23 citations · 26 across the 17 of their papers we have counts for
4 papers · 1 filter
BackFed: An Efficient & Standardized Benchmark Suite for Backdoor Attacks in Federated Learning
Thinh Dao, Dung Thuy Nguyen, Khoa D Doan +1
Research on backdoor attacks in Federated Learning (FL) has accelerated in recent years, with new attacks and defenses continually proposed in an escalating arms race. However, the…
Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape
Tuan Nguyen, Dung Thuy Nguyen, Khoa D Doan +1
Despite the promise of Federated Learning (FL) for privacy-preserving model training on distributed data, it remains susceptible to backdoor attacks. These attacks manipulate model…
Clean-Label Physical Backdoor Attacks with Data Distillation
Thinh Dao, Khoa D Doan, Kok-Seng Wong
Deep Neural Networks (DNNs) are shown to be vulnerable to backdoor poisoning attacks, with most research focusing on digital triggers -- artificial patterns added to test-time inpu…
Synthesizing Physical Backdoor Datasets: An Automated Framework Leveraging Deep Generative Models
Sze Jue Yang, Chinh D. La, Quang H. Nguyen +4
Backdoor attacks, representing an emerging threat to the integrity of deep neural networks, have garnered significant attention due to their ability to compromise deep learning sys…