An intelligent and privacy-enhanced data sharing strategy for blockchain-empowered Internet of Things |
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| Affiliation: | 1. College of Computer and Cyber Security, Fujian Normal University, Fuzhou, 350117, China;2. Engineering Research Center of Cyber Security and Education Informatization, Fujian Province University, Fuzhou, 350117, China;3. University of Exeter, EX4 4RN Exeter, UK |
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| Abstract: | With the development of the Internet of Things (IoT), the massive data sharing between IoT devices improves the Quality of Service (QoS) and user experience in various IoT applications. However, data sharing may cause serious privacy leakages to data providers. To address this problem, in this study, data sharing is realized through model sharing, based on which a secure data sharing mechanism, called BP2P-FL, is proposed using peer-to-peer federated learning with the privacy protection of data providers. In addition, by introducing the blockchain to the data sharing, every training process is recorded to ensure that data providers offer high-quality data. For further privacy protection, the differential privacy technology is used to disturb the global data sharing model. The experimental results show that BP2P-FL has high accuracy and feasibility in the data sharing of various IoT applications. |
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| Keywords: | Data sharing Federated learning Blockchain Privacy protection IoT |
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