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Intrusion Detection Approach Using Connectionist Expert System
作者姓名:马锐  刘玉树  杜彦辉
作者单位:[1]School of Software, Beijing Institute of Technology, Beijing 100081, China [2]Department of Information Security Science, Chinese People's Public Security University, Beijing 100038, China
基金项目:the Ministerial Level Foundation (9181201)
摘    要:

关 键 词:专家系统  侵入检测  神经系统网络  检测效率
文章编号:1004-0579(2005)04-0467-04
收稿时间:2004-04-14

Intrusion Detection Approach Using Connectionist Expert System
MA Rui,LIU Yu-shu and DU Yan-hui.Intrusion Detection Approach Using Connectionist Expert System[J].Journal of Beijing Institute of Technology,2005,14(4):467-470.
Authors:MA Rui  LIU Yu-shu and DU Yan-hui
Affiliation:1. School of Software, Beijing Institute of Technology, Beijing 100081, China
2. Department of Information Security Science, Chinese People's Public Security University, Beijing 100038, China
Abstract: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.
Keywords:intrusion detection  neural networks  expert system
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