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XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning. (arXiv:2212.13675v1 [cs.CR])
Dec. 29, 2022, 2:10 a.m. | Jianyi Zhang, Fangjiao Zhang, Qichao Jin, Zhiqiang Wang, Xiaodong Lin, Xiali Hei
cs.CR updates on arXiv.org arxiv.org
Federated Learning (FL) has received increasing attention due to its privacy
protection capability. However, the base algorithm FedAvg is vulnerable when it
suffers from so-called backdoor attacks. Former researchers proposed several
robust aggregation methods. Unfortunately, many of these aggregation methods
are unable to defend against backdoor attacks. What's more, the attackers
recently have proposed some hiding methods that further improve backdoor
attacks' stealthiness, making all the existing robust aggregation methods fail.
To tackle the threat of backdoor attacks, we propose …
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