BARM: Blockchain-based Anonymous Reward Mechanism for Medical Recommendation in Smart Healthcare
Hui Wang, Yong Xie, Xing Su, Hehua Yao · 2022
Medical Recommendation Service (MRS) can provide simple diagnostics and recommend a suitable doctor for patients when they input their disease symptoms by using AI and big data. However, people may be unwilling to share medical data due to data privacy issues and a lack of incentives, which makes it hard for MRS to continue to develop. Until now, there are no efficient solutions. To solve this, we propose a blockchain-based anonymous reward mechanism for medical recommendation (BARM) in smart healthcare. The proposed scheme uses accumulator, commitment, and Signatures of Knowledge (SoK) to provide anonymous rewards for users to mobilize more users to share data as much as possible. And we design a smart contract that can provide submit, query, and revoke functions to realize anonymous authentication of patients. The formal security analysis shows that the proposed scheme meets the required security requirements. Detailed performance analysis results show that the computation cost and communication cost of the scheme is feasible, which can be applied to the medical recommendation scenario of anonymous protection and promote the development of smart healthcare.