The development and application of federated machine learning are facing the critical challenges about how to balance the tradeoff among privacy, security, performance, and efficiency, how to realize supervision covering the whole life cycle and how to get the explainable results. Then trustworthy federated machine learning is proposed to solve the above problem. In this standard, a general view on framework for trustworthy federated machine learning is provided in four parts: a principle in trustworthy federated machine learning, requirements from the perspective of different principles and different federated machine learning participants, and methods to realize trustworthy federated machine learning. It also provides some guidance on how trustworthy federated machine learning is used in various scenarios.
- Standard Committee
- C/AISC - Artificial Intelligence Standards Committee
- Status
- Active Standard
- PAR Approval
- 2022-06-16
- Board Approval
- 2024-09-26
Working Group Details
- Society
- IEEE Computer Society
- Standard Committee
- C/AISC - Artificial Intelligence Standards Committee
- Working Group
-
FT-FML - Framework for Trustworthy Federated Machine Learning
- IEEE Program Manager
- Christy Bahn
Contact Christy Bahn - Working Group Chair
- Zuping Wu
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No Superseded Standards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No Inactive-Withdrawn Standards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