3 citations · 11 across the 38 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…
Under-confidence Backdoors Are Resilient and Stealthy Backdoors
Minlong Peng, Zidi Xiong, Quang H. Nguyen +3
By injecting a small number of poisoned samples into the training set, backdoor attacks aim to make the victim model produce designed outputs on any input injected with pre-designe…