基于图的数据挖掘在入侵检测系统中的应用

网络入侵检测系统(IDS)是保障网络安全的有效手段，但目前的入侵检测系统仍不能有效识别新型攻击，根据国内外最新的图数据挖掘理论，设计一个特征子图挖掘算法，并将其应用到入侵检测系统中，该算法挖掘出正常的特征子结构，与之偏离的子结构为异常结构。实验结果表明，该系统在识别新型攻击上具有较高检测率。

Graph-based data mining for intrusion detection system

Intrusion Detection Systems (IDS) are developing very rapid in recent years, while the networks are being used widely. But most of traditional IDS can't detecting new attacks. Graph-based data mining is a subject that occurred in the past few years. Based on the theory of graph-based data mining, an algorithm of mining the substructures of a graph was designed, and it was applitd into IDS. It can mine normal pattern from graph data. The result of experiment shows that it can detect new attacks efficiently.