The Research On Hierarchical Privacy Protection Method Of Internet Of Vehicles Based On Location Semantics

Internet of Vehicle(IOV)refers to the wireless transmission technology between communication devices to realize the information exchange between vehicles and the surrounding environment,so as to provide drivers with intelligent driving management services.In the IOV system,vehicles obtain Location Based Service(LBS)through location information.When users provide their own location information,sensitive information is exposed and vulnerable to privacy attacks by malicious users.Therefore,the issue of privacy disclosure when obtaining LBS in IOV deserves high attention.Due to the lack of consideration of location semantics in existing studies,privacy protection areas are vulnerable to inferred attacks by attackers,which makes privacy protection ineffective and reduces the availability of private data.While ensuring data availability,there is a trade-off between privacy protection and quality of service.As privacy protection increases,so does the complexity of data processing,which reduces the efficiency and accuracy of services.Aiming at the privacy protection needs of users when they obtain LBS in IOV,this paper addresses the problem of low data availability and balances the relationship between privacy protection and service quality from the perspectives of historical trajectory data and real-time trajectory release respectively.The specific work content is as follows:(1)Based on historical track data,this paper proposes an anonymous protection method based on location semantics.Firstly,a sensitive semantic location map is generated according to the historical trajectory.Secondly,the semantic security protection level is set according to the user needs,and the privacy level is customized to improve the service quality on the basis of meeting the user’s privacy needs.Finally,semantic similarity is used to screen the components of anonymous zone from the three aspects of time,space and semantics,so that the distribution of anonymous zone takes into account the semantic security and temporal and spatial correlation,avoiding the attackers to weaken the protection effect of anonymous zone through background information,so as to improve the availability of privacy protection data.(2)The anonymous zone generated according to the historical track data is static and lacks real-time performance,which cannot adapt to the changeable road conditions in the Internet of vehicles.In order to remedy this defect,this paper proposes a real-time publishing trajectory privacy hierarchical protection method.Firstly,combining user privacy needs and historical track data,information entropy is used to assign appropriate privacy levels for different locations,so as to ensure better privacy protection without sacrificing service quality.Then,the false location set is generated according to the road condition and vehicle running state.Then,a privacy protection model and a trajectory differential privacy protection model are built to screen false locations that meet privacy security requirements.Finally,the false location is optimized again from the semantic and curve similarity degree to improve the data availability of false trajectories.