The Research Of Location-based Service Privacy Protection In Internet Of Vehicle

With the rapid development of the Internet of Vehicles and the maturity of the navigation system,intelligent services for vehicles have become widespread,especially location-based services have been widely integrated into people's daily lives.However,all applications based on location services require users to submit their location information,which will make users' location information public and cause sensitive information to leak.For example,users frequently upload location information,will disclose their driving routes and points of interest,the attacker intercepts this information to make speculative attacks on it,and then obtains the user's sensitive information,such as home address,work place,political beliefs,and even endangering the lives of users.Therefore,how to protect the privacy of the location while ensuring the user's personalized service needs is an urgent problem to be solved.The thesis focuses on how to provide users with personalized location privacy protection in vehicular networks.The main work is embodied in personalized services and location privacy protection.The specific research work is as follows:(1)The privacy protection needs of users at different query locations are different.In view of the existing mechanism,which simply divides privacy into different levels and cannot provide personalized privacy protection problems for users' different needs,we propose a Personalized Privacy Budget Allocation(PPBA)algorithm based on sensitive location attributes.By defining a normalized decision matrix to describe the efficiency and privacy effects of the recommended navigation route,and establish a multi-attribute utility function to quantify the benefits of each route,determine the most profitable road as the user's driving route,and then change between the current location and the nearest sensitive location Distance assigns a privacy budget to each query location.(2)In terms of privacy protection of in-vehicle network locations,in view of the existing location privacy protection schemes,which ignore the privacy leakage problems caused by the restricted driving routes of vehicle users and the disclosure of service request information,we design a Location Privacy Protection Scheme(LPPS)using geo-indistinguishability.Based on the information entropy theory,the trajectory impact factor is defined to describe the regional privacy effect,and a Stackelberg model is established to quantify the privacy benefits of in-vehicle users,so that the service area with the highest quality of service and privacy is used instead of the user's real location point,so that the user can guarantee the quality of service while maintaining privacy.Reached the highest.(3)Finally,this paper uses real location data sets for simulation verification.The results show that this scheme improves the effectiveness of the data,the user's privacy is increased by 26%,and the loss of Qo S is reduced by 30%,although the service accuracy is lost by 5%-15%,but due to the accuracy verification of this solution,it meets the user's needs.