Defenses in Adversarial Machine Learning: A Survey

Defenses in Adversarial Machine Learning: A Survey

13 December 2023

Hongrui Chen

Papers citing "Defenses in Adversarial Machine Learning: A Survey"

16 / 16 papers shown

Title
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors Peter Lorenz Mario Fernandez Jens Müller Ullrich Kothe AAML 56 1 0 21 Jun 2024
Detecting Backdoors in Pre-trained Encoders Shiwei Feng Guanhong Tao Shuyang Cheng Guangyu Shen Xiangzhe Xu Yingqi Liu Kaiyuan Zhang Shiqing Ma Xiangyu Zhang 63 45 0 23 Mar 2023
Backdoor Defense via Deconfounded Representation Learning Zaixin Zhang Qi Liu Zhicai Wang Zepu Lu Qingyong Hu AAML 42 39 0 13 Mar 2023
Efficient and Effective Augmentation Strategy for Adversarial Training Sravanti Addepalli Samyak Jain R. Venkatesh Babu AAML 51 57 0 27 Oct 2022
InfoAT: Improving Adversarial Training Using the Information Bottleneck Principle Mengting Xu Tao Zhang Zhongnian Li Daoqiang Zhang AAML 27 15 0 23 Jun 2022
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks Sizhe Chen Zhehao Huang Qinghua Tao Yingwen Wu Cihang Xie X. Huang AAML 103 27 0 24 May 2022
Diffusion Models for Adversarial Purification Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 184 410 0 16 May 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 39 71 0 26 Mar 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 183 344 0 15 Dec 2021
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 167 256 0 10 Nov 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 44 100 0 07 Oct 2021
On the Effectiveness of Small Input Noise for Defending Against Query-based Black-Box Attacks Junyoung Byun Hyojun Go Changick Kim AAML 118 17 0 13 Jan 2021
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization Saehyung Lee Hyungyu Lee Sungroh Yoon AAML 148 113 0 05 Mar 2020
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 36 94 0 16 Oct 2019
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 159 284 0 02 Dec 2018
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 43 259 0 30 Nov 2018