Paper ID: 2301.05795

Poisoning Attacks and Defenses in Federated Learning: A Survey

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

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.

Submitted: Jan 14, 2023