A Network Intrusion Detection Algorithm Based on Rough Set Attribute-weighted Clustering
Intrusion detection system is automatic system which recognize intrusions to computers or computer network systems. Existing security detection system has many problems such as wrong detection of intrusions, missed intrusions, poor real-time performance. An intrusion detection algorithm is developed by combining a rough set algorithm with intrusion detection technology for security detection, attribute reduction, production of detection rules, and finally analysis of intrusion data with these rules. Based on it, a new rough set attribute-weighted clustering algorithm is used in network intrusion detection. Test rules show that the intrusion detection algorithm is more efficient than algorithm based on BP (back propagation) neural networks and vector machines, thereby, improving the detection ratio and reduces the wrong detection ratio. The system provides detection service effective for information system.
Rough Set Weighted Clustering Intrusion Detection
WANG Lifang
Institute of Electronic and Computer Science Technology, North University of China, Taiyuang,Shanxi, China,030051
国际会议
第八届国际测试技术研讨会(8th International Symposium on Test and Measurement)
重庆
英文
3551-3554
2009-08-01（万方平台首次上网日期，不代表论文的发表时间）