IEEE 3127:2025

New IEEE Standard - Active - Draft.
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 use of data, withdrawing use of data, and potentially sell data under specified conditions.

This guide specifies an architectural framework and application guidelines for Blockchain based Federated Machine Learning, including: 1) a description and a definition of Blockchain-based Federated Machine Learning, 2) the types of Federated Machine Learning for Blockchain-based Federated Machine Learning, 3) application scenarios for each type, 4) a definition of the levels of competency for blockchain based federated learning and guidelines for certifying these systems, 5) Security and privacy requirements of blockchain based federated learning, and 6) performance evaluations of Blockchain-based Federated Machine Learning in real application systems.
The purpose of this document is to provide guidance for improving the security auditability and traceability of Blockchain-based Federated Machine Learning. 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 requirements. 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 use of data, withdrawing use of data and potentially sell data under specified conditions.