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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
Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs Rana Abou-Khamis Ashraf Matrawy AAML 83 47 0 08 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 89 58 0 08 Jul 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML 89 12 0 05 Jul 2020
On Connections between Regularizations for Improving DNN Robustness Yiwen Guo Long Chen Yurong Chen Changshui Zhang AAML 51 14 0 04 Jul 2020
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring Zhihui Shao Jianyi Yang Shaolei Ren HILM 76 10 0 03 Jul 2020
Outlier Detection through Null Space Analysis of Neural Networks Matthew Cook A. Zare P. Gader 65 19 0 02 Jul 2020
Generating Adversarial Examples with Controllable Non-transferability Renzhi Wang Tianwei Zhang Xiaofei Xie Lei Ma Cong Tian Felix Juefei Xu Yang Liu SILM AAML 80 3 0 02 Jul 2020
Deep Learning Defenses Against Adversarial Examples for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Ines Goicoechea-Telleria Raul Orduna Urrutia AAML 72 5 0 02 Jul 2020
Robust and Accurate Authorship Attribution via Program Normalization Yizhen Wang Mohannad J. Alhanahnah Ke Wang Mihai Christodorescu S. Jha AAML 38 1 0 01 Jul 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey S. Silva Peyman Najafirad AAML OOD 106 135 0 01 Jul 2020
Adversarial Example Games A. Bose Gauthier Gidel Hugo Berrard Andre Cianflone Pascal Vincent Simon Lacoste-Julien William L. Hamilton AAML GAN 105 52 0 01 Jul 2020
ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks Miguel Villarreal-Vasquez B. Bhargava AAML 98 39 0 01 Jul 2020
Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks Kishor Datta Gupta Zahid Akhtar D. Dasgupta AAML 52 10 0 01 Jul 2020
Unifying Model Explainability and Robustness via Machine-Checkable Concepts Vedant Nanda Till Speicher John P. Dickerson Krishna P. Gummadi Muhammad Bilal Zafar AAML 38 4 0 01 Jul 2020
Generating Adversarial Examples with an Optimized Quality Aminollah Khormali Daehun Nyang David A. Mohaisen AAML 45 1 0 30 Jun 2020
Geometry-Inspired Top-k Adversarial Perturbations Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 83 10 0 28 Jun 2020
FDA3 : Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications Yunfei Song Tian Liu Tongquan Wei Xiangfeng Wang Zhe Tao Mingsong Chen 108 50 0 28 Jun 2020
Can We Mitigate Backdoor Attack Using Adversarial Detection Methods? Kaidi Jin Tianwei Zhang Chao Shen Yufei Chen Ming Fan Chenhao Lin Ting Liu AAML 43 14 0 26 Jun 2020
Orthogonal Deep Models As Defense Against Black-Box Attacks M. Jalwana Naveed Akhtar Bennamoun Ajmal Mian AAML 45 11 0 26 Jun 2020
Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks Francesco Croce Maksym Andriushchenko Naman D. Singh Nicolas Flammarion Matthias Hein 105 101 0 23 Jun 2020
RayS: A Ray Searching Method for Hard-label Adversarial Attack Jinghui Chen Quanquan Gu AAML 85 139 0 23 Jun 2020
Lipschitz Recurrent Neural Networks N. Benjamin Erichson Omri Azencot A. Queiruga Liam Hodgkinson Michael W. Mahoney 90 112 0 22 Jun 2020
Students Need More Attention: BERT-based AttentionModel for Small Data with Application to AutomaticPatient Message Triage Shijing Si Rui Wang Jedrek Wosik Hao Zhang D. Dov Guoyin Wang Ricardo Henao Lawrence Carin 65 26 0 22 Jun 2020
Network Moments: Extensions and Sparse-Smooth Attacks Modar Alfadly Adel Bibi Emilio Botero Salman Alsubaihi Guohao Li AAML 51 2 0 21 Jun 2020
Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble Yi Zhou Xiaoqing Zheng Cho-Jui Hsieh Kai-Wei Chang Xuanjing Huang SILM 105 48 0 20 Jun 2020
Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers I. Fursov A. Zaytsev Nikita Klyuchnikov A. Kravchenko Evgeny Burnaev AAML SILM 45 5 0 19 Jun 2020
Adversarial Attacks for Multi-view Deep Models Xuli Sun Shiliang Sun AAML 29 0 0 19 Jun 2020
REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions Lokender Tiwari Anish Madan Saket Anand Subhashis Banerjee AAML 37 1 0 18 Jun 2020
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders Bartosz Wójcik P. Morawiecki Marek Śmieja Tomasz Krzy.zek Przemysław Spurek Jacek Tabor GAN 67 13 0 17 Jun 2020
Adversarial Defense by Latent Style Transformations Shuo Wang Surya Nepal A. Abuadbba Carsten Rudolph M. Grobler AAML 34 11 0 17 Jun 2020
Total Deep Variation: A Stable Regularizer for Inverse Problems Erich Kobler Alexander Effland K. Kunisch Thomas Pock MedIm 82 19 0 15 Jun 2020
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data Zhun Deng Linjun Zhang Amirata Ghorbani James Zou 99 32 0 15 Jun 2020
Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems Yuanjiang Cao Xiaocong Chen Lina Yao Xianzhi Wang W. Zhang AAML 66 44 0 14 Jun 2020
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks Mojtaba Faramarzi Mohammad Amini Akilesh Badrinaaraayanan Vikas Verma A. Chandar AAML 74 32 0 14 Jun 2020
Defensive Approximation: Securing CNNs using Approximate Computing Amira Guesmi Ihsen Alouani Khaled N. Khasawneh M. Baklouti T. Frikha Mohamed Abid Nael B. Abu-Ghazaleh AAML 88 38 0 13 Jun 2020
Adversarial Self-Supervised Contrastive Learning Minseon Kim Jihoon Tack Sung Ju Hwang SSL 90 251 0 13 Jun 2020
Targeted Adversarial Perturbations for Monocular Depth Prediction A. Wong Safa Cicek Stefano Soatto AAML MDE 62 45 0 12 Jun 2020
Towards Robust Pattern Recognition: A Review Xu-Yao Zhang Cheng-Lin Liu C. Suen OOD HAI 69 110 0 12 Jun 2020
Backdoors in Neural Models of Source Code Goutham Ramakrishnan Aws Albarghouthi AAML SILM 141 58 0 11 Jun 2020
Achieving robustness in classification using optimal transport with hinge regularization M. Serrurier Franck Mamalet Alberto González Sanz Thibaut Boissin Jean-Michel Loubes E. del Barrio AAML 58 40 0 11 Jun 2020
Protecting Against Image Translation Deepfakes by Leaking Universal Perturbations from Black-Box Neural Networks Nataniel Ruiz Sarah Adel Bargal Stan Sclaroff AAML 63 11 0 11 Jun 2020
Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors Gerda Bortsova C. González-Gonzalo S. Wetstein Florian Dubost Ioannis Katramados ... Bram van Ginneken J. Pluim M. Veta Clara I. Sánchez Marleen de Bruijne AAML MedIm 47 131 0 11 Jun 2020
Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption Xu Sun Zhiyuan Zhang Xuancheng Ren Ruixuan Luo Liangyou Li 68 39 0 10 Jun 2020
Provable tradeoffs in adversarially robust classification Yan Sun Hamed Hassani David Hong Alexander Robey 107 56 0 09 Jun 2020
Towards an Intrinsic Definition of Robustness for a Classifier Théo Giraudon Vincent Gripon Matthias Löwe Franck Vermet OOD AAML 25 2 0 09 Jun 2020
Picket: Guarding Against Corrupted Data in Tabular Data during Learning and Inference Zifan Liu Zhechun Zhou Theodoros Rekatsinas 50 16 0 08 Jun 2020
Adversarial Feature Desensitization P. Bashivan Reza Bayat Adam Ibrahim Kartik Ahuja Mojtaba Faramarzi Touraj Laleh Blake A. Richards Irina Rish AAML 50 21 0 08 Jun 2020
Tricking Adversarial Attacks To Fail Blerta Lindqvist AAML 48 0 0 08 Jun 2020
Consistency Regularization for Certified Robustness of Smoothed Classifiers Jongheon Jeong Jinwoo Shin AAML 86 88 0 07 Jun 2020
mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks Hai Shu Ronghua Shi Qiran Jia Hongtu Zhu Ziqi Chen AAML 42 2 0 05 Jun 2020