In order to quickly and accurately find the implementer of the network crime,based on the user portrait technology,a rapid detection method for users with abnormal behaviors is proposed.This method needs to construct ...In order to quickly and accurately find the implementer of the network crime,based on the user portrait technology,a rapid detection method for users with abnormal behaviors is proposed.This method needs to construct the abnormal behavior rule base on various kinds of abnormal behaviors in advance,and construct the user portrait including basic attribute tags,behavior attribute tags and abnormal behavior similarity tags for network users who have abnormal behaviors.When a network crime occurs,firstly get the corresponding tag values in all user portraits according to the category of the network crime.Then,use the Naive Bayesian method matching each user portrait,to quickly locate the most likely network criminal suspects.In the case that no suspect is found,all users are audited comprehensively through matching abnormal behavior rule base.The experimental results show that,the accuracy rate of using this method for fast detection of network crimes is 95.9%,and the audit time is shortened to 1/35 of that of the conventional behavior audit method.展开更多
基金This research is supported by The National Natural Science Foundation of China under Grant(No.61672101)Beijing Key Laboratory of Internet Culture and Digital Dissemination Research(No.ICDDXN004)Key Lab of Information Network Security of Ministry of Public Security(No.C18601).
文摘In order to quickly and accurately find the implementer of the network crime,based on the user portrait technology,a rapid detection method for users with abnormal behaviors is proposed.This method needs to construct the abnormal behavior rule base on various kinds of abnormal behaviors in advance,and construct the user portrait including basic attribute tags,behavior attribute tags and abnormal behavior similarity tags for network users who have abnormal behaviors.When a network crime occurs,firstly get the corresponding tag values in all user portraits according to the category of the network crime.Then,use the Naive Bayesian method matching each user portrait,to quickly locate the most likely network criminal suspects.In the case that no suspect is found,all users are audited comprehensively through matching abnormal behavior rule base.The experimental results show that,the accuracy rate of using this method for fast detection of network crimes is 95.9%,and the audit time is shortened to 1/35 of that of the conventional behavior audit method.
