DeepFool: a simple and accurate method to fool deep neural networks

14 November 2015

Seyed-Mohsen Moosavi-Dezfooli

Papers citing "DeepFool: a simple and accurate method to fool deep neural networks"

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Title
Adversarial vulnerability for any classifier Alhussein Fawzi Hamza Fawzi Omar Fawzi AAML 33 248 0 23 Feb 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan Yiwen Guo Changshui Zhang AAML 38 109 0 23 Feb 2018
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks Gaurav Goswami Nalini Ratha Akshay Agarwal Richa Singh Mayank Vatsa AAML 21 165 0 22 Feb 2018
Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch João Monteiro Isabela Albuquerque Zahid Akhtar T. Falk AAML 41 29 0 21 Feb 2018
Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections Xin Zhang Armando Solar-Lezama Rishabh Singh FAtt 21 63 0 21 Feb 2018
On Lyapunov exponents and adversarial perturbation Vinay Uday Prabhu Nishant Desai John Whaley AAML 20 4 0 20 Feb 2018
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Siwei Li Li-Wei Chen Michael E. Kounavis Duen Horng Chau FedML AAML 43 225 0 19 Feb 2018
Adversarial Texts with Gradient Methods Zhitao Gong Wenlu Wang Yangqiu Song D. Song Wei-Shinn Ku AAML 34 77 0 22 Jan 2018
A3T: Adversarially Augmented Adversarial Training Akram Erraqabi A. Baratin Yoshua Bengio Simon Lacoste-Julien AAML 32 9 0 12 Jan 2018
Less is More: Culling the Training Set to Improve Robustness of Deep Neural Networks Yongshuai Liu Jiyu Chen Hao Chen AAML 27 14 0 09 Jan 2018
Did you hear that? Adversarial Examples Against Automatic Speech Recognition M. Alzantot Bharathan Balaji Mani B. Srivastava AAML 18 251 0 02 Jan 2018
A General Framework for Adversarial Examples with Objectives Mahmood Sharif Sruti Bhagavatula Lujo Bauer Michael K. Reiter AAML GAN 13 191 0 31 Dec 2017
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 28 1,088 0 27 Dec 2017
ReabsNet: Detecting and Revising Adversarial Examples Jiefeng Chen Zihang Meng Changtian Sun Weiliang Tang Yinglun Zhu AAML GAN 24 4 0 21 Dec 2017
Training Ensembles to Detect Adversarial Examples Alexander Bagnall Razvan Bunescu Gordon Stewart AAML 23 38 0 11 Dec 2017
NAG: Network for Adversary Generation Konda Reddy Mopuri Utkarsh Ojha Utsav Garg R. Venkatesh Babu AAML 21 144 0 09 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 40 1,390 0 08 Dec 2017
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning Hongge Chen Huan Zhang Pin-Yu Chen Jinfeng Yi Cho-Jui Hsieh GAN AAML 35 49 0 06 Dec 2017
Improving Network Robustness against Adversarial Attacks with Compact Convolution Rajeev Ranjan S. Sankaranarayanan Carlos D. Castillo Rama Chellappa AAML 21 14 0 03 Dec 2017
Measuring the tendency of CNNs to Learn Surface Statistical Regularities Jason Jo Yoshua Bengio AAML 26 249 0 30 Nov 2017
Geometric robustness of deep networks: analysis and improvement Can Kanbak Seyed-Mohsen Moosavi-Dezfooli P. Frossard OOD AAML 41 130 0 24 Nov 2017
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training Xi Wu Uyeong Jang Jiefeng Chen Lingjiao Chen S. Jha AAML 35 21 0 21 Nov 2017
Adversarial Attacks Beyond the Image Space Fangyin Wei Chenxi Liu Yu-Siang Wang Weichao Qiu Lingxi Xie Yu-Wing Tai Chi-Keung Tang Alan Yuille AAML 41 145 0 20 Nov 2017
Attacking Binarized Neural Networks A. Galloway Graham W. Taylor M. Moussa MQ AAML 14 104 0 01 Nov 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 43 855 0 29 Oct 2017
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 80 857 0 29 Oct 2017
On Data-Driven Saak Transform C.-C. Jay Kuo Yueru Chen AI4TS 21 93 0 11 Oct 2017
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight Yen-Chen Lin Ming Liu Min Sun Jia-Bin Huang AAML 29 48 0 02 Oct 2017
Provably Minimally-Distorted Adversarial Examples Nicholas Carlini Guy Katz Clark W. Barrett D. Dill AAML 17 89 0 29 Sep 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 24 637 0 13 Sep 2017
Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks Thilo Strauss Markus Hanselmann Andrej Junginger Holger Ulmer AAML 20 134 0 11 Sep 2017
DeepFense: Online Accelerated Defense Against Adversarial Deep Learning B. Rouhani Mohammad Samragh Mojan Javaheripi T. Javidi F. Koushanfar AAML 12 15 0 08 Sep 2017
Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid Marco Melis Ambra Demontis Battista Biggio Gavin Brown Giorgio Fumera Fabio Roli AAML 21 98 0 23 Aug 2017
Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples Yinpeng Dong Hang Su Jun Zhu Fan Bao AAML 39 127 0 18 Aug 2017
UPSET and ANGRI : Breaking High Performance Image Classifiers Sayantan Sarkar Ankan Bansal U. Mahbub Rama Chellappa AAML 30 108 0 04 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks A. Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 83 11,872 0 19 Jun 2017
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong Warren He James Wei Xinyun Chen Nicholas Carlini D. Song AAML 43 242 0 15 Jun 2017
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples Yizhen Wang S. Jha Kamalika Chaudhuri AAML 13 154 0 13 Jun 2017
Towards Robust Detection of Adversarial Examples Tianyu Pang Chao Du Yinpeng Dong Jun Zhu AAML 36 18 0 02 Jun 2017
Classification regions of deep neural networks Alhussein Fawzi Seyed-Mohsen Moosavi-Dezfooli P. Frossard Stefano Soatto 21 51 0 26 May 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 13 1,198 0 25 May 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation Matthias Hein Maksym Andriushchenko AAML 45 505 0 23 May 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction Bin Liang Hongcheng Li Miaoqiang Su Xirong Li Wenchang Shi Xiaofeng Wang AAML 12 215 0 23 May 2017
Regularizing deep networks using efficient layerwise adversarial training S. Sankaranarayanan Arpit Jain Rama Chellappa Ser Nam Lim AAML 30 96 0 22 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 61 1,842 0 20 May 2017
MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense Sailik Sengupta Tathagata Chakraborti S. Kambhampati AAML 15 63 0 19 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 65 2,699 0 19 May 2017
DeepCorrect: Correcting DNN models against Image Distortions Tejas S. Borkar Lina Karam 21 93 0 05 May 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 86 798 0 28 Apr 2017