Intrusion Detection Using Multiple Classifiers Fusion and Clustering Analysis

摘要：

Decision fusion of multiple classifiers can obtain more accurately classification than the best single classifier.By applying multiple classifiers fusion and clustering analysis and the nearest neighbor rule respectively,this paper presents a new intrusion detection algorithm.The analysis and experiment results show that this algorithm can acideve a good detection performance and reduce remarkably the errors and false alarms for intrusion detection.

关键词： Clustering analysis Decision fusion Intrusion detection Multiple classifiers fusio

作者: Cheng Zhong Aizhong Mi Feng Yang

会议类型: 国际会议

会议名称: The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)

会议地点: 成都

会议语种:英文

页码: 1181-1183

在线出版日期: 2007-12-19（万方平台首次上网日期，不代表论文的发表时间）