文献类型：会议论文

英文题名：A danger-theory-based abnormal traffic detection model in local network

作者：Wang, Xiuying[1]; Shao, Zhiqing[1]; Xiao, Lizhong[2]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China; [2] Department of Computer Science, Shanghai Institute of Vocation and Technology, Shanghai, China

会议论文集：Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008

会议日期：December 12, 2008 - December 14, 2008

会议地点：Wuhan, Hubei, China

语种：英文

外文关键词：Antibodies - Peer to peer networks

摘要：To solve the problem that abnormal traffic including Internet worm and P2P downloading has occupied the LAN's bandwidth, a danger-theory-based model to detect anomaly traffic in LAN is presented in this paper. The definition is given, in this paper, to such terms as dangerous signal, antigens, antibodies and memory antibodies. Besides, matching rule between antigen and antibody is improved. Experiments show the outstanding performance of the proposed model in real-time property, high detection rate and unsupervised learning. ? 2008 IEEE.