4 citations · 6 across the 3 of their papers we have counts for
3 papers
Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated Learning
Son Nguyen, Thinh Nguyen, Khoa D Doan +1
Federated Learning (FL) is a distributed machine learning approach that maintains data privacy by training on decentralized data sources. Similar to centralized machine learning, F…
An Empirical Study of Federated Learning on IoT-Edge Devices: Resource Allocation and Heterogeneity
Kok-Seng Wong, Manh Nguyen-Duc, Khiem Le-Huy +3
Nowadays, billions of phones, IoT and edge devices around the world generate data continuously, enabling many Machine Learning (ML)-based products and applications. However, due to…
FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection
Thuy Dung Nguyen, Anh Duy Nguyen, Kok-Seng Wong +4
Federated learning (FL) enables multiple clients to train a model without compromising sensitive data. The decentralized nature of FL makes it susceptible to adversarial attacks, e…