IEEE Approved Draft Guide for an Architectural Framework for Blockchain-based Federated Machine Learning
NORM herausgegeben am 12.3.2025
Bezeichnung normen: IEEE P3127
Ausgabedatum normen: 12.3.2025
Gewicht ca.: 300 g (0.66 Pfund)
Land: Internationale technische Norm
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.
ISBN: 979-8-8557-1329-9, 979-8-8557-1329-9
Number of Pages: 38
Product Code: STDUD27389, STDAPE27389
Keywords: blockchain, federated machine learning, FML, IEEE 3127™
Category: 319
Draft Number: P3127/D0.7, Jun 2024 - UNAPPROVED DRAFT, P3127/D0.7, Jun 2024 - APPROVED DRAFT