Published: 2026-08-13 · Last modified: 2026-08-15
DOI: 10.1109/TDSC.2026.3724153
Blockchain FMLE Data Sharing Integrity Audit Deduplication Data Security Smart Healthcare
Projects: 2023YFB3107103 62332005 62262073
Cloud storage increasingly uses deduplication to reduce costs, while users require strong confidentiality and integrity for outsourced data—especially in healthcare, where sensitive, redundant data is frequently shared under strict privacy constraints. Although Message-Locked Encryption (MLE) supports encrypted deduplication, existing methods focus on exact duplicates and assume trusted auditors, making them unsuitable for medical use. We propose MediChainAudit, a blockchain-based system for medical clouds that integrates: (i) an enhanced encryption mode enabling fuzzy (similarity-aware) block-level deduplication, (ii) a decentralized public audit framework removing the need for trusted third parties, and (iii) a secure key-exchange and sharing protocol. Using a hybrid storage model—on-chain integrity tags and off-chain ciphertext—the system minimizes blockchain overhead while supporting verifiable secure deletion. We formalize security goals including PRV-CDA confidentiality, integrity, ownership consistency, and deduplication correctness, providing proofs under standard cryptographic assumptions. To our knowledge, MediChainAudit is the first blockchain-based solution to integrate fuzzy deduplication auditing, secure sharing, and side-channel attack defense with proven PRV-CDA security.
@ARTICLE{ZHANGTDSC26,
author = {Jie Zhang and
Xiaohong Li and
Ruitao Feng and
Shanshan Xu and
Yongyang Lv and
Zhe Hou and
Guangdong Bai},
title = {MediChainAudit: Encrypted Medical Data Auditing on Blockchain with Fuzzy Deduplication and Secure Sharing},
journal = {{IEEE} Trans. Dependable Secur. Comput.},
volume = {},
number = {},
pages = {1--17},
year = {2026},
url = {https://doi.org/10.1109/TDSC.2025.3609801},
doi = {10.1109/TDSC.2026.3724153},
timestamp = {Sun, 08 Feb 2026 16:49:23 +0100},
biburl = {https://dblp.org/rec/journals/tdsc/ZhangLFXLHB26.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}