Conditional anonymous remote healthcare data sharing over blockchain

Liu, Jingwei, Jiang, Weiyang, Sun, Rong, Bashir, Ali Kashif ORCID: https://orcid.org/0000-0001-7595-2522, Alshehri, Mohammad Dahman, Hua, Qiaozhi and Yu, Keping (2023) Conditional anonymous remote healthcare data sharing over blockchain. IEEE journal of biomedical and health informatics, 27 (5). pp. 2231-2242. ISSN 2168-2194

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Official URL: https://doi.org/10.1109/JBHI.2022.3183397

Abstract

As an important carrier of healthcare data, Electronic Medical Records (EMRs) generated from various sensors, i.e., wearable, implantable, are extremely valuable research materials for artificial intelligence and machine learning. The efficient circulation of EMRs can improve remote medical services and promote the development of the related healthcare industry. However, in traditional centralized data sharing architectures, the balance between privacy and traceability still cannot be well handled. To address the issue that malicious users cannot be locked in the fully anonymous sharing schemes, we propose a trackable anonymous remote healthcare data storing and sharing scheme over decentralized consortium blockchain. Through an “on-chain & off-chain” model, it relieves the massive data storage pressure of medical blockchain. By introducing an improved proxy re-encryption mechanism, the proposed scheme realizes the fine-gained access control of the outsourced data, and can also prevent the collusion between semi-trusted cloud servers and data requestors who try to reveal EMRs without authorization. Compared with the existing schemes, our solution can provide a lower computational overhead in repeated EMRs sharing, resulting in a more efficient overall performance.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	03 Jan 2023 10:14
Publisher:	IEEE
Additional Information:	© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions:	Faculties > Science and Engineering Research Centres > Centre for Advanced Computational Science
Subject terms:	Humans, Information Dissemination, Confidentiality, Privacy, Computer Security, Artificial Intelligence, Delivery of Health Care, Electronic Health Records, Blockchain, Humans, Blockchain, Computer Security, Confidentiality, Artificial Intelligence, Privacy, Electronic Health Records, Delivery of Health Care, Information Dissemination
URI:	https://e-space.mmu.ac.uk/id/eprint/631060
DOI:	https://doi.org/10.1109/JBHI.2022.3183397
ISSN	2168-2194
e-ISSN	2168-2208

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