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arXiv · 2301.05795

Poisoning Attacks and Defenses in Federated Learning: A Survey

Subhash Sagar·Chang-Sun Li·Seng W. Loke·Jinho Choi
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Abstract

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.

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Subhash Sagar, Chang-Sun Li, Seng W. Loke, Jinho Choi. 2023-01-14. Poisoning Attacks and Defenses in Federated Learning: A Survey. https://arxiv.org/abs/2301.05795

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