Oct 14, 2022 · This paper presents a novel defense mechanism, CrowdGuard, that effectively mitigates backdoor attacks in FL and overcomes the deficiencies of ...
Abstract—Federated Learning (FL) is a promising approach enabling multiple clients to train Deep Neural Networks (DNNs).
To mitigate the privacy risk and prevent the feedback-loop from allowing malicious clients to perform inference attacks on the received local models, CrowdGuard ...
A novel defense mechanism, CrowdGuard, is presented that effectively mitigates backdoor attacks in FL and overcomes the deficiencies of existing techniques ...
Crowdguard: Federated backdoor detection in federated learning. P Rieger, T Krauß, M Miettinen, A Dmitrienko, AR Sadeghi. NDSS, 2024. 11*, 2024. FedCRI ...
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CrowdGuard: Federated Backdoor Detection in Federated Learning. T. Krauß, P. Rieger, M. Miettinen, A. Dmitrienko, and A. Sadeghi.
CrowdGuard is proposed, a model defense that mitigates backdoor attacks by leveraging the clients' data to analyze the individual models before the ...
Crowdguard: Federated backdoor detection in federated learning. P Rieger, T Krauß, M Miettinen, A Dmitrienko, AR Sadeghi. NDSS, 2024. 11*, 2024. FedCRI ...
CrowdGuard: Federated Backdoor Detection in Federated Learning ... However, FL is susceptible to backdoor (or targeted poisoning) attacks. Federated Learning ...
CrowdGuard: Federated Backdoor Detection in Federated Learning. Conference ... ScanFed: Scalable Behavior-Based Backdoor Detection in Federated Learning.
