Privacy-Preserving Cross-Zone Ride-Matching for Online Ride-Hailing Service

Hui Ma, Yuan Ping, Yong Zhang and Wen-Tsao Pan

Mathematical Problems in Engineering, 2022, vol. 2022, 1-7

Abstract: Although online ride-hailing supplies the nearest taxi matching for riders, the potential leakage of riders’ hobbies and physical condition raises privacy concerns. Since most of the privacy-preserving schemes do limited matching of riders and drivers in the same zone, in this paper, we propose a novel privacy-preserving cross-zone ride-matching scheme, namely, Cride, which extends one zone into multiple neighboring zones. Based on the zone division of a city, CRide allows distance computation between rider and driver across adjacent zones in the encrypted domain. Furthermore, towards efficiency improvement, a ciphertext packing technique is introduced. Theoretical analysis and experimental results suggest that CRide achieves a high ride-matching accuracy and acceptable efficiency without leaking privacy.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:5040766

DOI: 10.1155/2022/5040766

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