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Blockchain-Based Data Preservation System for Medical Data
Abstract
Medical care has become an indispensable part of people's lives, with a dramatic increase in the volume of medical data (e.g., diagnosis certificates and medical records). Medical data, however, is easily stolen, tampered with, or even completely deleted. If the above occurs, medical data cannot be recorded or retrieved in a reliable manner, resulting in delay treatment progress, even endanger the patient's life. In this paper, we propose a novel blockchain-based data preservation system (DPS) for medical data. To provide a reliable storage solution to ensure the primitiveness and verifiability of stored data while preserving privacy for users, we leverage the blockchain framework. With the proposed DPS, users can preserve important data in perpetuity, and the originality of the data can be verified if tampering is suspected. In addition, we use prudent data storage strategies and a variety of cryptographic algorithms to guarantee user privacy; e.g., an adversary is unable to read the plain text even if the data are stolen. We implement a prototype of the DPS based on the real world blockchain-based platform Ethereum. Performance evaluation results demonstrate the effectiveness and efficiency of the proposed system.
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In the citing paper
“Data integrity was enhanced by storing hashed medical data or hash pointer on chain [49,41,38].”
From Blockchain in healthcare and health sciences—A scoping review (2020) · cites this paper as [49]
In the citing paper
“Blockchain technology [8] which uses a shared, immutable, and transparent ledger has a great potential to solve the issues of real-time data access, vulnerability, data fragmentation, lack of traceability, security, and privacy which exist in the current client-server architecture.”
From Lightweight blockchain for healthcare (2019) · cites this paper as [8]
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Metadata
- Authors
- Li, H., Zhu, L., Shen, M., Gao, F., Tao, X., & Liu, S.
- Affiliations
- Beijing Institute of Technology (CN)
- Guilin University of Electronic Technology (CN)
- Corresponding author
- Shen, Meng
- Venue
- Journal of Medical Systems
- Published
- 2018-06-28
- Volume
- 42
- Issue
- 8
- Pages
- 141-141
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- OpenAlex
- W2810381494
- Cited by
- 347
- References
- 28
- Citations by year
- 2026: 12 · 2025: 30 · 2024: 40 · 2023: 56 · 2022: 69 · 2021: 56 · 2020: 47 · 2019: 34 · 2018: 3
- FWCI
- 56.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Medical Systems (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Guangxi Cooperative Innovation Center of cloud computing and Big Data (No.YD16E14)
- National Science Foundation of China under Grant (61602039)
- CCF-Venustech Open Research Fund
- BIT-UMF research and development fund
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Keywords
- blockchain, medical records, data tamper detection, data integrity verification, data privacy, cryptographic algorithms, Ethereum, data storage strategies, data theft
- MeSH terms
- Algorithms, Humans, Computer Security, Privacy, Electronic Health Records
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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