Detection of Malicious Clients in Federated Learning Using Graph Neural Network

Federated Learning (FL) facilitates decentralized model training without the exchange of raw data, thereby guaranteeing privacy. However, due to its distributed nature, this paradigm is susceptible to adversarial threats such as sign-flipping attacks, in which malicious clients reverse model paramet...

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Auteurs principaux:	Anee Sharma, Ningrinla Marchang
Format:	Artigo
Langue:	Inglês
Publié:	IEEE 2025-01-01
Collection:	IEEE Access
Sujets:	Federated learning anomaly detection graph neural networks sign-flipping attacks graph attention networks malicious clients
Accès en ligne:	https://ieeexplore.ieee.org/document/10980311/
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