Federated $f$-Differential Privacy

22 Feb 2021 Qinqing Zheng Shuxiao Chen Qi Long Weijie J. Su

Federated learning (FL) is a training paradigm where the clients collaboratively learn models by repeatedly sharing information without compromising much on the privacy of their local sensitive data. In this paper, we introduce federated $f$-differential privacy, a new notion specifically tailored to the federated setting, based on the framework of Gaussian differential privacy... (read more)

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