Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training

9 February 2021

Papers citing "Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training"

21 / 21 papers shown

Title
Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging Rui Luo Jie Bao Zhixin Zhou Chuangyin Dang MedIm AAML 37 5 0 07 Nov 2024
Nonlinear Transformations Against Unlearnable Datasets T. Hapuarachchi Jing Lin Kaiqi Xiong Mohamed Rahouti Gitte Ost 28 1 0 05 Jun 2024
PureEBM: Universal Poison Purification via Mid-Run Dynamics of Energy-Based Models Omead Brandon Pooladzandi Jeffrey Q. Jiang Sunay Bhat Gregory Pottie AAML 31 0 0 28 May 2024
Effective and Robust Adversarial Training against Data and Label Corruptions Pengfei Zhang Zi Huang Xin-Shun Xu Guangdong Bai 51 4 0 07 May 2024
Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders Yi Yu Yufei Wang Song Xia Wenhan Yang Shijian Lu Yap-Peng Tan A.C. Kot AAML 37 11 0 02 May 2024
Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously Yihan Wang Yifan Zhu Xiao-Shan Gao AAML 25 6 0 06 Feb 2024
Game-Theoretic Unlearnable Example Generator Shuang Liu Yihan Wang Xiao-Shan Gao AAML 29 8 0 31 Jan 2024
CUDA: Convolution-based Unlearnable Datasets Vinu Sankar Sadasivan Mahdi Soltanolkotabi S. Feizi MU 29 25 0 07 Mar 2023
Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detection Zhen Cheng Fei Zhu Xu-Yao Zhang Cheng-Lin Liu MoMe OODD 40 11 0 02 Mar 2023
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks Tianwei Liu Yu Yang Baharan Mirzasoleiman AAML 22 27 0 14 Aug 2022
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning Hao He Kaiwen Zha Dina Katabi AAML 34 32 0 22 Feb 2022
On the Effectiveness of Adversarial Training against Backdoor Attacks Yinghua Gao Dongxian Wu Jingfeng Zhang Guanhao Gan Shutao Xia Gang Niu Masashi Sugiyama AAML 32 22 0 22 Feb 2022
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao Lei Feng Hongxin Wei Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 78 16 0 31 Jan 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 194 345 0 15 Dec 2021
Adversarial Neuron Pruning Purifies Backdoored Deep Models Dongxian Wu Yisen Wang AAML 17 275 0 27 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 46 100 0 07 Oct 2021
Poisoning the Unlabeled Dataset of Semi-Supervised Learning Nicholas Carlini AAML 149 68 0 04 May 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 153 190 0 13 Jan 2021
Unadversarial Examples: Designing Objects for Robust Vision Hadi Salman Andrew Ilyas Logan Engstrom Sai H. Vemprala A. Madry Ashish Kapoor WIGM 62 59 0 22 Dec 2020
On Evaluating Neural Network Backdoor Defenses A. Veldanda S. Garg AAML 21 8 0 23 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 231 677 0 19 Oct 2020