A Blockchain-Based Privacy-Preserving Healthcare Data Sharing Scheme for Incremental Updates

Lianhai Wang, Xiaoqian Liu,Wei Shao, Chenxi Guan, Qihao Huang,Shujiang Xu,Shuhui Zhang, Chin-Ling Chen

SYMMETRY-BASEL(2024)

引用 0|浏览0
暂无评分
摘要
With the rapid development of artificial intelligence (AI) in the healthcare industry, the sharing of personal healthcare data plays an essential role in advancing medical AI. Unfortunately, personal healthcare data sharing is plagued by challenges like ambiguous data ownership and privacy leakage. Blockchain, which stores the hash of shared data on-chain and ciphertext off-chain, is treated as a promising approach to address the above issues. However, this approach lacks a flexible and reliable mechanism for incremental updates of the same case data. To avoid the overhead of authentication, access control, and rewards caused by on-chain data changes, we propose a blockchain and trusted execution environment (TEE)-based privacy-preserving sharing scheme for healthcare data that supports incremental updates. Based on chameleon hash and TEE, the scheme achieves reliable incremental updates and verification without changing the on-chain data. In the scheme, for privacy concerns, off-chain data are protected through symmetric encryption, whereas data verification, decryption, and computation are performed within TEE. The experimental results show the feasibility and effectiveness of the proposed scheme.
更多
查看译文
关键词
blockchain,healthcare data sharing,incremental update,privacy protection,TEE
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要