Title | An Incentive Mechanism Using Shapley Value for Blockchain-Based Medical Data Sharing |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Zhu, L., Dong, H., Shen, M., Gai, K. |
Conference Name | 2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS) |
Date Published | may |
Keywords | Big Data, blockchain, blockchain-based medical data sharing, Business, compositionality, computational process, cooperation model, cryptocurrencies, data miners, Data models, data owners, data privacy, disease diagnosis, diseases, Distributed databases, game theory, incentive mechanism, incentive schemes, Intelligent Data and Security, Intelligent Data Security, learning (artificial intelligence), machine learning techniques, medical data sharing, Medical diagnostic imaging, medical information systems, Predictive models, pubcrawl, Resiliency, Scalability, security, security of data, Shapley value, Shapley value revenue distribution, topological relationships |
Abstract | With the development of big data and machine learning techniques, medical data sharing for the use of disease diagnosis has received considerable attention. Blockchain, as an emerging technology, has been widely used to resolve the efficiency and security issues in medical data sharing. However, the existing studies on blockchain-based medical data sharing have rarely concerned about the reasonable incentive mechanism. In this paper, we propose a cooperation model where medical data is shared via blockchain. We derive the topological relationships among the participants consisting of data owners, miners and third parties, and gradually develop the computational process of Shapley value revenue distribution. Specifically, we explore the revenue distribution under different consensuses of blockchain. Finally, we demonstrate the incentive effect and rationality of the proposed solution by analyzing the revenue distribution. |
DOI | 10.1109/BigDataSecurity-HPSC-IDS.2019.00030 |
Citation Key | zhu_incentive_2019 |