| Recently,with the development of position sensing technology and wireless sensors,the number of position sensing devices has increased significantly,and location-based services(Location-Based Services,LBS)are becoming more and more popular.The LBS is widely used in the internet of vehicles(Internet of Vehicles,Io V)and the servers in Io V continuously obtain a large amount of location trajectories information.These information contains a large number of personal privacy data,so it is necessary to protect the trajectories data of vehicles in the Io V.At present,most of the trajectory privacy protection methods are implemented by trusted third party(Trusted Third Party,TTP)centralized anonymous servers.However,the traditional third party centralized anonymous servers have the problem of performance bottleneck and because the servers store a lot of user's data,it is easy to be attacked centrally.This paper uses the edge servers instead of the TTP in location services.In consideration of the problem that the similarity of trajectories is not high enough,the number of virtual trajectories is not accurate enough,the virtual trajectories are not accurate enough,which leads to the decrease of security and affects the quality of user services.The trajectory privacy protection methods in the Io V under the edge computing architecture are designed in this paper.The specific research contents are as follows.(1)A location-based trajectory privacy protection method in Io V is proposed.In order to better protect the user's trajectory information,we design a virtual trajectory generation(Virtual Trajectory Generation,VTG)under the edge architecture.When the vehicle users make requests,the virtual ranges are constructed,the position coordinates in virtual trajectories are set and a certain number of virtual trajectories are designed by analyzing the request information of the users at different times.It avoids the problem of generating unrealistic position points in traditional trajectories generation algorithm and makes the generated virtual trajectories more easier to confuse attackers.At the same time,a new trajectory privacy measure is introduced to measure the degree of VTG privacy protection methods.The edge nodes in the privacy protection model are used as trusted third parties which solves the problem that traditional third parties are easy to be centralized attacked while alleviating the storage and computing pressure of cloud servers.The experimental results show that the method can further narrow the virtual scope,improve the similarity of the trajectories,reduce the number of deviation points and provide better privacy protection for the real trajectories of the users.(2)A regional trajectory privacy protection method based on trajectory entropy is proposed.Aiming at the problem of low users' trajectories utilization and uncertain number of virtual trajectories in the region,a region trajectory protection method based on trajectory entropy(Based on Trajectory Entropy,BTE)is proposed to protect the users' real trajectories.The influence of attackers background is added to the trajectory entropy calculation to obtain the required number of virtual trajectories and avoid the generation of unnecessary trajectories.At the same time,a virtual trajectory generation algorithm based on trajectory entropy is designed to generate virtual trajectories.The trajectories that do not meet the requirements are eliminated through calculating the weighted multi-feature distance between trajectories to further improve trajectory utilization and the purpose of protecting the real trajectories is achieved.Simulation experiments verify the effectiveness of the proposed method in terms of efficiency and trajectories' similarity.The experimental results show that this method can effectively determine the number of virtual trajectories required,reduce the invalid virtual trajectories,improve the similarity of trajectories,and shorten the delay in response to users' requests. |
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