基于粗糙集理论的网络入侵检测系统  

Network Intrusion Detection System Based on Rough Set Theory

作　　者：静永文[1] 

机构地区：[1]华北电力大学信息与网络管理中心,河北保定071003

出　　处：《微计算机信息》2009年第21期32-34,共3页Control & Automation

摘　　要：介绍了入侵检测系统模型的结构,应用粗糙集理论实现了一个网络连接的入侵检测系统,用于监控网络的异常行为。在分析基于神经网络的入侵检测模型基础上,将其中的综合分类器采用区分矩阵的属性约简算法对输入及隐含层节点进行约简的优化设计。经实验表明,粗糙集理论应用于多类分类问题和未知攻击的检测方面是有效的。This paper introduces the construction of Instruction Detection System,a network intrusion detection system based on Rough set theory has been developed,used in finding abnormal action in network. Based on＇analysis of network intrusion detection model, the attributes reduction algorithm of the discernible matrix is used for the optimization design of reducing nodes of input and hid- den layers. The experimental results indicate that the Rough sets theory is powerful in multi-class classification as well as effective in unknown attack detection.

关 键 词：粗糙集 属性约简 入侵检测系统 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]