Abstract
Medical data are important in diagnosis, treatment, recovery, and medical accident investigation. The integrity and availability of medical data are the basic guarantee for the smooth operation of these activities. The privacy of medical data is a natural demand from the sensitivity of medical data. At present, there are mainly two ways to protect the privacy of medical data. One way is to store medical data in a local database and set up an access control strategy of the database. The other way is to encrypt medical data with the patient’s key and to share the key when needed. The problem with the first method is that the data in the local database may be modified or deleted. The problem with the second method is that the key cannot be shared when the patient dies during the diagnosis and treatment. These two problems will damage the availability of data. This paper proposes to establish a shared key that could be reconstructed by the legitimate parties before the process of diagnosis and treatment begins. The data in the diagnosis and treatment process is encrypted and stored in a blockchain using the shared key. The proposal meets the integrity, availability and privacy requirements of medical data. It uses the sibling intractable function families (SIFF) to establish a shared key, and uses the Hyperledger Fabric to store encrypted data. The simulation shows that the system has good efficiency. Additionally, it is the first time to introduce SIFF to a blockchain application.
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Acknowledgments
This work is supported by the National Key R&D Program of China (2017YFB0802500), Supported by Guangxi Key Laboratory of Cryptography and Information Security (No.GCIS201711), Natural Science Foundation of China (61672550), Fundamental Research Funds for the Central Universities (No. 17lgjc45).
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This article is part of the Topical Collection on Blockchain-based Medical Data Management System: Security and Privacy Challenges and Opportunities
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Tian, H., He, J. & Ding, Y. Medical Data Management on Blockchain with Privacy. J Med Syst 43, 26 (2019). https://doi.org/10.1007/s10916-018-1144-x
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DOI: https://doi.org/10.1007/s10916-018-1144-x