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

作     者：Zhang, En Huang, Yuchen Qin, Leiyong 

作者机构：Henan Normal University College of Computer and Information Engineering Xinxiang453007 China 

出 版 物：《IEEE Transactions on Vehicular Technology》 (IEEE Trans. Veh. Technol.)

年 卷 期：2025年第74卷第6期

页      面：8694-8706页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0835[工学-软件工程] 0823[工学-交通运输工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China 

主　　题：Differential privacy 

摘      要：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. © 1967-2012 IEEE.