User-habit based early warning of worm - WANG Ping; FANG Bin-xing; YUN Xiao-chun; PENG Da-wei (Tongxin xuebao)
On the burst-out of massive worm,the overwhelming flow caused by random scanning would temporarily alter the behavior representation of users.Therefore,it was consequently reasonable to conclude that statistics and classify the user habit would certainly help in the detection of worm efficiently.The behavior of user was analyzed deeply,a new approach for early warning of worms was proposed,and a user-based early warning system was realized.Because of the diversity of user habit,several application models can be derived from the model,it has strong direction signification.