Active PAR

P3187

Guide for Framework for Trustworthy Federated Machine Learning

This guide provides a reference framework for trustworthy Federated Machine Learning. The document provides guidance with respect to provable security for data and models, optimized model utility, controllable communication and computational complexity, explainable decision making and supervised processes. The guide describes three main aspects: 1) principles for trustworthy Federated Machine Learning, 2) requirements for different roles in trustworthy Federated Machine Learning, and 3) techniques to realize trustworthy Federated Machine Learning.

Sponsor Committee
C/AISC - Artificial Intelligence Standards Committee
Status
Active PAR
PAR Approval
2022-06-16

Working Group Details

Society
IEEE Computer Society
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Sponsor Committee
C/AISC - Artificial Intelligence Standards Committee
Working Group
FTFML - Framework for Trustworthy Federated Machine Learning
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IEEE Program Manager
Christy Bahn
Contact
Working Group Chair
Zuping Wu
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