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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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advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch G. Ding Luyu Wang Xiaomeng Jin 74 183 0 20 Feb 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 147 905 0 18 Feb 2019
Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces Mohammad Saidur Rahman Mohsen Imani Nate Mathews M. Wright AAML 86 81 0 18 Feb 2019
AuxBlocks: Defense Adversarial Example via Auxiliary Blocks Yueyao Yu Pengfei Yu Wenye Li AAML 18 6 0 18 Feb 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 80 176 0 13 Feb 2019
Model Compression with Adversarial Robustness: A Unified Optimization Framework Shupeng Gui Haotao Wang Chen Yu Haichuan Yang Zhangyang Wang Ji Liu MQ 79 139 0 10 Feb 2019
When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks Chao-Han Huck Yang Yi-Chieh Liu Pin-Yu Chen Xiaoli Ma Y. Tsai BDL AAML CML 80 21 0 09 Feb 2019
Understanding the One-Pixel Attack: Propagation Maps and Locality Analysis Danilo Vasconcellos Vargas Jiawei Su FAtt AAML 41 38 0 08 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 219 2,057 0 08 Feb 2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation Juyeon Heo Sunghwan Joo Taesup Moon AAML FAtt 126 206 0 06 Feb 2019
Are All Layers Created Equal? Chiyuan Zhang Samy Bengio Y. Singer 111 140 0 06 Feb 2019
Theoretical evidence for adversarial robustness through randomization Rafael Pinot Laurent Meunier Alexandre Araujo H. Kashima Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 110 83 0 04 Feb 2019
Computational Limitations in Robust Classification and Win-Win Results Akshay Degwekar Preetum Nakkiran Vinod Vaikuntanathan 67 39 0 04 Feb 2019
Robustness of Generalized Learning Vector Quantization Models against Adversarial Attacks S. Saralajew Lars Holdijk Maike Rees T. Villmann OOD 49 19 0 01 Feb 2019
Robustness Certificates Against Adversarial Examples for ReLU Networks Sahil Singla Soheil Feizi AAML 68 21 0 01 Feb 2019
Augmenting Model Robustness with Transformation-Invariant Attacks Houpu Yao Zhe Wang Guangyu Nie Yassine Mazboudi Yezhou Yang Yi Ren AAML OOD 31 3 0 31 Jan 2019
A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance A. Shamir Itay Safran Eyal Ronen O. Dunkelman GAN AAML 59 95 0 30 Jan 2019
Reliable Smart Road Signs M. O. Sayin Chung-Wei Lin Eunsuk Kang Shiníchi Shiraishi Tamer Basar AAML 23 0 0 30 Jan 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 137 320 0 29 Jan 2019
Improving Adversarial Robustness of Ensembles with Diversity Training Sanjay Kariyappa Moinuddin K. Qureshi AAML FedML 88 138 0 28 Jan 2019
Defense Methods Against Adversarial Examples for Recurrent Neural Networks Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML GAN 81 42 0 28 Jan 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 106 441 0 25 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 254 2,566 0 24 Jan 2019
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples Kamil Nar Orhan Ocal S. Shankar Sastry Kannan Ramchandran AAML 90 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 76 145 0 15 Jan 2019
ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System Huangxun Chen Chenyu Huang Qianyi Huang Qian Zhang Wei Wang AAML 75 28 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 55 44 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 100 176 0 07 Jan 2019
Adversarial CAPTCHAs Chenghui Shi Xiaogang Xu S. Ji Kai Bu Jianhai Chen R. Beyah Ting Wang AAML 51 53 0 04 Jan 2019
Adversarial Robustness May Be at Odds With Simplicity Preetum Nakkiran AAML 109 108 0 02 Jan 2019
AIR5: Five Pillars of Artificial Intelligence Research Yew-Soon Ong Abhishek Gupta 74 29 0 30 Dec 2018
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 139 286 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 55 46 0 26 Dec 2018
A Data-driven Adversarial Examples Recognition Framework via Adversarial Feature Genome Li Chen Qi Li Jiawei Zhu Jian Peng Haifeng Li AAML 59 3 0 25 Dec 2018
PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning Mehdi Jafarnia-Jahromi Tasmin Chowdhury Hsin-Tai Wu S. Mukherjee AAML 47 4 0 25 Dec 2018
DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense Hang Zhou Kejiang Chen Weiming Zhang Han Fang Wenbo Zhou Nenghai Yu 3DPC 69 8 0 25 Dec 2018
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks T. Brunner Frederik Diehl Michael Truong-Le Alois Knoll MLAU AAML 77 117 0 24 Dec 2018
Spartan Networks: Self-Feature-Squeezing Neural Networks for increased robustness in adversarial settings François Menet Paul Berthier José M. Fernandez M. Gagnon AAML 27 10 0 17 Dec 2018
Designing Adversarially Resilient Classifiers using Resilient Feature Engineering Kevin Eykholt A. Prakash AAML 60 4 0 17 Dec 2018
Trust Region Based Adversarial Attack on Neural Networks Z. Yao A. Gholami Peng Xu Kurt Keutzer Michael W. Mahoney AAML 64 54 0 16 Dec 2018
Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples E. Balda Arash Behboodi R. Mathar AAML 30 5 0 15 Dec 2018
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing Jingyi Wang Guoliang Dong Jun Sun Xinyu Wang Peixin Zhang AAML 78 191 0 14 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 187 559 0 13 Dec 2018
Adversarial Framing for Image and Video Classification Konrad Zolna Michal Zajac Negar Rostamzadeh Pedro H. O. Pinheiro AAML 106 61 0 11 Dec 2018
On the Security of Randomized Defenses Against Adversarial Samples K. Sharad G. Marson H. Truong Ghassan O. Karame AAML 47 1 0 11 Dec 2018
Defending Against Universal Perturbations With Shared Adversarial Training Chaithanya Kumar Mummadi Thomas Brox J. H. Metzen AAML 84 60 0 10 Dec 2018
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 172 916 0 09 Dec 2018
Fooling Network Interpretation in Image Classification Akshayvarun Subramanya Vipin Pillai Hamed Pirsiavash AAML FAtt 49 7 0 06 Dec 2018
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 112 274 0 06 Dec 2018
The Limitations of Model Uncertainty in Adversarial Settings Kathrin Grosse David Pfaff M. Smith Michael Backes AAML 63 34 0 06 Dec 2018