IEEE Guide for Framework for Trustworthy Federated Machine Learning
2024
The development and application of federated machine learning are facing the critical challenges of balancing the tradeoff among privacy, security, performance, and efficiency, how to realize supervision covering the whole life cycle, and how to get explainable results. Thus, trustworthy federated machine learning is proposed to solve the above problem. In this standard, a general view of 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. Also provided is guidance on how trustworthy federated machine learning is used in various scenarios.