Privbus: A privacy-enhanced crowdsourced bus service via fog computing

Abstract

Crowdsourced bus service provides the customized bus for a group of users with similar itineraries by designing the route based on the users’ trip plans. With crowdsourced bus service, the users with similar trips can enjoy the customized bus route efficiently and inexpensively. However, serious privacy concerns (e.g., the exposure of users’ current and future locations) have become a major barrier. To protect users’ itineraries, we propose Privbus, a privacy-enhanced crowdsourced bus service without hampering the functionality of bus route planning. Specifically, Privbus improves the performance of clustering itineraries due to the assistance of fogs. Then, Privbus executes the fog-assisted density peaks clustering operations on ciphertexts of users’ travel plans to protect the users’ trips. By doing so, the clustering operation is removed from users’ smart devices to fog nodes, so as to enable the users to be offline after they submit their travel plans. According to the clustering results, Privbus uses a route planning method to optimize the bus routes. The optimization reduces the time cost on travel of users, while guaranteeing the good profit and the wide coverage of crowdsourced bus service. Finally, through the performance evaluation and extensive experiments, we demonstrate that Privbus has the advantage of low computational and communication overhead, while providing high security and precision guarantees.