10 citations · 11 across the 5 of their papers we have counts for
4 papers
Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition
Bangjie Yin, Wenxuan Wang, Taiping Yao +5
Deep neural networks, particularly face recognition models, have been shown to be vulnerable to both digital and physical adversarial examples. However, existing adversarial exampl…
PredCoin: Defense against Query-based Hard-label Attack
Junfeng Guo, Yaswanth Yadlapalli, Thiele Lothar +2
Many adversarial attacks and defenses have recently been proposed for Deep Neural Networks (DNNs). While most of them are in the white-box setting, which is impractical, a new clas…
LINTS^RT: A Learning-driven Testbed for Intelligent Scheduling in Embedded Systems
Zelun Kong, Yaswanth Yadlapalli, Soroush Bateni +2
Due to the increasing complexity seen in both workloads and hardware resources in state-of-the-art embedded systems, developing efficient real-time schedulers and the corresponding…
PoisHygiene: Detecting and Mitigating Poisoning Attacks in Neural Networks
Junfeng Guo, Ting Wang, Cong Liu
The black-box nature of deep neural networks (DNNs) facilitates attackers to manipulate the behavior of DNN through data poisoning. Being able to detect and mitigate poisoning atta…