数据挖掘在网络异常检测中的应用

随着网络的普及，网络安全已经成为一个非常重要的课题。在Internet中存在大量的数据，数据挖掘（Data mining）是一种从大量数据中自动挖掘新知识并对数据进行描述的数学方法。异常检测是入侵检测（IDS）的一种，它对网络及用户正常行为的特征进行描述，并通过对于正常网络行为的偏差比较实现入侵检测。在该项目中，利用K-Mean数据挖掘的方法对网络数据加以描述并用于网络的异常检测。

The Application of Data Mining in Network Anomaly Detection

With the popularity of the network,network security has become a very important issue.There exists a large amount of data in the Internet.Data mining is a mathematical method to automatically discover new knowledge from the data.Anomaly detection is one method of Intrusion Detection(IDS).It describes the normal behavior' s characteristics of network and user and realizes intrusion detection through comparing with normal network behavior.In this work we use K-Mean method to describe network data and apply it...