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.
出处
《微计算机信息》
2009年第21期32-34,共3页
Control & Automation
关键词
粗糙集
属性约简
入侵检测系统
rough set
attributes reduction
intrusion detection system
