Paper
7 August 2024 Electronic medical record sharing scheme based on searchable attribute encryption in blockchain
Ou Ruan, Cheng Zhang
Author Affiliations +
Proceedings Volume 13224, 4th International Conference on Internet of Things and Smart City (IoTSC 2024); 132241W (2024) https://doi.org/10.1117/12.3035023
Event: 4th International Conference on Internet of Things and Smart City, 2024, Hangzhou, China
Abstract
In the medical field, the rapid development of cloud computing has brought many advantages to medical record data sharing. However, there are still problems such as lack of patient control over personal medical record data, privacy leakage and inefficient sharing. To address these challenges, an electronic medical record sharing scheme based on searchable attribute encryption in blockchain is proposed. Based on the attribute encryption algorithm, the scheme allows patients to independently set their medical record access policies according to their personal needs, realizes fine-grained access control of medical record data, and combines blockchain and searchable encryption technology to realize the multi-keyword search function, which improves the security and search efficiency of medical record data. Secondly the scheme designs an attribute revocation algorithm so that users can update the sharing privileges in time to ensure the security and privacy of medical record data. Finally, after security analysis and experimental verification, the scheme is able to realize the secure sharing of patients' personal electronic medical records with low computational overhead under the premise of protecting patients' privacy.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Ou Ruan and Cheng Zhang "Electronic medical record sharing scheme based on searchable attribute encryption in blockchain", Proc. SPIE 13224, 4th International Conference on Internet of Things and Smart City (IoTSC 2024), 132241W (7 August 2024); https://doi.org/10.1117/12.3035023
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KEYWORDS
Blockchain

Clouds

Computer security

Data privacy

Data modeling

Medicine

Surgery

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