模糊C均值聚类在入侵检测中的应用研究综述

随着网络技术的发展和网络规模的扩大，针对计算机网络攻击的方式也日趋多样，那么入侵检测就成为了网络安全研究的热点。为此分析研究了模糊C均值聚类算法在入侵检测中的应用，在此基础上从初始聚类中心、初始化隶属度矩阵、加权指数m和与其他方法相结合四个方面对其在入侵检测中的应用做了进一步的研究，并且讨论了这些算法存在的问题，同时指出了模糊C均值聚类在入侵检测中的研究方向。

The Applied Research Summary for Fuzzy C-means Clustering in Intrusion Detection

Along with the development of network technique and the expansion of network size,the attack＇s ways for computer network is diverse day by day and then the intrusion detection has become the study hotspot of network security. This paper analyzes and studys the application of Fuzzy C-means Clustering algorithm in the intrusion detection,based on this also further studying the application of its improvement algorithms in the intrusion detection from the four aspects：the initial cluster center,the initialization degree of membership matrix,weighted index m and unifies with other algorithm,and discusses the existence issue of these algorithms,simultaneously has pointed out the study direction for the application of the Fuzzy C- means Clustering in the intrusion detection.