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IEEE Guide for an Architectural Framework for Blockchain‐Based Federated Machine Learning
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.
Keywords: blockchain, federated machine learning, FML, IEEE 3127™
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