Giuseppe Caire

Secure Aggregation with Uncoded Groupwise Keys Against User Collusion

2023

In this paper, we study the information theoretic secure aggregation problem, where the server node aims to aggregate K users' locally trained models, without revealing any other information about the users' local data. To ensure …

PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning

2024 · arXiv (Cornell University)

Federated learning (FL) has recently gained significant momentum due to its potential to leverage large-scale distributed user data while preserving user privacy. However, the typical paradigm of FL faces challenges of both privacy and robustness: …