Mutual-Supervised Federated Learning and Blockchain-Based IoT Data Sharing Article Swipe
Jianwei Liu
,
Qinyang Miao
,
Xinmin Fan
,
Xiaoding Wang
,
Hui Lin
,
Yikun Huang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1155/2022/7003426
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1155/2022/7003426
Due to the decentralized, tamper-proof, and auditable properties of blockchain, more and more scholars and researchers are studying the application of blockchain technology in IoT data sharing. Federated learning is an effective way to enable data sharing, but can be compromised by dishonest data owners who may provide malicious models. In addition, dishonest data requesters may also infer private information from model parameters. To solve the above problems, a secure data sharing mechanism based on mutual-supervised federated learning and blockchain, BPCV-FL, is proposed. This mechanism ensures data privacy by adopting gradient descent algorithm with differential privacy protection in local model training and ensures the reliability of shared data through mutual supervision on the blockchain. Experimental results show that the proposed BPCV-FL has high accuracy and security in IoT data sharing.
Related Topics
Concepts
Blockchain
Computer science
Federated learning
Differential privacy
Data sharing
Reliability (semiconductor)
Computer security
Private information retrieval
Information sharing
Data mining
Distributed computing
World Wide Web
Alternative medicine
Power (physics)
Pathology
Medicine
Quantum mechanics
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.1155/2022/7003426
- https://downloads.hindawi.com/journals/scn/2022/7003426.pdf
- OA Status
- hybrid
- Cited By
- 4
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4303684571
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4303684571Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1155/2022/7003426Digital Object Identifier
- Title
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Mutual-Supervised Federated Learning and Blockchain-Based IoT Data SharingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2022Year of publication
- Publication date
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2022-10-08Full publication date if available
- Authors
-
Jianwei Liu, Qinyang Miao, Xinmin Fan, Xiaoding Wang, Hui Lin, Yikun HuangList of authors in order
- Landing page
-
https://doi.org/10.1155/2022/7003426Publisher landing page
- PDF URL
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https://downloads.hindawi.com/journals/scn/2022/7003426.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://downloads.hindawi.com/journals/scn/2022/7003426.pdfDirect OA link when available
- Concepts
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Blockchain, Computer science, Federated learning, Differential privacy, Data sharing, Reliability (semiconductor), Computer security, Private information retrieval, Information sharing, Data mining, Distributed computing, World Wide Web, Alternative medicine, Power (physics), Pathology, Medicine, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 2, 2023: 1Per-year citation counts (last 5 years)
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23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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