Lightweight Privacy-Preserving Ride-Sharing Protocols for Autonomous Cars

Abstract

Ride-sharing is a popular way of transportation that reduces traffic and the costs of the trip. Emerge of autonomous vehicles makes ride-sharing more popular because these vehicles do not require a driver's effort. Therefore, in order to find a suitable ride-share, the service provider is not restricted to the driver's trip. Thus, the autonomous cars are more flexible with matching the passengers. Passengers who want to participate in car-sharing send their trip data to a ride-sharing service provider. However, the passenger's trip data contains sensitive information about the passenger's locations. Multiple studies show that a person's location data can reveal personal information about them, e.g., their health condition, home, work, hobbies, and financial situation. In this paper, we propose a lightweight privacy-preserving ride-sharing protocol for autonomous cars. Contrary to previous works on this topic, our protocol does not rely on any extra party to guarantee privacy and security. Our protocol consists of two main phases: i) privacypreserving group forming, and ii) privacy-preserving fair pick-up point selection. In addition to ride-sharing, the two phases of our protocol can also be applied to other use cases. We have implemented our protocol for a realistic ride-sharing scenario, where 1000 passengers simultaneously request a ride-share. Our evaluation results show that the time and communication costs of our protocol are such that it is feasible for real-world applications.