most citedShielding Federated Learning: Robust Aggregation with Adaptive Client Selection

50 citations · 50 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2024

Bypassing DARCY Defense: Indistinguishable Universal Adversarial Triggers

Zuquan Peng, Yuanyuan He, Jianbing Ni +1

Neural networks (NN) classification models for Natural Language Processing (NLP) are vulnerable to the Universal Adversarial Triggers (UAT) attack that triggers a model to produce…

cs.CR2022★ 50 cited

Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection

Wei Wan, Shengshan Hu, Jianrong Lu +3

Federated learning (FL) enables multiple clients to collaboratively train an accurate global model while protecting clients' data privacy. However, FL is susceptible to Byzantine a…