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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
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations Chi Zhang Jinghan Jia Burhaneddin Yaman S. Moeller Sijia Liu Mingyi Hong Mehmet Akçakaya AAML 56 8 0 25 Feb 2021
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints Maura Pintor Fabio Roli Wieland Brendel Battista Biggio AAML 92 73 0 25 Feb 2021
Robust SleepNets Yigit Can Alparslan Edward J. Kim AAML 30 1 0 24 Feb 2021
Graphfool: Targeted Label Adversarial Attack on Graph Embedding Jinyin Chen Xiang Lin Dunjie Zhang Haibin Zheng Guohan Huang Hui Xiong Xiang Lin AAML 79 3 0 24 Feb 2021
Multiplicative Reweighting for Robust Neural Network Optimization Noga Bar Tomer Koren Raja Giryes OOD NoLa 83 9 0 24 Feb 2021
Non-Singular Adversarial Robustness of Neural Networks Yu-Lin Tsai Chia-Yi Hsu Chia-Mu Yu Pin-Yu Chen AAML OOD 56 5 0 23 Feb 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses Chengyuan Yao Pavol Bielik Petar Tsankov Martin Vechev AAML 99 24 0 23 Feb 2021
Rethinking Natural Adversarial Examples for Classification Models Xiao-Li Li Jianmin Li Ting Dai Jie Shi Jun Zhu Xiaolin Hu AAML VLM 128 13 0 23 Feb 2021
Effective and Efficient Vote Attack on Capsule Networks Jindong Gu Baoyuan Wu Volker Tresp AAML 70 27 0 19 Feb 2021
Random Projections for Improved Adversarial Robustness Ginevra Carbone G. Sanguinetti Luca Bortolussi AAML 61 2 0 18 Feb 2021
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids Jiangnan Li Yingyuan Yang Jinyuan Stella Sun K. Tomsovic Hairong Qi AAML 127 15 0 17 Feb 2021
Domain Impression: A Source Data Free Domain Adaptation Method V. Kurmi Venkatesh Subramanian Vinay P. Namboodiri TTA 217 152 0 17 Feb 2021
Just Noticeable Difference for Deep Machine Vision Jian Jin Xingxing Zhang Xin Fu Huan Zhang Weisi Lin Jian Lou Yao Zhao VLM 266 31 0 16 Feb 2021
Just Noticeable Difference for Machine Perception and Generation of Regularized Adversarial Images with Minimal Perturbation Adil Kaan Akan Emre Akbas Fatoş T. Yarman Vural AAML 33 3 0 16 Feb 2021
Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows Anubhab Ghosh Antoine Honoré Dong Liu G. Henter Saikat Chatterjee BDL VLM 54 7 0 15 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 95 138 0 14 Feb 2021
Adversarial Attack on Network Embeddings via Supervised Network Poisoning Viresh Gupta Tanmoy Chakraborty AAML 74 12 0 14 Feb 2021
A Computability Perspective on (Verified) Machine Learning T. Crook J. Morgan A. Pauly M. Roggenbach FaML 39 3 0 12 Feb 2021
Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards A Fourier Perspective Chaoning Zhang Philipp Benz Adil Karjauv In So Kweon AAML 94 42 0 12 Feb 2021
Defense Against Reward Poisoning Attacks in Reinforcement Learning Kiarash Banihashem Adish Singla Goran Radanović AAML 92 27 0 10 Feb 2021
Dompteur: Taming Audio Adversarial Examples Thorsten Eisenhofer Lea Schonherr Joel Frank Lars Speckemeier D. Kolossa Thorsten Holz AAML 85 25 0 10 Feb 2021
RoBIC: A benchmark suite for assessing classifiers robustness Thibault Maho Benoît Bonnet Teddy Furon Erwan Le Merrer AAML 56 4 0 10 Feb 2021
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis Fengting Li Xuankai Liu Xiaoli Zhang Qi Li Kun Sun Kang Li AAML 73 13 0 10 Feb 2021
Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers Jacob Mitchell Springer Melanie Mitchell Garrett Kenyon AAML 56 13 0 09 Feb 2021
Security and Privacy for Artificial Intelligence: Opportunities and Challenges Ayodeji Oseni Nour Moustafa Helge Janicke Peng Liu Z. Tari A. Vasilakos AAML 67 52 0 09 Feb 2021
Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples Ömer Faruk Tuna Ferhat Ozgur Catak M. T. Eskil AAML 90 33 0 08 Feb 2021
Adversarial Imaging Pipelines Buu Phan Fahim Mannan Felix Heide AAML 53 26 0 07 Feb 2021
SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation Wuxinlin Cheng Chenhui Deng Zhiqiang Zhao Yaohui Cai Zhiru Zhang Zhuo Feng AAML 73 14 0 07 Feb 2021
Adversarial Attacks and Defenses in Physiological Computing: A Systematic Review Dongrui Wu Jiaxin Xu Weili Fang Yi Zhang Liuqing Yang Xiaodong Xu Hanbin Luo Xiang Yu AAML 127 25 0 04 Feb 2021
IWA: Integrated Gradient based White-box Attacks for Fooling Deep Neural Networks Yixiang Wang Jiqiang Liu Xiaolin Chang J. Misic Vojislav B. Mišić AAML 69 12 0 03 Feb 2021
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice V. Kulkarni M. Gawali A. Kharat VLM 117 21 0 03 Feb 2021
Towards Robust Neural Networks via Close-loop Control Zhuotong Chen Qianxiao Li Zheng Zhang OOD AAML 82 25 0 03 Feb 2021
Landmark Breaker: Obstructing DeepFake By Disturbing Landmark Extraction Pu Sun Yuezun Li H. Qi Siwei Lyu 55 17 0 01 Feb 2021
Admix: Enhancing the Transferability of Adversarial Attacks Xiaosen Wang Xu He Jingdong Wang Kun He AAML 151 201 0 31 Jan 2021
Cortical Features for Defense Against Adversarial Audio Attacks Ilya Kavalerov Frank Zheng W. Czaja Ramalingam Chellappa AAML 49 0 0 30 Jan 2021
You Only Query Once: Effective Black Box Adversarial Attacks with Minimal Repeated Queries Devin Willmott Anit Kumar Sahu Fatemeh Sheikholeslami Filipe Condessa Zico Kolter MLAU AAML 61 3 0 29 Jan 2021
Adversarial Learning with Cost-Sensitive Classes Hao Shen Sihong Chen Ran Wang Xizhao Wang AAML 70 11 0 29 Jan 2021
Improving Neural Network Robustness through Neighborhood Preserving Layers Bingyuan Liu Christopher Malon Lingzhou Xue E. Kruus AAML 35 5 0 28 Jan 2021
Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting F. Nesti Alessandro Biondi Giorgio Buttazzo AAML 46 40 0 27 Jan 2021
The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs Xinwei Zhao Matthew C. Stamm AAML 49 4 0 26 Jan 2021
Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers Xinwei Zhao Matthew C. Stamm AAML 47 3 0 26 Jan 2021
Visual explanation of black-box model: Similarity Difference and Uniqueness (SIDU) method Satya M. Muddamsetty M. N. Jahromi Andreea-Emilia Ciontos Laura M. Fenoy T. Moeslund AAML 90 26 0 26 Jan 2021
Spectral Leakage and Rethinking the Kernel Size in CNNs Nergis Tomen Jan van Gemert AAML 61 19 0 25 Jan 2021
A Survey on Active Deep Learning: From Model-driven to Data-driven Peng Liu Lizhe Wang Guojin He Lei Zhao 85 14 0 25 Jan 2021
A Comprehensive Evaluation Framework for Deep Model Robustness Jun Guo Wei Bao Jiakai Wang Yuqing Ma Xing Gao Gang Xiao Aishan Liu Zehao Zhao Xianglong Liu Wenjun Wu AAML ELM 97 61 0 24 Jan 2021
A Transferable Anti-Forensic Attack on Forensic CNNs Using A Generative Adversarial Network Xinwei Zhao Chen Chen Matthew C. Stamm GAN AAML 41 4 0 23 Jan 2021
Online Adversarial Purification based on Self-Supervision Changhao Shi Chester Holtz Zhengchao Wan AAML 82 57 0 23 Jan 2021
Generating Black-Box Adversarial Examples in Sparse Domain Ieee Hadi Zanddizari Student Member Behnam Zeinali Jerome Chang AAML 46 7 0 22 Jan 2021
A Person Re-identification Data Augmentation Method with Adversarial Defense Effect Yunpeng Gong Zhiyong Zeng Liwen Chen Yi-Xiao Luo Bin Weng Feng Ye AAML 83 19 0 21 Jan 2021
Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem Matthew J. Colbrook Vegard Antun A. Hansen 119 136 0 20 Jan 2021