详细讨论了协同工作和数据挖掘方法在入侵检测中的应用。使用了多种数据挖掘方法来建立检测模型,并采用了Agent/Manger/UI三层实体结构。并通过具体的例子重点介绍了在此框架中数据挖掘的应用过程。

With network security problem increasingly important ,the research on intrusion detection is going deeper and more deeper,but current IDS's false positve rate and false negative rate are not satisfying.This paper describes a CoIDS framework based on data mining approach.We discuss the application of CSCW and data mining techniques in intrusion detection.We use several data mining approach to create detection model,and use Agent/Manager /UI three-layer entity architecture.In addtion,we stress data mining process using in our framework trough some examples.