Pedaling Gossips: Towards Location-Privacy-Preserved Data Sharing with Smart Bicycles

Smart bicycles are capable of collecting valuable data through onboard sensors and utilizing this information to derive insights, such as assessing road quality. Sharing data among bicycles or with a server can offer valuable collective insights, in other words, high utility. However, it poses the risk of exposing sensitive location information from location-tagged data, thereby compromising location privacy. Such data sharing schemes lack privacy-aware methods, and metrics to quantify their impact on location privacy and utility. By leveraging bicycle-to-bicycle (B2B) communication, we propose Pedaling Gossips, a novel gossip-based dissemination scheme which balances location privacy and utility, in the context of road quality monitoring using smart bicycles. Our method allows bicycles to gossip road quality data through strategic dissemination of selected information, optimized via a genetic algorithm. We evaluate the impact of our method on location privacy using a new metric. Our results show that the proposed gossiping strategy enhances location privacy by up to 75% compared to a baseline, and approaches the performance of an oracle. This work demonstrates an effective approach for location-privacy-aware B2B data sharing and marks a step towards privacy-preserving mobile crowdsensing.