Dec 7, 2023 · We demonstrate that FreqFed can mitigate poisoning attacks effectively with a negligible impact on the utility of the aggregated model.

Abstract—Federated learning (FL) is a collaborative learning paradigm allowing multiple clients to jointly train a model without sharing their training data ...

FreqFed is presented, a novel aggregation mechanism that transforms the model updates into the frequency domain, where it is demonstrated that FreqFed can ...

We demonstrate that FreqFed can mitigate poisoning attacks effectively with a negligible impact on the utility of the aggregated model. similar · inspect. - ...

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning. H. Fereidooni, A. Pegoraro, P. Rieger, A. Dmitrienko, ...

Feb 13, 2024 · FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning. January 2024. January 2024. DOI:10.14722 ...

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning ... Mitigating Backdoor Attacks in Federated Learning ...

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning ... Method with Stringent Defense Against Poisoning Attacks.

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning. H Fereidooni, A Pegoraro, P Rieger, A Dmitrienko, AR ...

This paper proposes an attack mitigation approach in which a "clean" model can be trained despite the existence of a poisoning attempt.