d-EMR: Secure and distributed Electronic Medical Record management

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ehab Zaghloul, Tongtong Li, Jian Ren
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引用次数: 2

Abstract

As more and more data is produced, finding a secure and efficient data access structure has become a major research issue. The centralized systems used by medical institutions for the management and transfer of Electronic Medical Records (EMRs) can be vulnerable to security and privacy threats, often lack interoperability, and give patients limited or no access to their own EMRs. In this paper, we first propose a privilege-based data access structure and incorporates it into an attribute-based encryption mechanism to handle the management and sharing of big data sets. Our proposed privilege-based data access structure makes managing healthcare records using mobile healthcare devices efficient and feasible for large numbers of users. We then propose a novel distributed multilevel EMR (d-EMR) management scheme, which uses blockchain to address security concerns and enables selective sharing of medical records among staff members that belong to different levels of a hierarchical institution. We deploy smart contracts on Ethereum blockchain and utilize a distributed storage system to alleviate the dependence on the record-generating institutions to manage and share patient records. To preserve privacy of patient records, our smart contract is designed to allow patients to verify attributes prior to granting access rights. We provide extensive security, privacy, and evaluation analyses to show that our proposed scheme is both efficient and practical.

d-EMR:安全分布式电子病历管理
随着越来越多的数据被产生,寻找一种安全高效的数据访问结构已成为一个主要的研究问题。医疗机构用于管理和传输电子病历(EMR)的集中式系统可能容易受到安全和隐私威胁,通常缺乏互操作性,并且患者对自己的EMR的访问权限有限或根本无法访问。在本文中,我们首先提出了一种基于权限的数据访问结构,并将其纳入一种基于属性的加密机制中,以处理大数据集的管理和共享。我们提出的基于特权的数据访问结构使使用移动医疗设备管理医疗记录对大量用户来说既高效又可行。然后,我们提出了一种新的分布式多级电子病历(d-EMR)管理方案,该方案使用区块链来解决安全问题,并能够在属于分级机构不同级别的工作人员之间选择性共享医疗记录。我们在以太坊区块链上部署智能合约,并利用分布式存储系统来减轻对记录生成机构管理和共享患者记录的依赖。为了保护患者记录的隐私,我们的智能合约旨在允许患者在授予访问权限之前验证属性。我们提供了广泛的安全、隐私和评估分析,以表明我们提出的方案既有效又实用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.70
自引率
0.00%
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