In this paper, we aim at developing a privacy-preserving service to compute meeting points in ridesharing, such that each user remains in control of his location data. More precisely, we propose a decentralized architecture that provides strong security and privacy guarantees without sacrificing the usability of ridesharing services. In particular, our approach protects the privacy of location data. Following the privacy-by-design principle, we have integrated existing privacy enhancing technologies and multimodal shortest path algorithms to privately compute mutually interesting meeting points for both driver and rider in ridesharing. In addition, we have built a prototype implementation of the proposed approach. The experiments, conducted on real transportation network, have demonstrated that it is possible to reach a trade-off in which both privacy and efficiency are acceptable.
In TRC – Emerging Technologies