Research On Location Privacy Related Technologies For Internet Of Vehicles

With the development of communication technology,mobile network and automobile industry,cars are no longer just simple means of transportation.Coupled with the iterative update of science and technology in the 21 st century and the rapid development of 5G information age,the traditional information age has gradually transitioned from the Internet age dominated by users connected to the Internet of Things era led by the Internet of everything.In the current society,with the continuous advancement of urbanization and the popularization of intelligent vehicles,Internet of Vehicles(IOV)is not only an important application branch of 5G network,but also plays a vital role in traffic accident warning,vehicle information query,traffic section control and other safety services.At the same time,location-based service(LBS)provides great convenience for the navigation system operation of vehicles in the road network system,vehicle remote diagnosis,in-car office and other business under the background of the increasingly strong development of the Internet of vehicles.Most of the existing research on privacy of Internet of vehicles focuses on the spatial dimension of location information data,and less consideration is given to other background information.Some research schemes can only be used in specific scenarios and are not universal.Some ignore the impact of the sensitivity of data in different regions and the correlation of time and space on privacy protection,resulting in the decline of service quality,and it is difficult to adapt to the complex and changing environment of IOV.In view of these shortcomings,this paper studies the privacy and security related technologies of Internet of vehicles in location-based services,and the work and innovations are as follows.Aiming at the problem that location privacy protection in Internet of Vehicles ignores the large difference in the change trend of user access to the same location unit every day under the continuous time background,a dummy location screening algorithm based on spatio-temporal correlation(STCDS)in Internet of vehicles was proposed.In the algorithm,the spatial sensitivity measurement standard is proposed,the location semantic similarity is comprehensively considered when selecting the dummy location,and the screening index of semantic-spatial sensitivity expectation is proposed to generate the dummy location set that meets the requirements of query probability in sub-time period and anonymous area.The experimental results prove the feasibility and effectiveness of the algorithm,which can adapt to the current location privacy protection requirements of the Internet of vehicles.The trajectory privacy protection of Internet of vehicles ignores the influence of location semantic information and lacks personalized design.The only method considering location semantics in the trajectory does not integrate semantic information into the standard of privacy protection level,which is vulnerable to background knowledge attacks.Therefore,a trajectory privacy protection algorithm based on regional sensitivity(TPPRS)for Internet of vehicles was proposed.The algorithm clusters the location semantic information in the user’s original trajectory and proposes a regional sensitivity discriminant criterion,divides the regional protection level,allocates Laplacian noise with different privacy budgets according to different protection levels,and generates a trajectory dataset of IOV that meets differential privacy.Finally,a personalized location privacy protection system was implemented by combining the spatio-temporal correlation based IOV dummy location screening algorithm STCDS with the regional sensitivity based IOV trajectory privacy protection algorithm TPPRS.Tests show that the system can meet the privacy protection requirements of single point and multiple continuous location points of IOV users.