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IEEE Guide for an Architectural Framework for Blockchain‐Based Federated Machine Learning
IEEE Std 3127-2025
Year: 2025
IEEE - The Institute of Electrical and Electronics Engineers, Inc.
Abstract: Guidance for improving the security auditability and traceability of blockchain-based federated machine learning is provided in this document. Blockchain-based federated machine learning helps data owners, producers, consumers, and collaborators to realize multi-party secure computing while meeting applicable interaction, decentralization, safety, reliability, and robustness guidelines. Blockchain-based Federated Machine Learning can improve the privacy of data owners, producers, consumers, and collaborators, and enable those entities to give permission for functions including the use of data, withdrawing the use of data, and potentially selling data under specified conditions.
Subject: federated machine learning
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IEEE Guide for an Architectural Framework for Blockchain‐Based Federated Machine Learning
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| contributor author | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
| date accessioned | 2025-09-30T23:08:22Z | |
| date available | 2025-09-30T23:08:22Z | |
| date copyright | 16 April 2025 | |
| date issued | 2025 | |
| identifier other | 10965995.pdf | |
| identifier uri | https://yse.yabesh.ir/std/handle/yse/348563 | |
| description abstract | Guidance for improving the security auditability and traceability of blockchain-based federated machine learning is provided in this document. Blockchain-based federated machine learning helps data owners, producers, consumers, and collaborators to realize multi-party secure computing while meeting applicable interaction, decentralization, safety, reliability, and robustness guidelines. Blockchain-based Federated Machine Learning can improve the privacy of data owners, producers, consumers, and collaborators, and enable those entities to give permission for functions including the use of data, withdrawing the use of data, and potentially selling data under specified conditions. | |
| language | English | |
| publisher | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
| title | IEEE Guide for an Architectural Framework for Blockchain‐Based Federated Machine Learning | en |
| title | IEEE Std 3127-2025 | num |
| type | standard | |
| page | 40 | |
| tree | IEEE - The Institute of Electrical and Electronics Engineers, Inc.:;2025 | |
| contenttype | fulltext | |
| subject keywords | federated machine learning | |
| subject keywords | FML | |
| subject keywords | IEEE 3127™ | |
| subject keywords | blockchain | |
| identifier DOI | 10.1109/IEEESTD.2025.10965995 |