基于图的数据挖掘在入侵检测系统中的应用  

Graph-based data mining for intrusion detection system

作　　者：吴师鹏[1] 欧阳为民[1] 陈宁宇[1] 徐春荣[1] 

机构地区：[1]上海大学计算机学院,上海200072

出　　处：《计算机工程与设计》2005年第6期1651-1653,共3页Computer Engineering and Design

摘　　要：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。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.

关 键 词：图 数据挖掘 网络安全 入侵检测 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]