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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
Internet of Predictable Things (IoPT) Framework to Increase Cyber-Physical System Resiliency Umit Cali Murat Kuzlu Vinayak Sharma M. Pipattanasomporn Ferhat Ozgur Catak 13 1 0 19 Jan 2021
PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack Jie Wang Z. Yin Jin Tang Jing Jiang Bin Luo AAML 64 2 0 19 Jan 2021
Attention-Guided Black-box Adversarial Attacks with Large-Scale Multiobjective Evolutionary Optimization Jie Wang Z. Yin Jing Jiang Yang Du AAML 101 8 0 19 Jan 2021
Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving James Tu Huichen Li Xinchen Yan Mengye Ren Yun Chen Ming Liang E. Bitar Ersin Yumer R. Urtasun AAML 88 78 0 17 Jan 2021
Context-Aware Image Denoising with Auto-Threshold Canny Edge Detection to Suppress Adversarial Perturbation Li-Yun Wang Yeganeh Jalalpour W. Feng 39 0 0 14 Jan 2021
Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android Apps Yujin Huang Han Hu Chunyang Chen AAML FedML 115 33 0 12 Jan 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 173 226 0 11 Jan 2021
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing Andreas Bär Jonas Löhdefink Nikhil Kapoor Serin Varghese Fabian Hüger Peter Schlicht Tim Fingscheidt AAML 192 35 0 11 Jan 2021
SyReNN: A Tool for Analyzing Deep Neural Networks Matthew Sotoudeh Aditya V. Thakur AAML GNN 63 16 0 09 Jan 2021
Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective Pulei Xiong Scott Buffett Shahrear Iqbal Philippe Lamontagne M. Mamun Heather Molyneaux OOD 81 15 0 08 Jan 2021
Adversarial Attack Attribution: Discovering Attributable Signals in Adversarial ML Attacks Marissa Dotter Sherry Xie Keith Manville Josh Harguess Colin Busho Mikel Rodriguez AAML 45 2 0 08 Jan 2021
Adversarial Machine Learning for 5G Communications Security Y. Sagduyu T. Erpek Yi Shi AAML 85 43 0 07 Jan 2021
Corner case data description and detection Tinghui Ouyang Vicent Sant Marco Yoshinao Isobe H. Asoh Y. Oiwa Yoshiki Seo AAML 57 13 0 07 Jan 2021
Understanding the Error in Evaluating Adversarial Robustness Pengfei Xia Ziqiang Li Hongjing Niu Bin Li AAML ELM 76 5 0 07 Jan 2021
Practical Blind Membership Inference Attack via Differential Comparisons Bo Hui Yuchen Yang Haolin Yuan Philippe Burlina Neil Zhenqiang Gong Yinzhi Cao MIACV 194 124 0 05 Jan 2021
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning Konstantinos P. Panousis S. Chatzis Antonios Alexos Sergios Theodoridis BDL AAML OOD 112 19 0 04 Jan 2021
Local Black-box Adversarial Attacks: A Query Efficient Approach Tao Xiang Hangcheng Liu Shangwei Guo Tianwei Zhang X. Liao AAML MLAU 46 15 0 04 Jan 2021
Active Learning Under Malicious Mislabeling and Poisoning Attacks Jing Lin R. Luley Kaiqi Xiong AAML 83 8 0 01 Jan 2021
Patch-wise++ Perturbation for Adversarial Targeted Attacks Lianli Gao Qilong Zhang Jingkuan Song Heng Tao Shen AAML 120 19 0 31 Dec 2020
Temporally-Transferable Perturbations: Efficient, One-Shot Adversarial Attacks for Online Visual Object Trackers Krishna Kanth Nakka Mathieu Salzmann AAML 31 5 0 30 Dec 2020
With False Friends Like These, Who Can Notice Mistakes? Lue Tao Lei Feng Jinfeng Yi Songcan Chen AAML 70 6 0 29 Dec 2020
Analysis of Dominant Classes in Universal Adversarial Perturbations Jon Vadillo Roberto Santana Jose A. Lozano AAML 64 5 0 28 Dec 2020
Adversarial Momentum-Contrastive Pre-Training Cong Xu Dan Li Min Yang SSL 74 15 0 24 Dec 2020
The Translucent Patch: A Physical and Universal Attack on Object Detectors Alon Zolfi Moshe Kravchik Yuval Elovici A. Shabtai AAML 67 89 0 23 Dec 2020
Discovering Robust Convolutional Architecture at Targeted Capacity: A Multi-Shot Approach Xuefei Ning Jiaqi Zhao Wenshuo Li Tianchen Zhao Yin Zheng Huazhong Yang Yu Wang AAML 95 5 0 22 Dec 2020
Defence against adversarial attacks using classical and quantum-enhanced Boltzmann machines Aidan Kehoe P. Wittek Yanbo Xue Alejandro Pozas-Kerstjens AAML 82 7 0 21 Dec 2020
Blurring Fools the Network -- Adversarial Attacks by Feature Peak Suppression and Gaussian Blurring Chenchen Zhao Hao Li AAML 27 3 0 21 Dec 2020
Exploiting Vulnerability of Pooling in Convolutional Neural Networks by Strict Layer-Output Manipulation for Adversarial Attacks Chenchen Zhao Hao Li AAML 41 0 0 21 Dec 2020
Color Channel Perturbation Attacks for Fooling Convolutional Neural Networks and A Defense Against Such Attacks Jayendra Kantipudi S. Dubey Soumendu Chakraborty AAML 91 22 0 20 Dec 2020
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 85 5 0 18 Dec 2020
Semantics and explanation: why counterfactual explanations produce adversarial examples in deep neural networks Kieran Browne Ben Swift AAML GAN 58 30 0 18 Dec 2020
A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks Qingsong Yao Zecheng He Yi Lin Kai Ma Yefeng Zheng S. Kevin Zhou AAML MedIm 109 16 0 17 Dec 2020
Adversarial trading Alexandre Miot AAML 56 1 0 16 Dec 2020
Exacerbating Algorithmic Bias through Fairness Attacks Ninareh Mehrabi Muhammad Naveed Fred Morstatter Aram Galstyan AAML 91 69 0 16 Dec 2020
FAWA: Fast Adversarial Watermark Attack on Optical Character Recognition (OCR) Systems Lu Chen Jiao Sun Wenyuan Xu AAML 35 16 0 15 Dec 2020
Robustness Threats of Differential Privacy Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 97 14 0 14 Dec 2020
Achieving Adversarial Robustness Requires An Active Teacher Chao Ma Lexing Ying 71 1 0 14 Dec 2020
Closeness and Uncertainty Aware Adversarial Examples Detection in Adversarial Machine Learning Ömer Faruk Tuna Ferhat Ozgur Catak M. T. Eskil AAML 83 11 0 11 Dec 2020
SPAA: Stealthy Projector-based Adversarial Attacks on Deep Image Classifiers Bingyao Huang Haibin Ling AAML 79 20 0 10 Dec 2020
Generating Out of Distribution Adversarial Attack using Latent Space Poisoning Ujjwal Upadhyay Prerana Mukherjee 78 7 0 09 Dec 2020
Risk Management Framework for Machine Learning Security J. Breier A. Baldwin H. Balinsky Yang Liu AAML 31 3 0 09 Dec 2020
Are DNNs fooled by extremely unrecognizable images? Soichiro Kumano Hiroshi Kera T. Yamasaki AAML 44 3 0 07 Dec 2020
Backpropagating Linearly Improves Transferability of Adversarial Examples Yiwen Guo Qizhang Li Hao Chen FedML AAML 82 116 0 07 Dec 2020
A Singular Value Perspective on Model Robustness Malhar Jere Maghav Kumar F. Koushanfar AAML 86 6 0 07 Dec 2020
Practical No-box Adversarial Attacks against DNNs Qizhang Li Yiwen Guo Hao Chen AAML 75 59 0 04 Dec 2020
Towards Natural Robustness Against Adversarial Examples Haoyu Chu Shikui Wei Yao-Min Zhao AAML 26 1 0 04 Dec 2020
Visually Imperceptible Adversarial Patch Attacks on Digital Images Yaguan Qian Jiamin Wang Bin Wang Xiang Ling Zhaoquan Gu Chunming Wu Wassim Swaileh AAML 66 2 0 02 Dec 2020
Overcoming Measurement Inconsistency in Deep Learning for Linear Inverse Problems: Applications in Medical Imaging Marija Vella João F. C. Mota 110 4 0 29 Nov 2020
A Targeted Universal Attack on Graph Convolutional Network Jiazhu Dai Weifeng Zhu Xiangfeng Luo AAML GNN 44 20 0 29 Nov 2020
FaceGuard: A Self-Supervised Defense Against Adversarial Face Images Debayan Deb Xiaoming Liu Anil K. Jain CVBM AAML PICV 98 27 0 28 Nov 2020