Detection of Malicious Clients in Federated Learning Using Graph Neural Network

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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Bibliographic Details
Main Authors: Anee Sharma, Ningrinla Marchang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Federated learning
anomaly detection
graph neural networks
sign-flipping attacks
graph attention networks
malicious clients
Online Access:https://ieeexplore.ieee.org/document/10980311/
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https://ieeexplore.ieee.org/document/10980311/

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