AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples

30 April 2024

Antonio Emanuele Cinà

Papers citing "AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples"

48 / 48 papers shown

Title
Revisiting Adversarial Perception Attacks and Defense Methods on Autonomous Driving Systems Cheng Chen Yuhong Wang Nafis S Munir Xiangwei Zhou Xugui Zhou AAML 37 0 0 14 May 2025
Rethinking Robustness in Machine Learning: A Posterior Agreement Approach João B. S. Carvalho Alessandro Torcinovich Victor Jimenez Rodriguez Antonio Emanuele Cinà Carlos Cotrini Lea Schönherr J. M. Buhmann OOD 87 0 0 20 Mar 2025
Sonic: Fast and Transferable Data Poisoning on Clustering Algorithms Francesco Villani Dario Lazzaro Antonio Emanuele Cinà Matteo DellÁmico Battista Biggio Fabio Roli 54 1 0 14 Aug 2024
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors Peter Lorenz Mario Fernandez Jens Müller Ullrich Kothe AAML 95 1 0 21 Jun 2024
Poisoning Web-Scale Training Datasets is Practical Nicholas Carlini Matthew Jagielski Christopher A. Choquette-Choo Daniel Paleka Will Pearce Hyrum S. Anderson Andreas Terzis Kurt Thomas Florian Tramèr SILM 63 189 0 20 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min Lin Weiwei Liu Shuicheng Yan DiffM 34 217 0 09 Feb 2023
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 64 71 0 15 Sep 2022
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples Maura Pintor Christian Scano Angelo Sotgiu Ambra Demontis Nicholas Carlini Battista Biggio Fabio Roli AAML 41 28 0 18 Jun 2021
PDPGD: Primal-Dual Proximal Gradient Descent Adversarial Attack Alexander Matyasko Lap-Pui Chau AAML 25 8 0 03 Jun 2021
Adversarial Example Detection for DNN Models: A Review and Experimental Comparison Ahmed Aldahdooh W. Hamidouche Sid Ahmed Fezza Olivier Déforges AAML 102 122 0 01 May 2021
Mind the box: $l_1$ -APGD for sparse adversarial attacks on image classifiers Francesco Croce Matthias Hein AAML 62 55 0 01 Mar 2021
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints Maura Pintor Fabio Roli Wieland Brendel Battista Biggio AAML 58 71 0 25 Feb 2021
A Comprehensive Evaluation Framework for Deep Model Robustness Jun Guo Wei Bao Jiakai Wang Yuqing Ma Xing Gao Gang Xiao Aishan Liu Zehao Zhao Xianglong Liu Wenjun Wu AAML ELM 49 57 0 24 Jan 2021
Stochastic sparse adversarial attacks M. Césaire Théo Combey H. Hajri Sylvain Lamprier Patrick Gallinari AAML 32 9 0 24 Nov 2020
Augmented Lagrangian Adversarial Attacks Jérôme Rony Eric Granger M. Pedersoli Ismail Ben Ayed AAML 28 39 0 24 Nov 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 262 689 0 19 Oct 2020
Torchattacks: A PyTorch Repository for Adversarial Attacks Hoki Kim 31 204 0 24 Sep 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 51 423 0 16 Jul 2020
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses Yaxin Li Wei Jin Han Xu Jiliang Tang AAML 40 131 0 13 May 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 179 1,821 0 03 Mar 2020
On Adaptive Attacks to Adversarial Example Defenses Florian Tramèr Nicholas Carlini Wieland Brendel Aleksander Madry AAML 177 827 0 19 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 118 1,167 0 12 Jan 2020
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 60 199 0 11 Sep 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 74 482 0 03 Jul 2019
Accurate, reliable and fast robustness evaluation Wieland Brendel Jonas Rauber Matthias Kümmerer Ivan Ustyuzhaninov Matthias Bethge AAML OOD 36 113 0 01 Jul 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 45 346 0 14 Jun 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 29 98 0 25 May 2019
A critique of the DeepSec Platform for Security Analysis of Deep Learning Models Nicholas Carlini ELM 31 14 0 17 May 2019
Activation Analysis of a Byte-Based Deep Neural Network for Malware Classification Scott E. Coull Christopher Gardner 34 50 0 12 Mar 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 61 894 0 18 Feb 2019
Trust Region Based Adversarial Attack on Neural Networks Z. Yao A. Gholami Peng Xu Kurt Keutzer Michael W. Mahoney AAML 30 54 0 16 Dec 2018
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses Jérôme Rony L. G. Hafemann Luiz Eduardo Soares de Oliveira Ismail Ben Ayed R. Sabourin Eric Granger AAML 30 299 0 23 Nov 2018
SparseFool: a few pixels make a big difference Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 28 197 0 06 Nov 2018
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 67 457 0 03 Jul 2018
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models Wieland Brendel Jonas Rauber Matthias Bethge AAML 58 1,335 0 12 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 83 1,401 0 08 Dec 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen Yash Sharma Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 46 639 0 13 Sep 2017
Security Evaluation of Pattern Classifiers under Attack Battista Biggio Giorgio Fumera Fabio Roli AAML 37 442 0 02 Sep 2017
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 93 2,140 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 208 11,962 0 19 Jun 2017
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library Nicolas Papernot Fartash Faghri Nicholas Carlini Ian Goodfellow Reuben Feinman ... David Berthelot P. Hendricks Jonas Rauber Rujun Long Patrick McDaniel AAML 47 512 0 03 Oct 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 155 8,497 0 16 Aug 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 210 8,030 0 13 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 480 5,868 0 08 Jul 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 52 3,947 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 90 4,878 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 151 18,922 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 157 14,831 1 21 Dec 2013