P2 Ride : Practical and Privacy-Preserving Ride-Matching Scheme for Ridesharing

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)3584-3593
Number of pages10
Journal / PublicationIEEE Transactions on Intelligent Transportation Systems
Volume24
Issue number3
Online published17 Nov 2022
Publication statusPublished - Mar 2023

Abstract

As a popular instance of sharing economy, ridesharing has been widely adopted in recent years. To use the convenient ridesharing service, riders and drivers have to share with the service provider their private trip information, which impedes users from freely enjoying the benefits of ridesharing. However, existing studies in ridesharing mainly focus on the optimization of rider-driver matching but ignore the protection of privacy of users. In this paper, we propose P2 Ride, a Practical and Privacy-preserving Ride-matching scheme for ridesharing, which enables the service provider to efficiently match drivers with appropriate riders without learning the privacy of both drivers and riders. In P2 Ride, we first convert the complex ride-matching computation into equality testing by leveraging overlapping partition systems, and then achieve the privacy-preserving ride-matching by designing a novel non-interactive private equality testing protocol. We prove the security of the proposed P2 Ride theoretically. Moreover, a prototype of the P2 Ride is implemented, and the experiment results over a real-world dataset demonstrate that the proposed P2 Ride can achieve both high ride-matching accuracy and practical efficiency.

Research Area(s)

  • location privacy, Privacy, privacy-preserving, Protocols, Prototypes, ride-matching, Ridesharing, Servers, Testing, Threat modeling, Urban areas

Citation Format(s)

P2 Ride: Practical and Privacy-Preserving Ride-Matching Scheme for Ridesharing. / Luo, Yuchuan; Fu, Shaojing; Jia, Xiaohua et al.
In: IEEE Transactions on Intelligent Transportation Systems, Vol. 24, No. 3, 03.2023, p. 3584-3593.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review