47 citations · 71 across the 4 of their papers we have counts for
4 papers
Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning
Yuchen Liu, Chen Chen, Lingjuan Lyu +2
Federated Learning (FL) is notorious for its vulnerability to Byzantine attacks. Most current Byzantine defenses share a common inductive bias: among all the gradients, the densely…
Guided Interpolation for Adversarial Training
Chen Chen, Jingfeng Zhang, Xilie Xu +4
To enhance adversarial robustness, adversarial training learns deep neural networks on the adversarial variants generated by their natural data. However, as the training progresses…
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu, Han Yu, Xingjun Ma +5
As data are increasingly being stored in different silos and societies becoming more aware of data privacy issues, the traditional centralized training of artificial intelligence (…
Robust Federated Recommendation System
Chen Chen, Jingfeng Zhang, Anthony K. H. Tung +2
Federated recommendation systems can provide good performance without collecting users' private data, making them attractive. However, they are susceptible to low-cost poisoning at…