基于数据挖掘算法的网络入侵检测系统研究

回顾了当前入侵检测技术和数据挖掘技术，分析了Snort网络入侵检测系统存在的问题，重点研究了数据挖掘中的关联算法Apriori算法和聚类算法K一均值算法；在Snort入侵检测系统的基础上，增加了正常行为挖掘模块、异常检测模块和新规则生成模块，构建了基于数据挖掘技术的网络入侵检测系统模型。新模型能够有效地检测新的入侵行为，而且提高了系统的检测效率。

The Research of Network Intrusion Detection System Based on Algorithm of Data Mining

The article reviews intrusion detection and data mining techniques detection system, especially module, anomaly detection system model based on data researches the association rule algorithm Apriori and , analyses the clustering rule engine module and new rules generating module are added to the existing problems o algorithm K-means Snort NIDS, finally, f the Snort network intrusion normal behavior patterns mining designs an intrusion detection mining technique. The new system can not only effectively detect new invasion, but also promote detective speed.