Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

1 February 2018

Papers citing "Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples"

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Title
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan X. Lin AAML FAtt 24 43 0 03 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 17 151 0 01 Apr 2019
Defending against adversarial attacks by randomized diversification O. Taran Shideh Rezaeifar T. Holotyak Slava Voloshynovskiy AAML 21 38 0 01 Apr 2019
Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 21 219 0 28 Mar 2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks Francesco Croce Jonas Rauber Matthias Hein AAML 20 30 0 27 Mar 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 32 75 0 25 Mar 2019
The Random Conditional Distribution for Higher-Order Probabilistic Inference Zenna Tavares Xin Zhang Edgar Minaysan Javier Burroni Rajesh Ranganath Armando Solar-Lezama 22 9 0 25 Mar 2019
The LogBarrier adversarial attack: making effective use of decision boundary information Chris Finlay Aram-Alexandre Pooladian Adam M. Oberman AAML 26 25 0 25 Mar 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
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 29 2 0 10 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
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN Ke Sun Zhanxing Zhu Zhouchen Lin AAML 19 20 0 28 Feb 2019
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 24 122 0 28 Feb 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 20 116 0 27 Feb 2019
Disentangled Deep Autoencoding Regularization for Robust Image Classification Zhenyu Duan Martin Renqiang Min Erran L. Li Mingbo Cai Yi Tian Xu Bingbing Ni 13 2 0 27 Feb 2019
Verification of Non-Linear Specifications for Neural Networks Chongli Qin Krishnamurthy Dvijotham Dvijotham Brendan O'Donoghue Rudy Bunel Robert Stanforth Sven Gowal J. Uesato G. Swirszcz Pushmeet Kohli AAML 14 43 0 25 Feb 2019
On the Sensitivity of Adversarial Robustness to Input Data Distributions G. Ding Kry Yik-Chau Lui Xiaomeng Jin Luyu Wang Ruitong Huang OOD 26 59 0 22 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 27 210 0 21 Feb 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 27 175 0 13 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 17 1,995 0 08 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 27 318 0 29 Jan 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 41 434 0 25 Jan 2019
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples Kamil Nar Orhan Ocal S. Shankar Sastry Kannan Ramchandran AAML 27 54 0 24 Jan 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 19 144 0 15 Jan 2019
ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System Huangxun Chen Chenyu Huang Qianyi Huang Qian Zhang Wei Wang AAML 31 26 0 12 Jan 2019
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification L. G. Hafemann R. Sabourin Luiz Eduardo Soares de Oliveira AAML 11 42 0 10 Jan 2019
Image Super-Resolution as a Defense Against Adversarial Attacks Aamir Mustafa Salman H. Khan Munawar Hayat Jianbing Shen Ling Shao AAML SupR 24 167 0 07 Jan 2019
Adversarial Attack and Defense on Graph Data: A Survey Lichao Sun Yingtong Dou Carl Yang Ji Wang Yixin Liu Philip S. Yu Lifang He Yangqiu Song GNN AAML 23 275 0 26 Dec 2018
A Multiversion Programming Inspired Approach to Detecting Audio Adversarial Examples Qiang Zeng Jianhai Su Chenglong Fu Golam Kayas Lannan Luo AAML 27 46 0 26 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 55 553 0 13 Dec 2018
Adversarial Framing for Image and Video Classification Konrad Zolna Michal Zajac Negar Rostamzadeh Pedro H. O. Pinheiro AAML 30 60 0 11 Dec 2018
On the Security of Randomized Defenses Against Adversarial Samples K. Sharad G. Marson H. Truong Ghassan O. Karame AAML 25 1 0 11 Dec 2018
Defending Against Universal Perturbations With Shared Adversarial Training Chaithanya Kumar Mummadi Thomas Brox J. H. Metzen AAML 18 60 0 10 Dec 2018
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu L. V. D. van der Maaten Alan Yuille Kaiming He 44 904 0 09 Dec 2018
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 21 270 0 06 Dec 2018
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples Huangyi Ge Sze Yiu Chau Bruno Ribeiro Ninghui Li AAML 27 1 0 05 Dec 2018
Prototype-based Neural Network Layers: Incorporating Vector Quantization S. Saralajew Lars Holdijk Maike Rees T. Villmann MQ 22 15 0 04 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 24 169 0 03 Dec 2018
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 173 288 0 02 Dec 2018
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Qi Lei Lingfei Wu Pin-Yu Chen A. Dimakis Inderjit S. Dhillon Michael Witbrock AAML 15 92 0 01 Dec 2018
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting Artur Bekasov Iain Murray AAML BDL 20 14 0 29 Nov 2018
A randomized gradient-free attack on ReLU networks Francesco Croce Matthias Hein AAML 37 21 0 28 Nov 2018
Noisy Computations during Inference: Harmful or Helpful? Minghai Qin D. Vučinić AAML 11 5 0 26 Nov 2018
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 29 318 0 23 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 397 0 19 Nov 2018
Mathematical Analysis of Adversarial Attacks Zehao Dou Stanley J. Osher Bao Wang AAML 24 18 0 15 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 15 68 0 13 Nov 2018
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
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 21 23 0 06 Nov 2018
Learning to Defend by Learning to Attack Haoming Jiang Zhehui Chen Yuyang Shi Bo Dai T. Zhao 18 22 0 03 Nov 2018