22 citations · 26 across the 4 of their papers we have counts for
4 papers
Optimizing Byzantine Node Placement in Decentralized Federated Learning
Edoardo Gabrielli, Gabriele Tolomei
Security evaluations of decentralized federated learning (DFL) typically focus on how Byzantine participants behave, while largely overlooking which participants are compromised. Y…
The Right to Hide: Masking Community Affiliation via Minimal Graph Rewiring
Matteo Silvestri, Edoardo Gabrielli, Fabrizio Silvestri +1
Protecting privacy in social graphs may require obscuring nodes' membership in sensitive communities. However, doing so without significantly disrupting the underlying graph topolo…
A Survey on Decentralized Federated Learning
Edoardo Gabrielli, Anthony Di Pietro, Dario Fenoglio +2
Federated learning (FL) enables collaborative training without pooling raw data, but standard FL relies on a central coordinator, which introduces a single point of failure and con…
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection
Edoardo Gabrielli, Dimitri Belli, Zoe Matrullo +2
Current defense mechanisms against model poisoning attacks in federated learning (FL) systems have proven effective up to a certain threshold of malicious clients. In this work, we…