P2986 - Recommended Practice for Privacy and Security for Federated Machine Learning
Project Details
This document provides recommended practices related to privacy and security for Federated Machine Learning, including security and privacy principles, defense mechanisms against non-malicious failures and examples of adversarial attacks on a Federated Machine Learning system. This document also defines an assessment framework to determine the effectiveness of a given defense mechanism under various settings.
Sponsor Committee
Joint Sponsors
Par Approval
Pars
Working Group Details
Working Group
Sponsor Committee
Society
IEEE Program Manager