lpRide : Lightweight and Privacy-Preserving Ride Matching Over Road Networks in Online Ride Hailing Systems

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

28 Scopus Citations
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Original languageEnglish
Article number8842607
Pages (from-to)10418-10428
Journal / PublicationIEEE Transactions on Vehicular Technology
Volume68
Issue number11
Online published17 Sep 2019
Publication statusPublished - Nov 2019

Abstract

An Online Ride Hailing (ORH) system enables a rider to request a taxi through a smartphone app on a short notice. To enjoy ORH services, users have to submit their location information to ORH servers. There are serious privacy concerns for users to reveal location information to ORH servers. In this paper, we propose a lightweight and privacy-preserving ride matching scheme for ORH systems, named lpRide, which can find the taxi with the minimum road distance to serve an incoming rider, while protecting the location privacy of both riders and taxis against the ORH server. In lpRide, we propose an efficient shortest road distance computation approach over encrypted data, which computes approximate road distance by using road network embedding and the modified Paillier cryptosystem. Moreover, we design a secure comparison method to compare two distances over the corresponding blinded ciphertexts, without revealing the actual distances. Theoretical analysis and experimental evaluations show that lpRide is private, accurate and efficient.

Research Area(s)

  • Online ride hailing, privacy-preserving, online ride matching, road distance, road network embedding

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