Blockchain-based Bidirectional Updates on Fine-grained Medical Data
This addresses privacy and consistency issues in medical data sharing for patients, doctors, and researchers, but appears incremental as it builds on existing blockchain and data slicing concepts.
The paper tackles the problem of securely sharing and updating fine-grained medical data among stakeholders by proposing a blockchain-based architecture that uses smart contracts for permission control and bidirectional transformations to synchronize data slices, promising to protect privacy and improve search efficiency.
Electronic medical data sharing between stakeholders, such as patients, doctors, and researchers, can promote more effective medical treatment collaboratively. These sensitive and private data should only be accessed by authorized users. Given a total medical data, users may care about parts of them and other unrelated information might interfere with the user interested data search and increase the risk of exposure. Besides accessing these data, users may want to update them and propagate to other sharing peers so that all peers keep identical data after each update. To satisfy these requirements, in this paper we propose a medical data sharing architecture that addresses the permission control using smart contracts on the blockchain and splits data into fined grained pieces shared with different peers then synchronize full data and these pieces with bidirectional transformations. Medical data reside on each userś local database and permission related data are stored on smart contracts. Only all peers have gained the newest shared data after updates can they start to do next operations on it, which are enforced by smart contracts. Blockchain based immutable shared ledge enables users to trace data updates history. This paper can provide a new perspective to view full medical data as different slices to be shared with various peers but consistency after updates between them are still promised, which can protect the privacy and improve data search efficiency.