A hybrid blockchain-based solution for secure sharing of electronic medical record data

被引:0
作者
Han, Gang [1 ,2 ,3 ]
Ma, Yan [3 ]
Zhang, Zhongliang [1 ]
Wang, Yuxin [3 ]
机构
[1] School of Management, Hangzhou Dianzi University, Zhejiang, Hangzhou
[2] The State Key Laboratory of Integrated Service Networks, Xidian University, Shaanxi, Xi’an
[3] The School of Cyberspace Security, Xi’an University of Posts and Telecommunications, Shaanxi, Xi’an
基金
中国国家自然科学基金;
关键词
Blockchain; Data classification; Digital signature; Electronic medical records;
D O I
10.7717/PEERJ-CS.2653
中图分类号
学科分类号
摘要
Patient privacy data security is a pivotal area of research within the burgeoning field of smart healthcare. This study proposes an innovative hybrid blockchain-based framework for the secure sharing of electronic medical record (EMR) data. Unlike traditional privacy protection schemes, our approach employs a novel tripartite blockchain architecture that segregates healthcare data across distinct blockchains for patients and healthcare providers while introducing a separate social blockchain to enable privacy-preserving data sharing with authorized external entities. This structure enhances both security and transparency while fostering collaborative efforts across different stakeholders. To address the inherent complexity of managing multiple blockchains, a unique cross-chain signature algorithm is introduced, based on the Boneh-Lynn-Shacham (BLS) signature aggregation technique. This algorithm not only streamlines the signature process across chains but also strengthens system security and optimizes storage efficiency, addressing a key challenge in multi-chain systems. Additionally, our external sharing algorithm resolves the prevalent issue of medical data silos by facilitating better data categorization and enabling selective, secure external sharing through the social blockchain. Security analyses and experimental results demonstrate that the proposed scheme offers superior security, storage optimization, and flexibility compared to existing solutions, making it a robust choice for safeguarding patient data in smart healthcare environments. © 2025 Han et al.
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