3 citations · 7 across the 4 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.LG2021★ 3 cited
Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout
Pengfei Xie, Linyuan Wang, Ruoxi Qin +4
Deep neural networks(DNNs) is vulnerable to be attacked by adversarial examples. Black-box attack is the most threatening attack. At present, black-box attack methods mainly adopt…
cs.CR2021
Dynamic Defense Approach for Adversarial Robustness in Deep Neural Networks via Stochastic Ensemble Smoothed Model
Ruoxi Qin, Linyuan Wang, Xingyuan Chen +2
Deep neural networks have been shown to suffer from critical vulnerabilities under adversarial attacks. This phenomenon stimulated the creation of different attack and defense stra…