Fraud information detection method and system based on community mining

Abstract

The embodiment of the invention provides a fraud information detection method and system based on community mining. The fraud information detection method comprises the following steps: acquiring a plurality of subject cluster communities and a plurality of behavior information cluster communities; then, according to a main body object behavior label corresponding to a target main body object, obtaining a reference main body object corresponding to the target main body object, and according to an information category label corresponding to the target behavior information, obtaining reference behavior information corresponding to the target behavior information; and finally, respectively calculating an association parameter between the target main body object and each piece of behavior information in the behavior information sequence, and detecting whether suspected fraud information exists in the behavior information corresponding to the target main body object in the behavior information sequence according to the association parameter. Thus, the suspected fraud information is detected based on the data mining mode of the main body cluster community and the information cluster community, and whether the suspected fraud information exists in the behavior information corresponding to the target main body object or not can be effectively detected.

Description

technical field [0001] The invention relates to the technical field of data security, in particular to a method and system for detecting fraudulent information based on community mining. Background technique [0002] Social networking services (Social Networking Services, SNS) have a very large number of users by promoting online communication and information sharing among people. In order to provide a good user experience, the functions of the social network itself are becoming more and more complex, which poses new challenges to the security and privacy protection of the social network. For example, some lawbreakers take advantage of the openness of social networks and the information exposed by users during use, such as photos, interaction information with friends, etc., to spread fraudulent information in a targeted manner, posing a serious threat to the safety of network users. In addition, with the popularization of online finance, fraudulent information such as desig...

AI Technical Summary

Problems solved by technology

In order to provide a good user experience, the functions of social networks themselves are becoming more and more complex, which poses new challenges to the security and privacy protection of social networks

For example, some lawbreakers take advantage of the openness of social networks and the information exposed by users during use, such as photos, interaction information with friends, etc., to spread fraudulent information in a targeted manner, posing a serious threat to the safety of network users

In addition, with the popularization of online finance, fraudulent information such as designing online banking is becoming more and more rampant, which further threatens the safety of users' funds and may cause direct economic losses to users.

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