Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

1 February 2018

Papers citing "Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples"

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Title
Learning Black-Box Attackers with Transferable Priors and Query Feedback Jiancheng Yang Yangzhou Jiang Xiaoyang Huang Bingbing Ni Chenglong Zhao AAML 18 81 0 21 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
A Generative Model based Adversarial Security of Deep Learning and Linear Classifier Models Ferhat Ozgur Catak Samed Sivaslioglu Kevser Sahinbas AAML 21 7 0 17 Oct 2020
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 16 22 0 15 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 323 0 07 Oct 2020
Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder Alvin Chan Yi Tay Yew-Soon Ong Aston Zhang SILM 13 57 0 06 Oct 2020
Understanding Catastrophic Overfitting in Single-step Adversarial Training Hoki Kim Woojin Lee Jaewook Lee AAML 11 107 0 05 Oct 2020
An Empirical Study of DNNs Robustification Inefficacy in Protecting Visual Recommenders V. W. Anelli T. D. Noia Daniele Malitesta Felice Antonio Merra AAML 19 2 0 02 Oct 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients Yifei Huang Yaodong Yu Hongyang R. Zhang Yi-An Ma Yuan Yao AAML 29 26 0 28 Sep 2020
Optimal Provable Robustness of Quantum Classification via Quantum Hypothesis Testing Maurice Weber Nana Liu Bo-wen Li Ce Zhang Zhikuan Zhao AAML 29 28 0 21 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 19 11 0 21 Sep 2020
Certifying Confidence via Randomized Smoothing Aounon Kumar Alexander Levine S. Feizi Tom Goldstein UQCV 28 38 0 17 Sep 2020
Malicious Network Traffic Detection via Deep Learning: An Information Theoretic View Erick Galinkin AAML 15 0 0 16 Sep 2020
Input Hessian Regularization of Neural Networks Waleed Mustafa Robert A. Vandermeulen Marius Kloft AAML 14 12 0 14 Sep 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa S. Feizi AAML 81 60 0 05 Sep 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl W. R. Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 19 215 0 04 Sep 2020
ASTRAL: Adversarial Trained LSTM-CNN for Named Entity Recognition Jiuniu Wang Wenjia Xu Xingyu Fu Guangluan Xu Yirong Wu 20 57 0 02 Sep 2020
Simulating Unknown Target Models for Query-Efficient Black-box Attacks Chen Ma L. Chen Junhai Yong MLAU OOD 41 17 0 02 Sep 2020
Adversarially Robust Neural Architectures Minjing Dong Yanxi Li Yunhe Wang Chang Xu AAML OOD 34 48 0 02 Sep 2020
Yet Another Intermediate-Level Attack Qizhang Li Yiwen Guo Hao Chen AAML 24 51 0 20 Aug 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 19 19 0 19 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
Anti-Bandit Neural Architecture Search for Model Defense Hanlin Chen Baochang Zhang Shenjun Xue Xuan Gong Hong Liu Rongrong Ji David Doermann AAML 14 33 0 03 Aug 2020
Stylized Adversarial Defense Muzammal Naseer Salman Khan Munawar Hayat F. Khan Fatih Porikli GAN AAML 20 16 0 29 Jul 2020
RANDOM MASK: Towards Robust Convolutional Neural Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Liwei Wang AAML OOD 16 17 0 27 Jul 2020
SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems H. Abdullah Kevin Warren Vincent Bindschaedler Nicolas Papernot Patrick Traynor AAML 24 128 0 13 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip H. S. Torr NoLa AAML 23 57 0 08 Jul 2020
Improving Calibration through the Relationship with Adversarial Robustness Yao Qin Xuezhi Wang Alex Beutel Ed H. Chi AAML 27 25 0 29 Jun 2020
Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy Sijia Liu Gaoyuan Zhang Cynthia Liu Pin-Yu Chen Shiyu Chang Luca Daniel AAML FAtt 19 66 0 26 Jun 2020
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability Kaizhao Liang Jacky Y. Zhang Boxin Wang Zhuolin Yang Oluwasanmi Koyejo B. Li AAML 28 25 0 25 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 19 81 0 15 Jun 2020
Adversarial Self-Supervised Contrastive Learning Minseon Kim Jihoon Tack Sung Ju Hwang SSL 20 246 0 13 Jun 2020
Large-Scale Adversarial Training for Vision-and-Language Representation Learning Zhe Gan Yen-Chun Chen Linjie Li Chen Zhu Yu Cheng Jingjing Liu ObjD VLM 29 488 0 11 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 27 146 0 20 May 2020
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks Linhai Ma Liang Liang AAML 23 18 0 19 May 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 22 29 0 17 May 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 16 32 0 16 May 2020
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition Tianhang Zheng Sheng Liu Changyou Chen Junsong Yuan Baochun Li K. Ren AAML 19 17 0 14 May 2020
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses Yaxin Li Wei Jin Han Xu Jiliang Tang AAML 19 129 0 13 May 2020
Enhancing Intrinsic Adversarial Robustness via Feature Pyramid Decoder Guanlin Li Shuya Ding Jun-Jie Luo Chang-rui Liu AAML 42 19 0 06 May 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 11 91 0 05 May 2020
Robust Encodings: A Framework for Combating Adversarial Typos Erik Jones Robin Jia Aditi Raghunathan Percy Liang AAML 130 102 0 04 May 2020
Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability H. Aghakhani Dongyu Meng Yu-Xiang Wang Christopher Kruegel Giovanni Vigna AAML 20 105 0 01 May 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi Natalie Frank M. Mohri AAML 26 56 0 28 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 26 8 0 23 Apr 2020
Scalable Attack on Graph Data by Injecting Vicious Nodes Jihong Wang Minnan Luo Fnu Suya Jundong Li Z. Yang Q. Zheng AAML GNN 19 85 0 22 Apr 2020
Single-step Adversarial training with Dropout Scheduling S. VivekB. R. Venkatesh Babu OOD AAML 16 71 0 18 Apr 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning Michael Everett Bjorn Lutjens Jonathan P. How AAML 13 41 0 11 Apr 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning Tianlong Chen Sijia Liu Shiyu Chang Yu Cheng Lisa Amini Zhangyang Wang AAML 18 246 0 28 Mar 2020
DaST: Data-free Substitute Training for Adversarial Attacks Mingyi Zhou Jing Wu Yipeng Liu Shuaicheng Liu Ce Zhu 11 142 0 28 Mar 2020