88 citations · 452 across the 72 of their papers we have counts for
10 papers · 1 filter
Unrestricted Adversarial Attacks on ImageNet Competition
Yuefeng Chen, Xiaofeng Mao, Yuan He +34
Many works have investigated the adversarial attacks or defenses under the settings where a bounded and imperceptible perturbation can be added to the input. However in the real-wo…
Adversarial Attacks on ML Defense Models Competition
Yinpeng Dong, Qi-An Fu, Xiao Yang +25
Due to the vulnerability of deep neural networks (DNNs) to adversarial examples, a large number of defense techniques have been proposed to alleviate this problem in recent years.…
Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness
Xiao Yang, Yinpeng Dong, Wenzhao Xiang +3
The vulnerability of deep neural networks to adversarial examples has motivated an increasing number of defense strategies for promoting model robustness. However, the progress is…
Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks
Xiao Yang, Yinpeng Dong, Tianyu Pang +2
Transfer-based adversarial attacks can evaluate model robustness in the black-box setting. Several methods have demonstrated impressive untargeted transferability, however, it is s…
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models
Zihao Xiao, Xianfeng Gao, Chilin Fu +5
Face recognition is greatly improved by deep convolutional neural networks (CNNs). Recently, these face recognition models have been used for identity authentication in security se…
Accumulative Poisoning Attacks on Real-time Data
Tianyu Pang, Xiao Yang, Yinpeng Dong +2
Collecting training data from untrusted sources exposes machine learning services to poisoning adversaries, who maliciously manipulate training data to degrade the model accuracy.…