Resilience of Wireless Ad Hoc Federated Learning against Model Poisoning Attacks

Author:

Tezuka Naoya1,Ochiai Hideya1,Sun Yuwei1,Esaki Hiroshi1

Affiliation:

1. The University of Tokyo

Publisher

IEEE

Reference22 articles.

1. How to backdoor federated learning;bagdasaryan;International Conference on Artificial Intelligence and Statistics,2020

2. Backdoor Learning: A Survey

3. Defending against Backdoors in Federated Learning with Robust Learning Rate

4. Attack of the tails: Yes, you really can backdoor federated learning;wang;Advances in neural information processing systems,2020

5. Evaluation of the masked node problem in ad hoc wireless LANs

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1. Risk-Aware Accelerated Wireless Federated Learning with Heterogeneous Clients;ICC 2024 - IEEE International Conference on Communications;2024-06-09

2. Tuning Vision Transformer with Device-to-Device Communication for Targeted Image Recognition;2023 IEEE 9th World Forum on Internet of Things (WF-IoT);2023-10-12

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