A Blockchain-based Data Sharing Marketplace with a Federated Learning Use Case
Abstract
Due to the sharp growth of employing mobile devices and IoT (Internet of Things) sensors in daily life, tremendous generated or collected data become one of the most valuable assets for not only users but also numerous applications, which provide various services using user data. However, a large portion of such data is possessed by only a few giant companies in a centralized manner. This incurs the concerns of how user data are harnessed and used and who can use such data because of many cases of privacy violence and data leakage. Therefore, in this paper, we propose a decentralized data sharing marketplace using Ethereum to enable users to share their data in a privacy-preserving and self-governing manner. Users can only share parts of the data from their devices they want to share in the marketplace and gain rewards from the bidding of buyers anonymously. Furthermore, a federated learning use case is demonstrated as a privacy-enhanced application of the proposed marketplace to encourage users to share processed data to avoid raw data leakage.
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Federated learning's model updates do not reveal the raw data from which they were derived.
“These updates do not reveal the raw data from which they were derived, further fortifying data privacy [57].”
From Federated learning meets blockchain in decentralized data-sharing: Healthcare use case (2024) · cites this paper as [57]
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References 4 · Cited by 5
- Authors
- Zhou, Z., Guo, C., Zhang, X., Wang, R., Zhang, L., & Imran, M.
- Affiliations
- University of Glasgow (GB)
- Venue
- 2023 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)
- Publisher
- IEEE
- Published
- 2023-05-01
- Pages
- 1041-1044
- OpenAlex
- W4384026694
- Cited by
- 5
- References
- 4
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2
- FWCI
- 1.28
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Keywords
- federated learning, Ethereum, decentralized data sharing, privacy preservation, data ownership, data leakage, IoT data
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