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Found 2 papers, 1 papers with code
The Impact of Adversarial Node Placement in Decentralized Federated Learning Networks
This paper addresses this gap by analyzing the performance of decentralized FL for various adversarial placement strategies when adversaries can jointly coordinate their placement within a network.
Mitigating Evasion Attacks in Federated Learning-Based Signal Classifiers
In this work, we first reveal the susceptibility of FL-based signal classifiers to model poisoning attacks, which compromise the training process despite not observing data transmissions.
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