Long-Term Optimal Incentives for Differential-Privacy Federated Learning: A Multi-Stage Game Approach
Differential-privacy federated learning (DP-FL) has emerged as a promising paradigm capable of mitigating the inherent threat of traditional FL architectures that are vulnerable to inferential attacks due to the frequent exchange and updating of model parameters. However, existing DP-FL frameworks often assume that the...