Efficient Dynamic Auditing Scheme for Cloud Data Sharing of Intelligent Connected Fleet

Intelligent connected vehicle fleet driven primarily by cloud data sharing is an efficient and energy-saving organizational model and demonstrates vast application potential in many scenarios. However, as the central hub for data sharing, the cloud platform's untrustworthiness poses severe challenges to the integrity and reliability of shared data. Existing auditing schemes fail to meet the low-latency, lightweight onboard computing, and succinct revocation demands of such fleets. Even with the application of batch auditing, the overall audit latency remains inadequately addressed. In this work, we propose an efficient auditing scheme called Drivora for cloud data sharing of intelligent connected fleet. We achieve secure delegated authenticator computation based on secret sharing and it requires only the master vehicle to perform the initial setup. Moreover, Drivora supports the aggregation of challenged blocks from multiple vehicles to produce a single integrity proof and it enables Drivora to handle multiple audit tasks from different vehicles at the same time. Furthermore, we propose a novel vehicle revocation mechanism. Different from traditional secret sharing-based approaches, Drivora requires only a single secret share to revoke multiple vehicles and achieves lower space complexity. We conduct extensive experimental evaluations of Drivora's performance and benchmark it against state-of-the-art approaches. Compared to conventional batch auditing, our scheme achieves a$2\times$-$107\times$improvement in auditing efficiency and reduces communication overhead by$2\times$-$939\times$. As the number of files increases, our overall auditing cost remains constant.