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20182022
most citedBlack-Box Adversarial Attack with Transferable Model-based Embedding

50 citations · 113 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.LG2022

Fast Adversarial Training with Adaptive Step Size

Zhichao Huang, Yanbo Fan, Chen Liu +5

While adversarial training and its variants have shown to be the most effective algorithms to defend against adversarial attacks, their extremely slow training process makes it har…

cs.LG2021★ 3 cited

On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training

Chen Liu, Zhichao Huang, Mathieu Salzmann +2

Adversarial training is a popular method to robustify models against adversarial attacks. However, it exhibits much more severe overfitting than training on clean inputs. In this w…

cs.LG2020★ 6 cited

CorrAttack: Black-box Adversarial Attack with Structured Search

Zhichao Huang, Yaowei Huang, Tong Zhang

We present a new method for score-based adversarial attack, where the attacker queries the loss-oracle of the target model. Our method employs a parameterized search space with a s…

cs.LG2019★ 50 cited

Black-Box Adversarial Attack with Transferable Model-based Embedding

Zhichao Huang, Tong Zhang

We present a new method for black-box adversarial attack. Unlike previous methods that combined transfer-based and scored-based methods by using the gradient or initialization of a…

cs.LG2018★ 24 cited

Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack

Haishan Ye, Zhichao Huang, Cong Fang +2

Zeroth-order optimization is an important research topic in machine learning. In recent years, it has become a key tool in black-box adversarial attack to neural network based imag…