Abstract: Ensuring the integrity of outsourced data in cloud storage remains a critical challenge, especially when existing auditing schemes rely on centralized third-party auditors (TPAs), which introduce single points of failure, privacy leakage risks, and a lack of economic fairness. Current blockchain-based approaches improve transparency but still fail to simultaneously achieve privacy-preserving verification and fair payment between data owners and cloud service providers (CSPs). To address this gap, this study proposes a blockchain-based integrity verification scheme that supports decentralized, privacy-preserving, and economically fair audits for encrypted cloud data. The proposed scheme integrates homomorphic linear authenticators (HLA) and multi-party computation (MPC) to verify data integrity without revealing plaintext, while smart contracts are used to enforce automatic payment or penalty based on audit results, ensuring fairness and accountability. A prototype implementation confirms the practicality of the system. Experimental results show that the audit latency is reduced by up to 35 per cent and smart contract gas consumption by approximately 30 per cent compared to existing schemes, while maintaining low computation and communication overhead. Security analysis demonstrates that the scheme provides data integrity, privacy protection, fairness, and resistance to replay and collusion attacks. Overall, this work offers a practical and scalable solution for secure cloud storage auditing.

Li Zhenxiang, Jin Yuanrong and Mohammad Nazir Ahmad. “A Blockchain-Based Privacy-Preserving Scheme for Integrity Verification and Fair Payment in Cloud Data Storage”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.1 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170135

@article{Zhenxiang2026,
title = {A Blockchain-Based Privacy-Preserving Scheme for Integrity Verification and Fair Payment in Cloud Data Storage},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170135},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170135},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {1},
author = {Li Zhenxiang and Jin Yuanrong and Mohammad Nazir Ahmad}
}