Second-Order Provable Defenses against Adversarial Attacks

1 June 2020

Papers citing "Second-Order Provable Defenses against Adversarial Attacks"

50 / 53 papers shown

Title
Learning to Learn Transferable Generative Attack for Person Re-Identification Yuan Bian Min Liu Xueping Wang Yunfeng Ma Yaonan Wang AAML OOD 124 1 0 06 Sep 2024
Certifying LLM Safety against Adversarial Prompting Aounon Kumar Chirag Agarwal Suraj Srinivas Aaron Jiaxun Li Soheil Feizi Himabindu Lakkaraju AAML 77 191 0 06 Sep 2023
(De)Randomized Smoothing for Certifiable Defense against Patch Attacks Alexander Levine Soheil Feizi AAML 68 149 0 25 Feb 2020
Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation Alexander Levine Soheil Feizi AAML 62 107 0 21 Nov 2019
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks Alexander Levine Soheil Feizi AAML 30 61 0 23 Oct 2019
Adversarial Robustness through Local Linearization Chongli Qin James Martens Sven Gowal Dilip Krishnan Krishnamurthy Dvijotham Alhussein Fawzi Soham De Robert Stanforth Pushmeet Kohli AAML 64 308 0 04 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 67 347 0 14 Jun 2019
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks Mahyar Fazlyab Alexander Robey Hamed Hassani M. Morari George J. Pappas 87 457 0 12 Jun 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 66 549 0 09 Jun 2019
Functional Adversarial Attacks Cassidy Laidlaw Soheil Feizi AAML 64 185 0 29 May 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 141 2,038 0 08 Feb 2019
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation Sahil Singla Eric Wallace Shi Feng Soheil Feizi FAtt 62 59 0 01 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 129 2,549 0 24 Jan 2019
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 72 319 0 23 Nov 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 86 321 0 13 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 43 23 0 06 Nov 2018
Semidefinite relaxations for certifying robustness to adversarial examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 96 439 0 02 Nov 2018
Efficient Neural Network Robustness Certification with General Activation Functions Huan Zhang Tsui-Wei Weng Pin-Yu Chen Cho-Jui Hsieh Luca Daniel AAML 89 760 0 02 Nov 2018
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models Sven Gowal Krishnamurthy Dvijotham Robert Stanforth Rudy Bunel Chongli Qin J. Uesato Relja Arandjelović Timothy A. Mann Pushmeet Kohli AAML 76 556 0 30 Oct 2018
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications Huan Zhang Pengchuan Zhang Cho-Jui Hsieh AAML 61 63 0 28 Oct 2018
Provable Robustness of ReLU networks via Maximization of Linear Regions Francesco Croce Maksym Andriushchenko Matthias Hein 72 166 0 17 Oct 2018
Efficient Formal Safety Analysis of Neural Networks Shiqi Wang Kexin Pei Justin Whitehouse Junfeng Yang Suman Jana AAML 65 404 0 19 Sep 2018
Scaling provable adversarial defenses Eric Wong Frank R. Schmidt J. H. Metzen J. Zico Kolter AAML 76 448 0 31 May 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 80 529 0 28 May 2018
The Singular Values of Convolutional Layers Hanie Sedghi Vineet Gupta Philip M. Long FAtt 81 202 0 26 May 2018
Training verified learners with learned verifiers Krishnamurthy Dvijotham Sven Gowal Robert Stanforth Relja Arandjelović Brendan O'Donoghue J. Uesato Pushmeet Kohli OOD 54 168 0 25 May 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 82 1,177 0 17 May 2018
Towards Fast Computation of Certified Robustness for ReLU Networks Tsui-Wei Weng Huan Zhang Hongge Chen Zhao Song Cho-Jui Hsieh Duane S. Boning Inderjit S. Dhillon Luca Daniel AAML 100 694 0 25 Apr 2018
On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses Anish Athalye Nicholas Carlini AAML 50 170 0 10 Apr 2018
A Dual Approach to Scalable Verification of Deep Networks Krishnamurthy Dvijotham Dvijotham Robert Stanforth Sven Gowal Timothy A. Mann Pushmeet Kohli 52 399 0 17 Mar 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 155 4,437 0 16 Feb 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks J. Uesato Brendan O'Donoghue Aaron van den Oord Pushmeet Kohli AAML 147 604 0 15 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 94 934 0 09 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 216 3,185 0 01 Feb 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 105 968 0 29 Jan 2018
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 88 420 0 02 Dec 2017
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 123 1,501 0 02 Nov 2017
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification Xiaoyu Cao Neil Zhenqiang Gong AAML 64 209 0 17 Sep 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 280 8,878 0 25 Aug 2017
An approach to reachability analysis for feed-forward ReLU neural networks A. Lomuscio Lalit Maganti 63 359 0 22 Jun 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 301 12,063 0 19 Jun 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation Matthias Hein Maksym Andriushchenko AAML 105 511 0 23 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 118 1,857 0 20 May 2017
Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks Rüdiger Ehlers 102 626 0 03 May 2017
Maximum Resilience of Artificial Neural Networks Chih-Hong Cheng Georg Nührenberg Harald Ruess AAML 99 284 0 28 Apr 2017
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 146 2,733 0 13 Apr 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 315 1,867 0 03 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 469 3,140 0 04 Nov 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 211 943 0 21 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 534 5,897 0 08 Jul 2016