Efficient and Secure Management of Medical Data Sharing Based on Blockchain Technology

In the current landscape of medical data management, processing data across diverse institutions and maximizing their value are paramount. However, traditional methods lack a secure and efficient mechanism for end-to-end traceability and supervision, posing challenges in distributed scenarios lackin...

Full description

Saved in:
Bibliographic Details
Published inApplied sciences Vol. 14; no. 15; p. 6816
Main Authors Mao, Xiangke, Li, Chao, Zhang, Yong, Zhang, Guigang, Xing, Chunxiao
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2024
Subjects
Algorithms
Authenticity
Behavior
Blockchain
blockchain technology
DAG
Data integrity
data management
Data processing
data provenance
Data security
Design
Digital currencies
Efficiency
Energy consumption
Information sharing
Information storage and retrieval
Medical records
Medical research
Pharmaceutical industry
Privacy
R&D
Research & development
China
Online AccessGet full text

Cover

More Information
Summary:In the current landscape of medical data management, processing data across diverse institutions and maximizing their value are paramount. However, traditional methods lack a secure and efficient mechanism for end-to-end traceability and supervision, posing challenges in distributed scenarios lacking mutual trust. Leveraging blockchain’s decentralized, tamper-proof, and traceable features, this paper introduces a blockchain-based medical data management platform. This platform enables full-process management of raw data, operational behaviors, intermediate data, and final data, meeting the needs of trusted storage and supervision of data. We propose two methods, namely, naive method and DAG-based method, to realize forward tracking and backward tracing of medical data stored on the blockchain, respectively. We validated and analyzed the storage and query performance of the medical data management platform on real medical data, and we also conducted experimental analyses on the efficiency of the proposed traceability algorithm under different data scales and processing path lengths. The results demonstrate that our platform and traceability methods effectively meet the management needs of medical data distributed across institutions.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app14156816