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"

50 / 905 papers shown

Title
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 37 1,090 0 27 Dec 2017
ReabsNet: Detecting and Revising Adversarial Examples Jiefeng Chen Zihang Meng Changtian Sun Weiliang Tang Yinglun Zhu AAML GAN 29 4 0 21 Dec 2017
Training Ensembles to Detect Adversarial Examples Alexander Bagnall Razvan Bunescu Gordon Stewart AAML 26 38 0 11 Dec 2017
NAG: Network for Adversary Generation Konda Reddy Mopuri Utkarsh Ojha Utsav Garg R. Venkatesh Babu AAML 27 144 0 09 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 40 1,391 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 24 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 44 130 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 58 855 0 29 Oct 2017
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 80 858 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-Yu 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 33 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 34 134 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 39 128 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 89 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 19 154 0 13 Jun 2017
Towards Robust Detection of Adversarial Examples Tianyu Pang Chao Du Yinpeng Dong Jun Zhu AAML 39 18 0 02 Jun 2017
Classification regions of deep neural networks Alhussein Fawzi Seyed-Mohsen Moosavi-Dezfooli P. Frossard Stefano Soatto 31 51 0 26 May 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 13 1,199 0 25 May 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation Matthias Hein Maksym Andriushchenko AAML 45 506 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 14 216 0 23 May 2017
Regularizing deep networks using efficient layerwise adversarial training S. Sankaranarayanan Arpit Jain Rama Chellappa Ser Nam Lim AAML 30 97 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 29 63 0 19 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 73 2,701 0 19 May 2017
DeepCorrect: Correcting DNN models against Image Distortions Tejas S. Borkar Lina Karam 27 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
Universal Adversarial Perturbations Against Semantic Image Segmentation J. H. Metzen Mummadi Chaithanya Kumar Thomas Brox Volker Fischer AAML 30 287 0 19 Apr 2017
The Space of Transferable Adversarial Examples Florian Tramèr Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML SILM 41 555 0 11 Apr 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 25 1,237 0 04 Apr 2017
Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective Seong Joon Oh Mario Fritz Bernt Schiele CVBM AAML 339 160 0 28 Mar 2017
Blocking Transferability of Adversarial Examples in Black-Box Learning Systems Hossein Hosseini Yize Chen Sreeram Kannan Baosen Zhang Radha Poovendran AAML 30 106 0 13 Mar 2017
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin Zhang-Wei Hong Yuan-Hong Liao Meng-Li Shih Ming-Yu Liu Min Sun AAML 28 411 0 08 Mar 2017
Compositional Falsification of Cyber-Physical Systems with Machine Learning Components T. Dreossi Alexandre Donzé S. Seshia AAML 32 230 0 02 Mar 2017
Simple Black-Box Adversarial Perturbations for Deep Networks Nina Narodytska S. Kasiviswanathan AAML 27 237 0 19 Dec 2016
Universal adversarial perturbations Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi Omar Fawzi P. Frossard AAML 62 2,513 0 26 Oct 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 933 0 21 Oct 2016
Robustness of classifiers: from adversarial to random noise Alhussein Fawzi Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 16 367 0 31 Aug 2016