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.
Working Group Details
- IEEE Computer Society
Learn More About IEEE Computer Society
- Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Working Group
BFML - Blockchain-based Federated Machine Learning
Learn More About BFML - Blockchain-based Federated Machine Learning
- IEEE Program Manager
- Christy Bahn
Contact Christy Bahn
- Working Group Chair
- Ye Ouyang
Other Activities From This Working Group
Current projects that have been authorized by the IEEE SA Standards Board to develop a standard.
No Active Projects
Standards approved by the IEEE SA Standards Board that are within the 10-year lifecycle.
No Active Standards
These standards have been replaced with a revised version of the standard, or by a compilation of the original active standard and all its existing amendments, corrigenda, and errata.
No Superseded Standards
These standards have been removed from active status through a ballot where the standard is made inactive as a consensus decision of a balloting group.
No Inactive-Withdrawn Standards
These standards are removed from active status through an administrative process for standards that have not undergone a revision process within 10 years.
No Inactive-Reserved Standards