Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted Attacks

18 December 2022

Papers citing "Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted Attacks"

37 / 37 papers shown

Title
S $^4$ ST: A Strong, Self-transferable, faSt, and Simple Scale Transformation for Transferable Targeted Attack Yongxiang Liu Bowen Peng Li Liu Xuzhao Li 308 0 0 13 Oct 2024
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 91 3 0 09 Oct 2024
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains Qilong Zhang Xiaodan Li YueFeng Chen Jingkuan Song Lianli Gao Yuan He Hui Xue AAML 85 65 0 27 Jan 2022
f-Domain-Adversarial Learning: Theory and Algorithms David Acuna Guojun Zhang M. Law Sanja Fidler FedML AI4CE 62 61 0 21 Jun 2021
Feature Space Targeted Attacks by Statistic Alignment Lianli Gao Yaya Cheng Qilong Zhang Xing Xu Jingkuan Song AAML 41 33 0 25 May 2021
On Generating Transferable Targeted Perturbations Muzammal Naseer Salman Khan Munawar Hayat Fahad Shahbaz Khan Fatih Porikli AAML 74 74 0 26 Mar 2021
Admix: Enhancing the Transferability of Adversarial Attacks Xiaosen Wang Xu He Jingdong Wang Kun He AAML 117 201 0 31 Jan 2021
On Success and Simplicity: A Second Look at Transferable Targeted Attacks Zhengyu Zhao Zhuoran Liu Martha Larson AAML 100 125 0 21 Dec 2020
Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation Shuang Li Fangrui Lv Binhui Xie Chi Harold Liu Jian Liang Chen Qin 52 115 0 13 Dec 2020
Backpropagating Linearly Improves Transferability of Adversarial Examples Yiwen Guo Qizhang Li Hao Chen FedML AAML 73 116 0 07 Dec 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 70 423 0 16 Jul 2020
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability Nathan Inkawhich Kevin J. Liang Binghui Wang Matthew J. Inkawhich Lawrence Carin Yiran Chen AAML 42 90 0 29 Apr 2020
Transferable Perturbations of Deep Feature Distributions Nathan Inkawhich Kevin J. Liang Lawrence Carin Yiran Chen AAML 57 86 0 27 Apr 2020
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets Dongxian Wu Yisen Wang Shutao Xia James Bailey Xingjun Ma AAML SILM 76 314 0 14 Feb 2020
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty Dan Hendrycks Norman Mu E. D. Cubuk Barret Zoph Justin Gilmer Balaji Lakshminarayanan OOD UQCV 103 1,300 0 05 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 493 42,407 0 03 Dec 2019
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks Jiadong Lin Chuanbiao Song Kun He Liwei Wang John E. Hopcroft AAML 68 569 0 17 Aug 2019
Cross-Domain Transferability of Adversarial Perturbations Muzammal Naseer Salman H. Khan M. H. Khan Fahad Shahbaz Khan Fatih Porikli AAML 88 145 0 28 May 2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks Yinpeng Dong Tianyu Pang Hang Su Jun Zhu SILM AAML 88 848 0 05 Apr 2019
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation Chen-Yu Lee Tanmay Batra M. H. Baig Daniel Ulbricht 132 540 0 10 Mar 2019
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix Wichmann Wieland Brendel 100 2,670 0 29 Nov 2018
Improving Transferability of Adversarial Examples with Input Diversity Cihang Xie Zhishuai Zhang Yuyin Zhou Song Bai Jianyu Wang Zhou Ren Alan Yuille AAML 106 1,121 0 19 Mar 2018
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation Kuniaki Saito Kohei Watanabe Yoshitaka Ushiku Tatsuya Harada 98 1,791 0 07 Dec 2017
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 69 355 0 06 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 304 12,069 0 19 Jun 2017
The Space of Transferable Adversarial Examples Florian Tramèr Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML SILM 90 558 0 11 Apr 2017
Delving into Transferable Adversarial Examples and Black-box Attacks Yanpei Liu Xinyun Chen Chang-rui Liu D. Song AAML 140 1,737 0 08 Nov 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 772 36,813 0 25 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 261 8,552 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 540 5,897 0 08 Jul 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples Nicolas Papernot Patrick McDaniel Ian Goodfellow SILM AAML 112 1,739 0 24 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,878 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,115 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,049 0 20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,348 0 04 Sep 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,525 0 01 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 270 14,918 1 21 Dec 2013