Location Privacy Protection Method Based On K-Anonymity

With the development of mobile communication technology and the popularization of mobile smart devices,LBS has covered all aspects of people's daily life and provides convenient and efficient services During LBS request,the user needs to submit personal identity information and accurate location information to an untrusted LBS server.The server performs a query based on the request,and returns the query result to the user.If the untrusted LBS server collects all the information submitted by the user,and even analyzes or publishes it to a malicious third party,it will lead to the leakage of the user's privacy and threaten the user's personal safety.Therefore,how to ensure the quality of LBS service under the premise of protecting user's privacy is an extremely important research work.In the existing solutions,the dummy-based k-anonymity method can provide accurate LBS request results with lower system overhead,which is widely used to protect the location privacy of users However,the neighboring location sets submitted in continuous requests always contain background information that can be exploited by the attacker,such as time correlation and real mobility pattern Therefore,existing methods cannot effectively protect user's location privacy and trajectory privacy To address these issues,this paper constructs a cloaking region based on spatiotemporal correlation to protect location privacy,and obfuscates the spatiotemporal correlation based on cache to protect trajectory privacy.Our main contributions are as follow:1.Proposed the spatiotemporal correlation-aware location privacy protection scheme based on k anonymity.It defines a privacy protection model by introducing an identity authentication server,which anonymizes the user's identity to avoid the performance bottleneck caused by the central anonymizer.Then it defines location entropy and path entropy,and selects dummy locations with similar time-dependent query probability and transition probability to maximize the entropy Security analysis and experimental results show that this method can ensure the privacy level and realize the spatiotemporal correlation-aware location privacy protection2.Proposed the caching-aware spatiotemporal confusion trajectory privacy protection scheme.It uses cached data to answer query requests,and sends fake queries to obfuscate the spatiotemporal correlation of real trajectory.Security analysis and experimental results show that this method can achieve confusion,improve caching,and protect the trajectory privacy in continuous requests.