用户行为特征提取及安全预警建模技术
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摘要
提出采用行为特征提取技术、用户行为建模技术、异常行为检测技术实现的用户行为特征提取及安全预警系统的主要技术和系统实现。此技术和系统能够实现对用户异常行为的感知与预警,为各业务部门及管理者提供辅助决策支持,对提升网络的安全防护水平具有重要作用和意义。
The main technology and system realization of user behavior feature selection and security early warning system are presented,which is realized based on behavior feature selection and user behavior modeling and anomaly detection technology. The technology and system can realize perception and early warning to user anomaly,and provide decision-making support to each business department and governor,have important effect and meaning on accelerating network security defending ability.
The main technology and system realization of user behavior feature selection and security early warning system are presented,which is realized based on behavior feature selection and user behavior modeling and anomaly detection technology. The technology and system can realize perception and early warning to user anomaly,and provide decision-making support to each business department and governor,have important effect and meaning on accelerating network security defending ability.
引文
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[2] Gong SG,Xiang T. Recognition of group activities using dynamic probabilistic networks. In:Werner B,ed. Proc. of the Int’l Conf. on Computer Vision. Los Alamitos:IEEE Computer Society Press,2003. 742-749.
[3] Shechtman E,Irani M. Space-Time behavior based correlation. In:Jacobs A,Baldwin T,eds. Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. Los Alamitos:IEEE Press,2005. 405-412.
[4] Zelnik-Manor L,Irani M. Event-Based analysis of video.In:Jacobs A,Baldwin T,eds. Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. Los Alamitos:IEEE Computer Society Press,2001. 123-130.
[5]郑援,李思昆.虚拟实体对象的行为建模方法研究.国防科技大学学报[J],1998,20(1):78-82.
[6] Zhong H,Shi J B,Visontai M. Detecting Unusual Activity in Video[C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Washington,D. C.,USA:IEEE,2004:819-826.
[7] Hamid R,Johnson A,Batta S,et al. Detecting Unusual Activity in Video[C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego,CA,USA:IEEE,2005:1031-1038.
[8] Xiang T,Gong SG. Video behaviour profiling and abnormality detection without manual labeling. In:Werner B,ed. Proc. of the Int’l Conf. on Computer Vision. Los Alamitos:IEEE Computer Society Press, 2005.1238-1245.