A Privacy Protection Method Based on Trajectory Location Point Association

Abstract

Location-based services (LBS) technology provides personalized services for users. However, private location information faces the risk of being leaked while users are enjoying the LBS services. In order to prevent this from occurring, this study proposes an anonymous privacy protection method based on trajectory location association, abbreviated as AS-AP, which considers the association between the user’s current location and the background information. The association between locations is mined from time and query preferences, and then fake locations and queries are generated as part of the anonymous interference requests. This conforms to the k-anonymity feature, which prevents attackers from inferring the user's real intent from the network information, thereby enhancing the credibility of network technology, and protecting data privacy. The experimental results indicate that AS-AP can provide more personalized privacy protection services while ensuring that users' sensitive data is protected.