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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
Type I Attack for Generative Models Chengjin Sun Sizhe Chen Jia Cai Xiaolin Huang AAML 65 11 0 04 Mar 2020
Discriminative Multi-level Reconstruction under Compact Latent Space for One-Class Novelty Detection Jaewoo Park Yoon Gyo Jung Andrew Beng Jin Teoh 22 4 0 03 Mar 2020
Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems Nataniel Ruiz Sarah Adel Bargal Stan Sclaroff PICV AAML 103 121 0 03 Mar 2020
Adversarial Network Traffic: Towards Evaluating the Robustness of Deep Learning-Based Network Traffic Classification A. M. Sadeghzadeh Saeed Shiravi R. Jalili OOD AAML 84 63 0 03 Mar 2020
Hidden Cost of Randomized Smoothing Jeet Mohapatra Ching-Yun Ko Tsui-Wei Weng Weng Sijia Liu Pin-Yu Chen Luca Daniel AAML 49 11 0 02 Mar 2020
Reachability Analysis for Feed-Forward Neural Networks using Face Lattices Xiaodong Yang Hoang-Dung Tran Weiming Xiang Taylor Johnson CVBM 94 19 0 02 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 129 67 0 02 Mar 2020
Why is the Mahalanobis Distance Effective for Anomaly Detection? Ryo Kamoi Kei Kobayashi OODD 203 60 0 01 Mar 2020
Applying Tensor Decomposition to image for Robustness against Adversarial Attack Seungju Cho Tae Joon Jun Mingu Kang Daeyoung Kim AAML 40 3 0 28 Feb 2020
Robust Unsupervised Neural Machine Translation with Adversarial Denoising Training Haipeng Sun Rui Wang Kehai Chen Xugang Lu Masao Utiyama Eiichiro Sumita Tiejun Zhao 49 4 0 28 Feb 2020
Are L2 adversarial examples intrinsically different? Mingxuan Li Jingyuan Wang Yufan Wu AAML 16 0 0 28 Feb 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 71 6 0 28 Feb 2020
On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks Yue Zhao Yuwei Wu Caihua Chen A. Lim 3DPC 97 72 0 27 Feb 2020
Defense-PointNet: Protecting PointNet Against Adversarial Attacks Yu Zhang G. Liang Tawfiq Salem Nathan Jacobs AAML 3DPC 81 27 0 27 Feb 2020
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks Sandesh Kamath Amit Deshpande Subrahmanyam Kambhampati Venkata V. Balasubramanian 88 12 0 26 Feb 2020
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 150 39 0 26 Feb 2020
Real-Time Detectors for Digital and Physical Adversarial Inputs to Perception Systems Y. Kantaros Taylor J. Carpenter Kaustubh Sridhar Yahan Yang Insup Lee James Weimer AAML 63 13 0 23 Feb 2020
Non-Intrusive Detection of Adversarial Deep Learning Attacks via Observer Networks K. Sivamani R. Sahay Aly El Gamal AAML 35 3 0 22 Feb 2020
Temporal Sparse Adversarial Attack on Sequence-based Gait Recognition Ziwen He Wei Wang Jing Dong Tieniu Tan AAML 89 25 0 22 Feb 2020
Adversarial Detection and Correction by Matching Prediction Distributions G. Vacanti A. V. Looveren AAML 110 16 0 21 Feb 2020
Towards Certifiable Adversarial Sample Detection Ilia Shumailov Yiren Zhao Robert D. Mullins Ross J. Anderson AAML 51 13 0 20 Feb 2020
Boosting Adversarial Training with Hypersphere Embedding Tianyu Pang Xiao Yang Yinpeng Dong Kun Xu Jun Zhu Hang Su AAML 89 156 0 20 Feb 2020
Blind Adversarial Network Perturbations Milad Nasr Alireza Bahramali Amir Houmansadr AAML 68 6 0 16 Feb 2020
Hold me tight! Influence of discriminative features on deep network boundaries Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 47 50 0 15 Feb 2020
Manifold-based Test Generation for Image Classifiers Taejoon Byun Abhishek Vijayakumar Sanjai Rayadurgam D. Cofer 37 9 0 15 Feb 2020
Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges T. H. Le Hao Chen Muhammad Ali Babar VLM 147 155 0 13 Feb 2020
CEB Improves Model Robustness Ian S. Fischer Alexander A. Alemi AAML 137 30 0 13 Feb 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 113 505 0 12 Feb 2020
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models Xiao Zang Yi Xie Jie Chen Bo Yuan AAML 76 48 0 12 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 88 64 0 11 Feb 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks Ginevra Carbone Matthew Wicker Luca Laurenti A. Patané Luca Bortolussi G. Sanguinetti AAML 104 79 0 11 Feb 2020
Adversarial Data Encryption Yingdong Hu Liang Zhang W. Shan Xiaoxiao Qin Jinghuai Qi Zhenzhou Wu Yang Yuan FedML MedIm 34 0 0 10 Feb 2020
Category-wise Attack: Transferable Adversarial Examples for Anchor Free Object Detection Quanyu Liao Xin Wang Bin Kong Siwei Lyu Youbing Yin Qi Song Xi Wu AAML 94 8 0 10 Feb 2020
Input Validation for Neural Networks via Runtime Local Robustness Verification Jiangchao Liu Liqian Chen A. Miné Ji Wang AAML 47 10 0 09 Feb 2020
Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks Lu Chen Wenyuan Xu AAML 44 21 0 08 Feb 2020
Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification Meet P. Vadera Satya Narayan Shukla B. Jalaeian Benjamin M. Marlin AAML BDL 45 6 0 07 Feb 2020
RAID: Randomized Adversarial-Input Detection for Neural Networks Hasan Ferit Eniser M. Christakis Valentin Wüstholz AAML 69 15 0 07 Feb 2020
Quasi-Equivalence of Width and Depth of Neural Networks Fenglei Fan Rongjie Lai Ge Wang 72 11 0 06 Feb 2020
An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models Yao Deng Xi Zheng Tianyi Zhang Chen Chen Guannan Lou Miryung Kim AAML 59 143 0 06 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study David Mickisch F. Assion Florens Greßner W. Günther M. Motta AAML 69 34 0 05 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 24 0 0 04 Feb 2020
Defending Adversarial Attacks via Semantic Feature Manipulation Shuo Wang Tianle Chen Surya Nepal Carsten Rudolph M. Grobler Shangyu Chen AAML 51 7 0 03 Feb 2020
Regularizers for Single-step Adversarial Training S. VivekB. R. Venkatesh Babu AAML 56 7 0 03 Feb 2020
AdvJND: Generating Adversarial Examples with Just Noticeable Difference Zifei Zhang Kai Qiao Lingyun Jiang Linyuan Wang Bin Yan AAML 54 9 0 01 Feb 2020
Adversarial Attacks on Convolutional Neural Networks in Facial Recognition Domain Yigit Can Alparslan Ken Alparslan Jeremy Keim-Shenk S. Khade Rachel Greenstadt AAML 52 14 0 30 Jan 2020
An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions Samuele Tosatto R. Akrour Jan Peters 64 4 0 29 Jan 2020
Explaining with Counter Visual Attributes and Examples Sadaf Gulshad A. Smeulders XAI FAtt AAML 77 15 0 27 Jan 2020
Practical Fast Gradient Sign Attack against Mammographic Image Classifier Ibrahim Yilmaz AAML 65 10 0 27 Jan 2020
Ensemble Noise Simulation to Handle Uncertainty about Gradient-based Adversarial Attacks Rehana Mahfuz R. Sahay Aly El Gamal AAML 40 2 0 26 Jan 2020
On the human evaluation of audio adversarial examples Jon Vadillo Roberto Santana AAML 55 3 0 23 Jan 2020