Privacy-preserving pathological data sharing among multiple remote parties
Article
Wu, Wei, Chen, Fulong, Yuan, Pinghai, Wang, Taochun, Xie, Dong, Zhao, Chuanxin, Wang, Chao, Tang, Detao, Li, Jingtao Li and Zhang, Ji. 2024. "Privacy-preserving pathological data sharing among multiple remote parties." Blockchain: Research and Applications. 5 (3). https://doi.org/10.1016/j.bcra.2024.100204
Article Title | Privacy-preserving pathological data sharing among multiple remote parties |
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Article Category | Article |
Authors | Wu, Wei, Chen, Fulong, Yuan, Pinghai, Wang, Taochun, Xie, Dong, Zhao, Chuanxin, Wang, Chao, Tang, Detao, Li, Jingtao Li and Zhang, Ji |
Journal Title | Blockchain: Research and Applications |
Journal Citation | 5 (3) |
Article Number | 100204 |
Number of Pages | 11 |
Year | 2024 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 2666-9536 |
2096-7209 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.bcra.2024.100204 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S2096720924000174 |
Abstract | The sharing of pathological data is highly important in various applications, such as remote diagnosis, graded diagnosis, illness treatment, and specialist system development. However, ensuring reliable, secure, privacy-preserving, and efficient sharing of pathological data poses significant challenges. This paper presents a novel solution that leverages blockchain technology to ensure reliability in pathological data sharing. Additionally, it employs conditional proxy re-encryption (C-PRE) and public key encryption with equality test technology to control the scope and preserve the privacy of shared data. To assess the practicality of our solution, we implemented a prototype system using Hyperledger Fabric and conducted evaluations with various metrics. We also compared the solution with relevant schemes. The results demonstrate that the proposed solution effectively meets the requirements for pathological data sharing and is practical in production scenarios. |
Keywords | Blockchain; Digital remote pathology; Conditional proxy re-encryption; Data storage; Data sharing |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 461299. Software engineering not elsewhere classified |
Byline Affiliations | Anhui Normal University, China |
University of Southern Queensland |
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https://research.usq.edu.au/item/z9q58/privacy-preserving-pathological-data-sharing-among-multiple-remote-parties
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