Integration of Heterogeneous Classifiers for Intrusion Detection

摘要：

To address the problem of less rare data and low detection accuracy, The paper proposes a heterogeneous classifier integrated by the random forests, support vector machines, clustering and Bayesian classifier to increase the detecting accuracy of rare class, and to detect rare class with the greatest weighted voting. Experimental results show that utilizing integration of heterogeneous classifiers in intrusion detection system can improve obviously detection precision and decrease false positive rate.

关键词： heterogeneous classifier integration intrusion detection

作者: Yong Zhang Linjie Zhu

作者单位: School of Computer and CommunicationLanzhou University of TechnologyLanzhou,China School of Computer and Communication Lanzhou University of Technology Lanzhou,China

会议类型: 国际会议

会议名称: 2010 3rd International Conference on Advanced Computer Theory and Engineering(2010年第三届先进计算机理论与工程国际会议 ICACTE 2010)

会议地点: 成都

会议语种:英文

页码: 1-3

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）