TY - JOUR
T1 - lpRide
T2 - Lightweight and Privacy-Preserving Ride Matching Over Road Networks in Online Ride Hailing Systems
AU - Yu, Haining
AU - Shu, Jiangang
AU - Jia, Xiaohua
AU - Zhang, Hongli
AU - Yu, Xiangzhan
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
KW - Online ride hailing
KW - privacy-preserving
KW - online ride matching
KW - road distance
KW - road network embedding
UR - http://www.scopus.com/inward/record.url?scp=85077745085&partnerID=8YFLogxK
UR - http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000501358800007
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85077745085&origin=recordpage
U2 - 10.1109/TVT.2019.2941761
DO - 10.1109/TVT.2019.2941761
M3 - RGC 21 - Publication in refereed journal
SN - 0018-9545
VL - 68
SP - 10418
EP - 10428
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 11
M1 - 8842607
ER -
