114 citations · 413 across the 46 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.CR2018★ 45 cited
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks
Siyue Wang, Xiao Wang, Pu Zhao +4
Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That is, adversarial examples, obtained by adding delicately crafted distortions onto original legal inputs…
cs.LG2018★ 114 cited
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Kaidi Xu, Sijia Liu, Pu Zhao +6
When generating adversarial examples to attack deep neural networks (DNNs), Lp norm of the added perturbation is usually used to measure the similarity between original image and a…
cs.LG2018★ 15 cited
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks
Pu Zhao, Sijia Liu, Yanzhi Wang +1
Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That is, adversarial examples, obtained by adding delicately crafted distortions onto original legal inputs…