Paper 2024/1109

QuickPool: Privacy-Preserving Ride-Sharing Service

Abstract

Online ride-sharing services (RSS) have become very popular owing to increased awareness of environmental concerns and as a response to increased traffic congestion. To request a ride, users submit their locations and route information for ride matching to a service provider (SP), leading to possible privacy concerns caused by leakage of users' location data. We propose QuickPool, an efficient SP-aided RSS solution that can obliviously match multiple riders and drivers simultaneously, without involving any other auxiliary server. End-users, namely, riders and drivers share their route information with SP as encryptions of the ordered set of points-of-interest (PoI) of their route from their start to end locations. SP performs a zone based oblivious matching of drivers and riders, based on partial route overlap as well as proximity of start and end points. QuickPool is in the semi-honest setting, and makes use of secure multi-party computation. We provide security proof of our protocol, perform extensive testing of our implementation and show that our protocol simultaneously matches multiple drivers and riders very efficiently. We compare the performance of QuickPool with state-of-the-art works and observe a run time improvement of 1.6 - 2$\times$, and communication improvement of at least 8$\times$.