| As a new mode of travel,ride-hailing meets people’s diversified travel needs,alleviates traffic congestion,enhances traffic safety,and is of positive significance to economic and social development.However,with the development of online ride-hailing services,its privacy and security problems are gradually exposed,especially the location privacy risks caused by location information disclosure,tracking,retention and abuse.The main responsibility of ride-hailing platform is to provide users with ride-sharing matching services,so the privacy protection of ride-sharing matching process is the core content to protect users’ privacy in ride-sharing scenarios.Although the existing privacy protection scheme of ride-sharing service has made good progress in protecting the privacy of driver and passenger location,it still has some problems.On the one hand,when the online ride-hailing platform is faced with a large number of requests from passengers and drivers,the time complexity to complete the matching between drivers and passengers is relatively high.On the other hand,in a typical scheme based on fixed hidden area division,drivers and passengers located at the boundary of adjacent areas,although similar in location,cannot be matched successfully.Therefore,based on the similarity of interest points,this paper studies the privacy protection scheme in ride-hailing matching.The main innovations of this paper are as follows:1.In view of the user location privacy leakage problem commonly existed in the driver and passenger matching scheme under the traditional ride-hailing architecture,this paper proposes a privacy protection scheme of ride-hailing service combining similarity matching technology of interest points and public key encryption with equality test(PKEET).In this scheme,a set of points of interest(POI)is used to represent the geographical location of users in the ride-hailing service,and the POI plaintext set is transformed into an unidentifiable POI privacy set,and the distance calculation problem of two location points is transformed into a privacy set intersection problem.By using the privacy set intersection scheme based on Bloon filter and PKEET,the online ride-sharing platform intersects the POI privacy sets of passengers and drivers,providing safer and more efficient ride-sharing matching services without knowing the specific location of users.Compared with the scheme based on hidden region division,this scheme can avoid the matching failure caused by region boundary problems,and further improve the matching success rate.Compared with typical ride-hailing privacy protection schemes such as PSRide,PGRide and Oride,under the assumption that the number of typical POI is 40,the average communication cost of this scheme increases by at least 60%and the average computing cost increases by at least 37%.2.In order to solve the problem of privacy leakage caused by more frequent sharing of vehicle location information under the Cloud-Edge-End architecture for the Internet of Vehicles,this paper proposes a privacy protection scheme of online ride-hailing that integrates flooding technology,K-anonymity technology and privacy collection intersection technology.Firstly,the scheme confuses the message in the network by applying the flooding technology and K-anonymity technology,so that other entities in the Internet of vehicles cannot link the user identity with the message,so as to ensure the privacy of the user identity.On this basis,the privacy set intersection technology based on hash function is used in this paper to reduce the communication cost and calculation cost of the scheme without reducing the security.Compared with typical ride-hailing privacy protection schemes such as PSRide,PGRide and Oride,under the assumption that the number of typical POI is 40,the average communication cost of this scheme increases by at least 85%and the average computing cost increases by at least 90%. |
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