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Poisoning Attacks and Defenses in Federated Learning: A Survey

01/14/2023

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by Subhash Sagar, et al.

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Federated learning (FL) enables the training of models among distributed clients without compromising the privacy of training datasets, while the invisibility of clients datasets and the training process poses a variety of security threats. This survey provides the taxonomy of poisoning attacks and experimental evaluation to discuss the need for robust FL.

Subhash Sagar
7 publications
Chang-Sun Li
1 publication
Seng W. Loke
17 publications
Jinho Choi
64 publications

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