FLAME: Taming Backdoors in Federated Learning

By T. D. Nguyen, P. Rieger, Huili Chen, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Shaza Zeitouni and 3 more. USENIX Security Symposium, 2022

494 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4089197a8fef8935bab8b879adc08dc5fdf53c6d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Mang Ye
2. Bo Du
3. Pong Chi Yuen
4. Dacheng Tao
5. Xiuwen Fang
6. Changxing Ding
7. Liangpei Zhang
8. Jing Zhang

Citations in the corpus

• Heterogeneous Federated Learning: State-of-the-art and Research Challenges (2023, methodology): “[163] propose FLAME, which does not rely on the underlying data distributions for benign and adversarial datasets.”