Multiuser data integrity auditing atop blockchain with secure user revocation for cognitive IoT networks

Cognitive computing over big data has advanced the cognitive Internet of Things (IoT), enhancing adaptive decision-making by the analysis of shared data, while posing challenges in the storage and multi-user sharing of large-scale real-time data. Decentralized cloud storage is a promising solution to reduce latency and prevent single-point failures, but a key factor in preventing erroneous decisions lies in the integrity of shared data. However, integrity auditing in decentralized and shared storage typically involves linear overheads, with revoked users potentially colluding with cloud providers to evade audits. To address these issues, we propose a blockchain-based multiuser data integrity auditing protocol for cognitive IoT, supporting secure user revocation and batch auditing in decentralized storage. Our protocol classifies group users into different categories and manages group users efficiently and dynamically. Besides, files stored across various storage nodes can be audited in batches and effectively updated based on novel block tags. Smart contracts deployed on the blockchain ensure fairness among participants. We formally prove the security of the protocol in the random oracle model and the algebraic group model, in particular, against collusion attacks. Finally, we evaluate the cost separately for on-chain operations and off-chain operations to show its practicality.