Attacking the Madry Defense Model with $L_1$ -based Adversarial Examples

30 October 2017

Papers citing "Attacking the Madry Defense Model with $L_1$-based Adversarial Examples"

37 / 37 papers shown

Title
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense Ryota Iijima Sayaka Shiota Hitoshi Kiya 38 6 0 11 Feb 2024
Training on Foveated Images Improves Robustness to Adversarial Attacks Muhammad Ahmed Shah Bhiksha Raj AAML 38 4 0 01 Aug 2023
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives Daniele Lunghi A. Simitsis O. Caelen Gianluca Bontempi AAML FaML 48 4 0 03 Jul 2023
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against Adversarial Machine Learning Mohammad Hossein Samavatian Saikat Majumdar Kristin Barber R. Teodorescu AAML 28 2 0 31 Jul 2022
Analysis and Extensions of Adversarial Training for Video Classification K. A. Kinfu René Vidal AAML 33 13 0 16 Jun 2022
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art P. Williams Ke Li AAML 27 2 0 07 Mar 2022
Pixle: a fast and effective black-box attack based on rearranging pixels Jary Pomponi Simone Scardapane A. Uncini AAML 22 32 0 04 Feb 2022
Robust Natural Language Processing: Recent Advances, Challenges, and Future Directions Marwan Omar Soohyeon Choi Daehun Nyang David A. Mohaisen 32 57 0 03 Jan 2022
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David Wagner Trevor Darrell AAML 26 27 0 18 May 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 27 6 0 01 Mar 2021
Machine learning pipeline for battery state of health estimation D. Roman Saurabh Saxena Valentin Robu Michael G. Pecht David Flynn 34 375 0 01 Feb 2021
Defending Against Multiple and Unforeseen Adversarial Videos Shao-Yuan Lo Vishal M. Patel AAML 31 23 0 11 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 19 92 0 05 May 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi Natalie Frank M. Mohri AAML 36 56 0 28 Apr 2020
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods Sanghyuk Chun Seong Joon Oh Sangdoo Yun Dongyoon Han Junsuk Choe Y. Yoo AAML OOD 345 53 0 09 Mar 2020
Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks Lu Chen Wenyuan Xu AAML 24 21 0 08 Feb 2020
Scratch that! An Evolution-based Adversarial Attack against Neural Networks Malhar Jere Loris Rossi Briland Hitaj Gabriela F. Cretu-Ciocarlie Giacomo Boracchi F. Koushanfar AAML 16 18 0 05 Dec 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 106 1,428 0 16 Jul 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 30 375 0 30 Apr 2019
Adversarial Defense Through Network Profiling Based Path Extraction Yuxian Qiu Jingwen Leng Cong Guo Quan Chen Chong Li Minyi Guo Yuhao Zhu AAML 24 51 0 17 Apr 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 19 3 0 24 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 31 40 0 03 Mar 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 36 318 0 29 Jan 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 34 721 0 28 Jan 2019
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning K. Makarychev Pascal Dupré Yury Makarychev Giancarlo Pellegrino Dan Boneh AAML 29 64 0 08 Nov 2018
CAAD 2018: Generating Transferable Adversarial Examples Yash Sharma Tien-Dung Le M. Alzantot AAML SILM 28 7 0 29 Sep 2018
On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces Chia-Yi Hsu Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 30 1 0 24 Sep 2018
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 23 121 0 16 Aug 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D. Su Huan Zhang Hongge Chen Jinfeng Yi Pin-Yu Chen Yupeng Gao VLM 40 389 0 05 Aug 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 50 226 0 18 Jul 2018
Curriculum Adversarial Training Qi-Zhi Cai Min Du Chang-rui Liu D. Song AAML 27 160 0 13 May 2018
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 258 916 0 21 Apr 2018
Bypassing Feature Squeezing by Increasing Adversary Strength Yash Sharma Pin-Yu Chen AAML 19 34 0 27 Mar 2018
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 17 26 0 26 Mar 2018
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 37 1,090 0 27 Dec 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 312 3,115 0 04 Nov 2016

Attacking the Madry Defense Model with L1L_1L1​-based Adversarial Examples

Papers citing "Attacking the Madry Defense Model with $L_1$-based Adversarial Examples"

Attacking the Madry Defense Model with $L_1$ -based Adversarial Examples