Location privacy-preserving in online taxi-hailing services

Xiaoying Shen, Licheng Wang, Qingqi Pei, Yuan Liu, Miaomiao Li
2020 Peer-to-Peer Networking and Applications  
Online taxi-hailing has become people's most popular trip mode due to its convenience and low cost. However, it also poses a privacy threat to passengers and drivers, since the online taxi-hailing service providers are able to track their precise mobility trajectories. In addition, there is a certain time delay between the time of a passenger makes a request and the time of the driver arrives the passenger's boarding position in current online taxi-hailing system. To solve these two problems,
more » ... ese two problems, we present a new and efficient location privacy protection scheme based on the MinHash algorithm (LPPM). With the LPPM, the exact positions of passengers and drivers are generalized into a set of points of interest around them, and the distance between them is transformed into the similarity between the two sets. Thus a service provider can efficiently match passengers and drivers by using MinHash algorithm without revealing their specific location information. In this paper, we use mobile edge computing technology in the online taxi-hailing system to address the second challenge. It can speed up data processing, drivers can make decisions in advance and reduce the possibility of road congestion. Security analysis shows that LPPM has high security, and the final experimental results confirmed that LPPM is effective.
doi:10.1007/s12083-020-00982-7 fatcat:sea64tj3knchjbrr3ilmjgtjou