Research on Fuzzy Genetics-Based Rule Classifier in Intrusion Detection System

摘要：

Intrusion detection technique has become the focus in the area of network security research. Various soft computing approaches have been applied to the intrusion detection field. The paper incorporate fuzzy logic and genetic algorithms into the classifying system based on fuzzy association rule to extract both accurate and interpretable fuzzy IF-THEN rules from network traffic data for classification, and utilize genetic algorithms to optimize the classifier, The experiments and evaluations of the proposed method were performed with the KDD Cup 99 intrusion detection dataset. Results indicate the high detection accuracy for intrusion attacks and low false alarm rate of the reliable system.

作者: YU-PING ZHOU JIAN-AN FANG DONG-MEI YU

作者单位: College of Information Science and Technology, Donghua University, Shanghai 201620, China

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 914-919

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）