Cookies
We need your consent to use the individual data so that you can see information about your interests, among other things. Click "OK" to give your consent.
IEEE 3127-2025
IEEE Guide for an Architectural Framework for Blockchain-Based Federated Machine Learning
Translate name
STANDARD published on 16.4.2025
The information about the standard:
Designation standards: IEEE 3127-2025
Publication date standards: 16.4.2025
SKU: NS-1222455
The number of pages: 40
Approximate weight : 120 g (0.26 lbs)
Country: International technical standard
Category: Technical standards IEEE
Annotation of standard text IEEE 3127-2025 :
New IEEE Standard - Active.
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.
ISBN: 979-8-8557-2004-4, 979-8-8557-2005-1
Number of Pages: 40
Product Code: STD27811, STDPD27811
Keywords: blockchain, federated machine learning, FML, IEEE 3127™
Category: 319
We recommend:
Updating of laws
Do you want to be sure about the validity of used regulations?
We offer you a solution so that you could use valid and updated legislative regulations.
Would you like to get more information? Look at this page.
