Provable robustness against all adversarial $l_p$ -perturbations for $p\geq 1$

27 May 2019

Francesco Croce

Matthias Hein

OOD

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Papers citing "Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$"

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Title
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP Hanxun Huang Sarah Monazam Erfani Yige Li Xingjun Ma James Bailey AAML 144 1 0 08 May 2025
Defending Against Frequency-Based Attacks with Diffusion Models Fatemeh Amerehi Patrick Healy AAML 75 0 0 15 Apr 2025
Deep Adversarial Defense Against Multilevel-Lp Attacks Ren Wang Yuxuan Li Alfred Hero AAML 63 0 0 12 Jul 2024
A Survey of Neural Network Robustness Assessment in Image Recognition Jie Wang Jun Ai Minyan Lu Haoran Su Dan Yu Yutao Zhang Junda Zhu Jingyu Liu AAML 100 3 0 12 Apr 2024
Towards Robust Domain Generation Algorithm Classification Arthur Drichel Marc Meyer Ulrike Meyer AAML 67 3 0 09 Apr 2024
Tropical Decision Boundaries for Neural Networks Are Robust Against Adversarial Attacks Kurt Pasque Christopher Teska Ruriko Yoshida Keiji Miura Jefferson Huang AAML 96 2 0 01 Feb 2024
FullLoRA: Efficiently Boosting the Robustness of Pretrained Vision Transformers Zheng Yuan Jie Zhang Shiguang Shan Xilin Chen 102 4 0 03 Jan 2024
Multi-scale Diffusion Denoised Smoothing Jongheon Jeong Jinwoo Shin DiffM 88 8 0 25 Oct 2023
Parameter-Saving Adversarial Training: Reinforcing Multi-Perturbation Robustness via Hypernetworks Huihui Gong Minjing Dong Siqi Ma S. Çamtepe Surya Nepal Chang Xu AAML OOD 48 1 0 28 Sep 2023
PRAT: PRofiling Adversarial aTtacks Rahul Ambati Naveed Akhtar Ajmal Mian Yogesh S Rawat AAML 51 1 0 20 Sep 2023
Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets Yimu Wang Dinghuai Zhang Yihan Wu Heng Huang Hongyang R. Zhang AAML 52 1 0 27 Jun 2023
Certified Adversarial Robustness Within Multiple Perturbation Bounds Soumalya Nandi Sravanti Addepalli Harsh Rangwani R. Venkatesh Babu AAML 58 3 0 20 Apr 2023
Optimization and Optimizers for Adversarial Robustness Hengyue Liang Buyun Liang Le Peng Ying Cui Tim Mitchell Ju Sun AAML 55 5 0 23 Mar 2023
$Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified $\ell_p$ Attacks$ Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified $\ell_p$ Attacks Ren Wang Yuxuan Li Sijia Liu AAML 65 0 0 17 Mar 2023
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks Sihui Dai Saeed Mahloujifar Chong Xiang Vikash Sehwag Pin-Yu Chen Prateek Mittal AAML OOD 102 7 0 21 Feb 2023
Confidence-aware Training of Smoothed Classifiers for Certified Robustness Jongheon Jeong Seojin Kim Jinwoo Shin AAML 76 7 0 18 Dec 2022
$Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance$ Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$ -norms For Better Adversarial Performance Ngoc N. Tran Anh Tuan Bui Dinh Q. Phung Trung Le AAML 51 1 0 05 Dec 2022
Learning Sample Reweighting for Accuracy and Adversarial Robustness Chester Holtz Tsui-Wei Weng Zhengchao Wan OOD 77 4 0 20 Oct 2022
Provably Adversarially Robust Nearest Prototype Classifiers Václav Voráček Matthias Hein AAML 43 11 0 14 Jul 2022
UniCR: Universally Approximated Certified Robustness via Randomized Smoothing Hanbin Hong Binghui Wang Yuan Hong AAML 76 11 0 05 Jul 2022
Formulating Robustness Against Unforeseen Attacks Sihui Dai Saeed Mahloujifar Prateek Mittal OOD AAML 66 8 0 28 Apr 2022
How Sampling Impacts the Robustness of Stochastic Neural Networks Sina Daubener Asja Fischer SILM AAML 44 1 0 22 Apr 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 123 73 0 26 Mar 2022
$Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees$ Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees D. Thaker Paris V. Giampouras René Vidal AAML 31 6 0 09 Mar 2022
The Fundamental Limits of Interval Arithmetic for Neural Networks M. Mirman Maximilian Baader Martin Vechev 37 6 0 09 Dec 2021
Adaptive Image Transformations for Transfer-based Adversarial Attack Zheng Yuan Jie Zhang Shiguang Shan OOD 89 27 0 27 Nov 2021
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness Jongheon Jeong Sejun Park Minkyu Kim Heung-Chang Lee Do-Guk Kim Jinwoo Shin AAML 85 57 0 17 Nov 2021
Improving Local Effectiveness for Global robust training Jingyue Lu M. P. Kumar AAML 49 0 0 26 Oct 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 155 240 0 01 Aug 2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 104 69 0 26 Jul 2021
Selection of Source Images Heavily Influences the Effectiveness of Adversarial Attacks Utku Ozbulak Esla Timothy Anzaku W. D. Neve Arnout Van Messem AAML 132 10 0 14 Jun 2021
Relaxing Local Robustness Klas Leino Matt Fredrikson AAML 52 8 0 11 Jun 2021
Adversarial Robustness against Multiple and Single $l_p$ -Threat Models via Quick Fine-Tuning of Robust Classifiers Francesco Croce Matthias Hein OOD AAML 67 18 0 26 May 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 111 61 0 08 Mar 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 97 61 0 24 Jan 2021
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks Arno Blaas Stephen J. Roberts BDL AAML 78 2 0 07 Jan 2021
$Towards Defending Multiple $\ell_p$-norm Bounded Adversarial Perturbations via Gated Batch Normalization$ Towards Defending Multiple $\ell_p$ -norm Bounded Adversarial Perturbations via Gated Batch Normalization Aishan Liu Shiyu Tang Xinyun Chen Lei Huang Zhuozhuo Tu Xianglong Liu Dacheng Tao AAML 110 35 0 03 Dec 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Yue Liu AAML 123 131 0 09 Sep 2020
Learning perturbation sets for robust machine learning Eric Wong J. Zico Kolter OOD 76 81 0 16 Jul 2020
Adversarial Examples and Metrics Nico Döttling Kathrin Grosse Michael Backes Ian Molloy AAML 35 0 0 14 Jul 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey S. Silva Peyman Najafirad AAML OOD 99 135 0 01 Jul 2020
ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy Natalia Shepeleva Werner Zellinger Michal Lewandowski Bernhard A. Moser 32 3 0 20 May 2020
How to compare adversarial robustness of classifiers from a global perspective Niklas Risse Christina Göpfert Jan Philip Göpfert AAML 19 0 0 22 Apr 2020
Approximate Manifold Defense Against Multiple Adversarial Perturbations Jay Nandy Wynne Hsu Mong Li Lee AAML 55 12 0 05 Apr 2020
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li Saminul Haque Cem Anil James Lucas Roger C. Grosse Joern-Henrik Jacobsen 119 116 0 03 Nov 2019
Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications Andreas Venzke Spyros Chatzivasileiadis 87 67 0 03 Oct 2019
Adversarial Robustness Against the Union of Multiple Perturbation Models Pratyush Maini Eric Wong J. Zico Kolter OOD AAML 63 151 0 09 Sep 2019
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural Networks Dino Oglic Zoran Cvetkovic Peter Sollich BDL 39 8 0 23 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 70 37 0 09 Jun 2019