Fine-grained Passenger-Vehicle Coupling Management for Secure Ride-Sharing Services

Recently, ride-sharing has become an essential service for daily use. Some popular mobile apps have been utilised to match up between a user and a rider. Mobile apps provide mutual location information and private information for checking security levels, such as their profile photos, the rider’s star level, and feedback records about the user. Despite providing such information, frequent mismatching between a user and a vehicle causes severe safety problems. Therefore, this paper proposes a secure coupling scheme between users and riders via fine-grained cyber-physical interaction to prevent getting into the wrong car. The proposed scheme relies on dynamic Bluetooth low energy (BLE) beaconing to provide precise mutual detection between passengers and riders. Smart mobile devices dynamically generate BLE beacon messages to recognise and authenticate each other, and such beaconing is also used to measure the highly accurate distance between them. For mutual beaconing, the scheme deals with frequent switching of the advertising and scanning modes of the Bluetooth channel and their interval. Since passengers and vehicles might continuously move, accurate distance detection is not trivial. So, this scheme considers edge servers to apply various machine learning techniques and filtering schemes to achieve precise detection. Performance evaluations rely on a proof-of-concept prototype, and various field test data are utilised to prove the proposed concept’s performance.