Privacy-Preserving Matching Scheme for IoV-Enabled Ride-Sharing Services

Ride-sharing services provide automated route matching for drivers and passengers with similar itineraries and schedules, which alleviate traffic congestion and reduce travel costs. To protect the location privacy in the ride-sharing process, a variety of privacy-preserving matching schemes were proposed. However, the existing matching schemes incur high computational overhead, and cannot resist the attack of malicious adversaries. In this paper, we proposed a privacy-preserving matching scheme based on threshold private set intersection, which can protect the location privacy in the malicious model. To reduce computational overhead, we designed a new efficient method for the cardinality test of the route intersection size, based on symmetric-key primitives and a constant number of public-key operations. In addition, our privacy-preserving matching scheme uses geographic indistinguishability to generate virtual points as input sets of privacy-preserving matching scheme, and the Internet of Vehicles (IoV) uses the output of privacy-preserving matching scheme to match the appropriate vehicle for the user. The performance evaluation shows that the proposed scheme is efficient for IoV-enabled ride-sharing services.