ELSA: Secure Aggregation for Federated Learning with Malicious Actors

ePrint Report: ELSA: Secure Aggregation for Federated Learning with Malicious Actors

Mayank Rathee, Conghao Shen, Sameer Wagh, Raluca Ada Popa

Federated learning (FL) is an increasingly popular
approach for machine learning (ML) in cases where the train-
ing dataset is highly distributed. Clients perform local training
on their datasets and the updates are then aggregated into
the global model. Existing protocols for aggregation are either
inefficient, or don’t consider the case of malicious actors in the
system. This is a …

eprint report federated learning malicious malicious actors