入侵检测系统中的数值型关联规则挖掘方法  

Application of Quantitative Association Rules in Intrusion Detection System

作　　者：樊龙[1] 薛贺[1] 陈乐[1] 

机构地区：[1]西北工业大学计算机学院软件工程系,西安710072

出　　处：《微计算机应用》2007年第1期22-26,共5页Microcomputer Applications

摘　　要：入侵检测技术弥补了传统安全机制的一些缺陷。基于数据挖掘的入侵检测系统的挖掘算法尚有不足之处。通过对聚类分析和关联分析的算法分别进行改进，构建出新的基于数值属性关联规则挖掘算法的入侵检测系统。运用此系统进行入侵检测实验，实验结果证明改进的算法效果良好。Intrusion detection settles the issues on which traditional safe methods couldnt work. However, the mining algorithms of intrusion detection system based on data mining technology haveimperfectness, which assumesassociation analysis and clustering to mine data. Accordingly, both the two mining techniques are improved in this paper to beemployed sequently in a new system based on quantitative attribute association rules mining to carry out an experiment. The experimental result is investigated and the expected promotion of the algorithms is achieved.

关 键 词：入侵检测 数据挖掘 关联分析 聚类分析 数值型关联规则 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]