Intrusion Detection Approach Using Connectionist Expert System  

作　　者：马锐 刘玉树 杜彦辉 

机构地区：[1]School of Software, Beijing Institute of Technology, Beijing100081, China [2]Department of Information Security Science, Chinese People's Public Security University, Beijing100038, China

出　　处：《Journal of Beijing Institute of Technology》2005年第4期467-470,共4页北京理工大学学报（英文版）

基　　金：SponsoredbytheMinisterialLevelFoundation(9181201)

摘　　要：In order to improve the detection efficiency of rule-based expert systems, an intrusion detection approach using connectionist expert system is proposed. The approach converts the AND/OR nodes into the corresponding neurons, adopts the three layered feed forward network with full interconnection between layers, translates the feature values into the continuous values belong to the interval [0, 1], shows the confidence degree about intrusion detection rules using the weight values of the neural networks and makes uncertain inference with sigmoid function. Compared with the rule based expert system, the neural network expert system improves the inference efficiency.In order to improve the detection efficiency of rule-based expert systems, an intrusion detection approach using connectionist expert system is proposed. The approach converts the AND/OR nodes into the corresponding neurons, adopts the three layered feed forward network with full interconnection between layers, translates the feature values into the continuous values belong to the interval [0, 1], shows the confidence degree about intrusion detection rules using the weight values of the neural networks and makes uncertain inference with sigmoid function. Compared with the rule based expert system, the neural network expert system improves the inference efficiency.

关 键 词：intrusion detection neural networks expert system 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]