Blockchain-Based Data Preservation System for Medical Data
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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.
KeywordsData preservation Blockchain Medical data Sensitive data Ethereum
This work was supported in part by the 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 and BIT-UMF research and development fund.
Compliance with Ethical Standards
Conflict of interests
Mr. H. Li declares that he has no conflict of interest. Mr. Z. Lie declares that he has no conflict of interest. Mr. M. Shen declares that he has no conflict of interest. Mr. F. Gao declares that he has no conflict of interest. Ms. X. Tao declares that she has no conflict of interest. Mr. S. Liu declares that he has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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