USING FUZZY NEURAL NETWORKS AND RULE HEURISTICS FOR ANOMALY INTRUSION DETECTION ON DATABASE CONNECTION

摘要：

This paper addresses the Issue of intrusion detection in database security management A Fuzzy Adaptive Resonance Theory neural network and rule heuristics are used to build a model of company security judgment The model is based on analysis of the log file of connections from the client side to the database of server side. The log file information includes user name, network address of client, the time of connection, the database name, the program used, and the protocol. Those features are inputted to a Fuzzy Adaptive Resonance Theory neural network for security judgment An experiment using records from a local government office database indicates that our system has good results in detecting anomalous intrusions.

关键词： Fuzzy ART intrusion detection system (IDS) misuse intrusion detection ezpert system

作者: RUNG-CHING CHEN KAI-FANG CHENG CHENG-CHIA HSIEH

作者单位: Department of Information Management ChaoYang University of Technology

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 3607-3612

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）