114 citations · 413 across the 46 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.CV2019★ 14 cited
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
Pu Zhao, Sijia Liu, Pin-Yu Chen +4
Robust machine learning is currently one of the most prominent topics which could potentially help shaping a future of advanced AI platforms that not only perform well in average c…
cs.LG2019★ 46 cited
Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks
Pu Zhao, Siyue Wang, Cheng Gongye +3
Despite the great achievements of deep neural networks (DNNs), the vulnerability of state-of-the-art DNNs raises security concerns of DNNs in many application domains requiring hig…
cs.CV2019★ 37 cited
Interpreting Adversarial Examples by Activation Promotion and Suppression
Kaidi Xu, Sijia Liu, Gaoyuan Zhang +5
It is widely known that convolutional neural networks (CNNs) are vulnerable to adversarial examples: images with imperceptible perturbations crafted to fool classifiers. However, i…