A blockchain-orchestrated Federated Learning architecture for healthcare consortia
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Abstract (arXiv)
We propose a novel architecture for federated learning within healthcare consortia. At the heart of the solution is a unique integration of privacy preserving technologies, built upon native enterprise blockchain components available in the Ethereum ecosystem. We show how the specific characteristics and challenges of healthcare consortia informed our design choices, notably the conception of a new Secure Aggregation protocol assembled with a protected hardware component and an encryption toolkit native to Ethereum. Our architecture also brings in a privacy preserving audit trail that logs events in the network without revealing identities.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Oct 2019.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 3.
8 papers.
- 2022Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directionscited by 35
- 2021A Systematic Survey of Blockchained Federated Learningcited by 15
- 2022Incentive Mechanism Design for Joint Resource Allocation in Blockchain-based Federated Learningcited by 13
- 2024Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learningcited by 9
- 2023Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchaincited by 5
- 2023FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attackscited by 4
- 2024Decentralized Intelligence Network (DIN)cited by 2
- 2024Decentralized Health Intelligence Network (DHIN)cited by 0
- 2024Decentralized Health Intelligence Network (DHIN)12 Aug 2024
- 2024Decentralized Intelligence Network (DIN)2 Jul 2024
- 2024Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning28 Mar 2024
- 2023FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks3 Oct 2023
- 2023Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain27 Feb 2023
- 2022Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions5 Aug 2022
- 2022Incentive Mechanism Design for Joint Resource Allocation in Blockchain-based Federated Learning18 Feb 2022
- 2021A Systematic Survey of Blockchained Federated Learning5 Oct 2021