FedPerm: Private and Robust Federated Learning by Parameter Permutation. (arXiv:2208.07922v1 [cs.LG])

Federated Learning (FL) is a distributed learning paradigm that enables
mutually untrusting clients to collaboratively train a common machine learning
model. Client data privacy is paramount in FL. At the same time, the model must
be protected from poisoning attacks from adversarial clients. Existing
solutions address these two problems in isolation. We present FedPerm, a new FL
algorithm that addresses both these problems by combining a novel intra-model
parameter shuffling technique that amplifies data privacy, with Private
Information Retrieval (PIR) …

federated learning lg parameter