Energy Attack: On Transferring Adversarial Examples

9 September 2021

Papers citing "Energy Attack: On Transferring Adversarial Examples"

32 / 32 papers shown

Title
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 676 41,483 0 22 Oct 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 93 426 0 16 Jul 2020
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows H. M. Dolatabadi S. Erfani C. Leckie AAML 97 66 0 15 Jul 2020
What Do Neural Networks Learn When Trained With Random Labels? Hartmut Maennel Ibrahim Alabdulmohsin Ilya O. Tolstikhin R. Baldock Olivier Bousquet Sylvain Gelly Daniel Keysers FedML 156 89 0 18 Jun 2020
Boosting Adversarial Training with Hypersphere Embedding Tianyu Pang Xiao Yang Yinpeng Dong Kun Xu Jun Zhu Hang Su AAML 74 156 0 20 Feb 2020
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 91 992 0 29 Nov 2019
Black-Box Adversarial Attack with Transferable Model-based Embedding Zhichao Huang Tong Zhang 65 119 0 17 Nov 2019
Are Perceptually-Aligned Gradients a General Property of Robust Classifiers? Simran Kaur Jeremy M. Cohen Zachary Chase Lipton OOD AAML 53 66 0 18 Oct 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 72 678 0 17 Sep 2019
Improving Black-box Adversarial Attacks with a Transfer-based Prior Shuyu Cheng Yinpeng Dong Tianyu Pang Hang Su Jun Zhu AAML 90 274 0 17 Jun 2019
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks Ziang Yan Yiwen Guo Changshui Zhang AAML 65 111 0 11 Jun 2019
Simple Black-box Adversarial Attacks Chuan Guo Jacob R. Gardner Yurong You A. Wilson Kilian Q. Weinberger AAML 65 580 0 17 May 2019
There are No Bit Parts for Sign Bits in Black-Box Attacks Abdullah Al-Dujaili Una-May O’Reilly AAML 114 20 0 19 Feb 2019
On Evaluating Adversarial Robustness Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow Aleksander Madry Alexey Kurakin ELM AAML 107 905 0 18 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 155 2,560 0 24 Jan 2019
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks Jinghui Chen Dongruo Zhou Jinfeng Yi Quanquan Gu AAML 66 68 0 27 Nov 2018
Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors Andrew Ilyas Logan Engstrom Aleksander Madry MLAU AAML 99 375 0 20 Jul 2018
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks Chun-Chen Tu Pai-Shun Ting Pin-Yu Chen Sijia Liu Huan Zhang Jinfeng Yi Cho-Jui Hsieh Shin-Ming Cheng MLAU AAML 84 398 0 30 May 2018
Black-box Adversarial Attacks with Limited Queries and Information Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin MLAU AAML 165 1,208 0 23 Apr 2018
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans Gamaleldin F. Elsayed Shreya Shankar Brian Cheung Nicolas Papernot Alexey Kurakin Ian Goodfellow Jascha Narain Sohl-Dickstein AAML 97 262 0 22 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 243 3,194 0 01 Feb 2018
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 163 2,160 0 21 Aug 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models Pin-Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho-Jui Hsieh AAML 90 1,887 0 14 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,138 0 19 Jun 2017
Universal adversarial perturbations Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi Omar Fawzi P. Frossard AAML 152 2,533 0 26 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 547 5,912 0 08 Jul 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,510 0 10 Dec 2015
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,427 0 02 Dec 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 154 4,905 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,129 0 20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,529 0 04 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 289 14,968 1 21 Dec 2013