Research On Privacy Protection Based On Location Services

With the widespread application of technologies such as GPS and wireless communication,location-based services have facilitated users' daily lives.Based on the intelligent positioning system,users interact with LBS applications to enjoy location-based services such as point-of-interest query,emergency handling,and location sharing.However,when enjoying many services provided by LBS applications,users need to submit their own location information and authorize the LBS application to perform data analysis on some location information,which causes serious user privacy leakage problems.Therefore,designing a location privacy security mechanism that takes into account both privacy protection and utility for users has become a current hot research issue based on location services.This paper focuses on the credibility of collaborative users in distributed location k anonymity,the location sharing strategy between users and third-party adversaries in LBS application authorization,and the utility of shared location data and privacy protection issues.The specific research work is as follows.(1)Aiming at the credibility of collaborative users in distributed location k anonymity,a privacy protection scheme for k anonymity location based on the fusion of game theory and blockchain is proposed.Firstly,determine the cooperative users who participate in the construction of anonymous groups based on the static game theory;Secondly,build a reputation mechanism to combine users' recent behavior and earnings,and restrict the dishonest behavior of requesting users and collaborating users who participate in the construction of anonymous groups;finally,using the blockchain to store the game process and collaborative users' location information,and penalizes dishonest users with reduced reputation value and earnings.This ensures the true availability of anonymous groups,promotes user honest cooperation,and protects user privacy.(2)Aiming at the sharing of location information between users and third parties,a personalized LBS user location privacy protection scheme based on game theory is proposed.Firstly,users set sharing thresholds for location information sharing,and set sensitive values based on the importance of privacy to different locations.Secondly,establish a reputation rating mechanism based on the historical behavior of third parties,and consider the impact of the network's comprehensive environment and reputation rating on third-party integrity location requests.Finally,the static game theory is used to analyze the behavior strategies of users and third-party adversaries,and the enemy's honesty value is calculated from the perspective of revenue.By comparing the trustworthiness value and the sharing threshold value,the malicious location request of a third-party adversary is rejected and punished.Thereby protecting users' location privacy and encouraging users to use location-based services more actively.(3)Aiming at the utility and privacy protection of shared location data,a LBS user location privacy protection scheme based on differential privacy is proposed.Firstly,preprocess the shared location data set,and use the Trie tree structure to store location data and frequencies.Secondly,select locations with high frequency,and use the Laplacian mechanism under differential privacy to add noise to generalize sensitive location data.Finally,post-processing was performed on the disturbed position data,and the accuracy and false rejection rate of the position data under the three post-processing were compared through experiments.Thereby,while protecting the privacy of the user's sensitive location,the shared location data set has higher usability.