The Poisson binomial mechanism for secure and private federated learning. (arXiv:2207.09916v1 [cs.CR])

We introduce the Poisson Binomial mechanism (PBM), a discrete differential
privacy mechanism for distributed mean estimation (DME) with applications to
federated learning and analytics. We provide a tight analysis of its privacy
guarantees, showing that it achieves the same privacy-accuracy trade-offs as
the continuous Gaussian mechanism. Our analysis is based on a novel bound on
the R\'enyi divergence of two Poisson binomial distributions that may be of
independent interest.

Unlike previous discrete DP schemes based on additive noise, our mechanism …

arxiv binomial federated learning learning