A Blockchain-Empowered Arbitrable Multimedia Data Auditing Scheme in IoT Cloud Computing

Shenling Wang, Yifang Zhang and Yu Guo
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Shenling Wang: School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China
Yifang Zhang: School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China
Yu Guo: School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China

Mathematics, 2022, vol. 10, issue 6, 1-17

Abstract: As increasing clients tend to outsource massive multimedia data generated by Internet of Things (IoT) devices to the cloud, data auditing is becoming crucial, as it enables clients to verify the integrity of their outsourcing data. However, most existing data auditing schemes cannot guarantee 100% data integrity and cannot meet the security requirement of practical multimedia services. Moreover, the lack of fair arbitration leads to clients not receiving compensation in a timely manner when the outsourced data is corrupted by the cloud service provider (CSP). In this work, we propose an arbitrable data auditing scheme based on the blockchain. In our scheme, clients usually only need to conduct private audits, and public auditing by a smart contract is triggered only when verification fails in private auditing. This hybrid auditing design enables clients to save audit fees and receive compensation automatically and in a timely manner when the outsourced data are corrupted by the CSP. In addition, by applying the deterministic checking technique based on a bilinear map accumulator, our scheme can guarantee 100% data integrity. Furthermore, our scheme can prevent fraudulent claims when clients apply for compensation from the CSP. We analyze the security strengths and complete the prototype’s implementation. The experimental results show that our blockchain-based data auditing scheme is secure, efficient, and practical.

Keywords: data auditing; data integrity; bilinear map accumulator; blockchain; smart contract (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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