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20192026
most citedFedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning

1 citations · 2 across the 6 of their papers we have counts for

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cs.CR2025

On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions

Daniel M. Jimenez-Gutierrez, Yelizaveta Falkouskaya, Jose L. Hernandez-Ramos +3

Federated Learning (FL) is an emerging distributed machine learning paradigm enabling multiple clients to train a global model collaboratively without sharing their raw data. While…