Machine Learning · Computer Science
On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel +5
2019-02-21
Machine Learning · Computer Science
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramer, Nicholas Carlini, Wieland Brendel, Aleksander Madry
2020-10-26
Machine Learning · Computer Science
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong
Warren He, James Wei, Xinyun Chen, Nicholas Carlini +1
2017-06-16
Machine Learning · Computer Science
MemLoss: Enhancing Adversarial Training with Recycling Adversarial Examples
Soroush Mahdi, Maryam Amirmazlaghani, Saeed Saravani, Zahra Dehghanian
2025-10-13
Machine Learning · Computer Science
Provably Minimally-Distorted Adversarial Examples
Nicholas Carlini, Guy Katz, Clark Barrett, David L. Dill
2018-02-21
Machine Learning · Computer Science
Towards Robust Detection of Adversarial Examples
Tianyu Pang, Chao Du, Yinpeng Dong, Jun Zhu
2018-11-08
Computer Vision and Pattern Recognition · Computer Science
Adversarial Example Defense via Perturbation Grading Strategy
Shaowei Zhu, Wanli Lyu, Bin Li, Zhaoxia Yin +1
2024-12-10
Cryptography and Security · Computer Science
Attack as Defense: Characterizing Adversarial Examples using Robustness
Zhe Zhao, Guangke Chen, Jingyi Wang, Yiwei Yang +2
2021-03-16
Machine Learning · Computer Science
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks
Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang
2020-10-27
Machine Learning · Computer Science
When Should You Defend Your Classifier -- A Game-theoretical Analysis of Countermeasures against Adversarial Examples
Maximilian Samsinger, Florian Merkle, Pascal Schöttle, Tomas Pevny
2021-09-28
Machine Learning · Computer Science
Advocating for Multiple Defense Strategies against Adversarial Examples
Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Negrevergne
2020-12-07
Machine Learning · Computer Science
Defending Against Machine Learning Model Stealing Attacks Using Deceptive Perturbations
Taesung Lee, Benjamin Edwards, Ian Molloy, Dong Su
2018-12-14
Computer Vision and Pattern Recognition · Computer Science
Beating Attackers At Their Own Games: Adversarial Example Detection Using Adversarial Gradient Directions
Yuhang Wu, Sunpreet S. Arora, Yanhong Wu, Hao Yang
2021-01-01
Machine Learning · Computer Science
Defending Adversarial Attacks by Correcting logits
Yifeng Li, Lingxi Xie, Ya Zhang, Rui Zhang +2
2019-06-27
Machine Learning · Computer Science
ML-LOO: Detecting Adversarial Examples with Feature Attribution
Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang +1
2019-06-11
Computer Vision and Pattern Recognition · Computer Science
Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising
Sandhya Aneja, Nagender Aneja, Pg Emeroylariffion Abas, Abdul Ghani Naim
2022-06-28