ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy. (arXiv:2308.12210v2 [cs.LG] UPDATED)

Differentially Private Federated Learning (DP-FL) has garnered attention as a
collaborative machine learning approach that ensures formal privacy. Most DP-FL
approaches ensure DP at the record-level within each silo for cross-silo FL.
However, a single user's data may extend across multiple silos, and the desired
user-level DP guarantee for such a setting remains unknown. In this study, we
present Uldp-FL, a novel FL framework designed to guarantee user-level DP in
cross-silo FL where a single user's data may belong to …

attention data differential privacy federated federated learning guarantee machine machine learning may privacy private record silos single the record