TY - GEN
T1 - TrustPHR:Trustworthy Management and Shared Utilization of PHR Based on Blockchain
AU - Zhao, Fei
AU - Wang, Yuhan
AU - Zang, Tianyi
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - The sharing application of personal health records (PHR) faces security challenges such as data breaches, tampering risks, and lack of trust. To address these issues, this paper proposes a blockchain-based model for trustworthy management and sharing of PHR, called TrustPHR, ensuring credible traceability and secure sharing throughout the entire lifecycle of PHR. The model integrates the high security, anti-tampering features, and efficient consensus mechanisms of the Algorand blockchain, and utilizes IPFS distributed storage to achieve efficient storage and rapid retrieval of massive medical data, and own algorithms, thereby constructing a decentralized, verifiable PHR management system. The experimental results demonstrate that, in a typical 10000 transactions, this model achieves approximately a 10-fold improvement in data traceability efficiency compared to traditional methods, while simultaneously reducing system resource consumption by 50%. This provides a feasible and high-performance solution for the trustworthy sharing of healthcare data.
AB - The sharing application of personal health records (PHR) faces security challenges such as data breaches, tampering risks, and lack of trust. To address these issues, this paper proposes a blockchain-based model for trustworthy management and sharing of PHR, called TrustPHR, ensuring credible traceability and secure sharing throughout the entire lifecycle of PHR. The model integrates the high security, anti-tampering features, and efficient consensus mechanisms of the Algorand blockchain, and utilizes IPFS distributed storage to achieve efficient storage and rapid retrieval of massive medical data, and own algorithms, thereby constructing a decentralized, verifiable PHR management system. The experimental results demonstrate that, in a typical 10000 transactions, this model achieves approximately a 10-fold improvement in data traceability efficiency compared to traditional methods, while simultaneously reducing system resource consumption by 50%. This provides a feasible and high-performance solution for the trustworthy sharing of healthcare data.
KW - Blockchain
KW - Data security
KW - IPFS
KW - PHR
KW - Trustworthy management
UR - https://www.scopus.com/pages/publications/105040347284
U2 - 10.1007/978-981-95-7254-0_36
DO - 10.1007/978-981-95-7254-0_36
M3 - 会议稿件
AN - SCOPUS:105040347284
SN - 9789819572533
T3 - Communications in Computer and Information Science
SP - 484
EP - 499
BT - Computer Science and Education. AI Technology Frontiers - 19th International Conference, ICCSE 2025, Proceedings
A2 - Hong, Wenxing
A2 - Cui, Binyue
A2 - Weng, Yang
A2 - Li, Chao
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th International Conference on Computer Science and Education, ICCSE 2025
Y2 - 19 August 2025 through 24 August 2025
ER -