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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"

50 / 1,929 papers shown

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Dropping Pixels for Adversarial Robustness Hossein Hosseini Sreeram Kannan Radha Poovendran 44 16 0 01 May 2019
Detecting Adversarial Examples through Nonlinear Dimensionality Reduction Francesco Crecchi D. Bacciu Battista Biggio AAML 83 10 0 30 Apr 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 113 380 0 30 Apr 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 139 1,255 0 29 Apr 2019
Gotta Catch Ém All: Using Honeypots to Catch Adversarial Attacks on Neural Networks Shawn Shan Emily Wenger Bolun Wang Yangqiu Song Haitao Zheng Ben Y. Zhao 89 75 0 18 Apr 2019
ZK-GanDef: A GAN based Zero Knowledge Adversarial Training Defense for Neural Networks Guanxiong Liu Issa M. Khalil Abdallah Khreishah AAML 50 18 0 17 Apr 2019
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers Ameya Joshi Amitangshu Mukherjee Soumik Sarkar Chinmay Hegde AAML 92 100 0 17 Apr 2019
Defensive Quantization: When Efficiency Meets Robustness Ji Lin Chuang Gan Song Han MQ 112 204 0 17 Apr 2019
Adversarial Defense Through Network Profiling Based Path Extraction Yuxian Qiu Jingwen Leng Cong Guo Quan Chen Chong Li Minyi Guo Yuhao Zhu AAML 69 51 0 17 Apr 2019
Reducing Adversarial Example Transferability Using Gradient Regularization George Adam P. Smirnov B. Haibe-Kains Anna Goldenberg AAML 81 4 0 16 Apr 2019
AT-GAN: An Adversarial Generator Model for Non-constrained Adversarial Examples Xiaosen Wang Kun He Chuanbiao Song Liwei Wang John E. Hopcroft GAN 78 34 0 16 Apr 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 74 35 0 12 Apr 2019
Black-box Adversarial Attacks on Video Recognition Models Linxi Jiang Xingjun Ma Shaoxiang Chen James Bailey Yu-Gang Jiang AAML MLAU 76 147 0 10 Apr 2019
Universal Lipschitz Approximation in Bounded Depth Neural Networks Jérémy E. Cohen Todd P. Huster Ravid Cohen AAML 65 23 0 09 Apr 2019
JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks N. Benjamin Erichson Z. Yao Michael W. Mahoney AAML 69 24 0 07 Apr 2019
On Training Robust PDF Malware Classifiers Yizheng Chen Shiqi Wang Dongdong She Suman Jana AAML 99 69 0 06 Apr 2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks Yinpeng Dong Tianyu Pang Hang Su Jun Zhu SILM AAML 96 858 0 05 Apr 2019
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack Jianbo Chen Michael I. Jordan Martin J. Wainwright AAML 119 671 0 03 Apr 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan Xinyu Lin AAML FAtt 140 43 0 03 Apr 2019
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A. Salem Apratim Bhattacharyya Michael Backes Mario Fritz Yang Zhang FedML AAML MIACV 96 257 0 01 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 64 152 0 01 Apr 2019
Defending against adversarial attacks by randomized diversification O. Taran Shideh Rezaeifar T. Holotyak Svyatoslav Voloshynovskiy AAML 82 39 0 01 Apr 2019
Adversarial Robustness vs Model Compression, or Both? Shaokai Ye Kaidi Xu Sijia Liu Jan-Henrik Lambrechts Huan Zhang Aojun Zhou Kaisheng Ma Yanzhi Wang Xue Lin AAML 98 165 0 29 Mar 2019
Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 106 225 0 28 Mar 2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks Francesco Croce Jonas Rauber Matthias Hein AAML 65 31 0 27 Mar 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 79 76 0 25 Mar 2019
The Random Conditional Distribution for Higher-Order Probabilistic Inference Zenna Tavares Xin Zhang Edgar Minaysan Javier Burroni Rajesh Ranganath Armando Solar-Lezama 52 9 0 25 Mar 2019
The LogBarrier adversarial attack: making effective use of decision boundary information Chris Finlay Aram-Alexandre Pooladian Adam M. Oberman AAML 79 25 0 25 Mar 2019
Robust Neural Networks using Randomized Adversarial Training Alexandre Araujo Laurent Meunier Rafael Pinot Benjamin Négrevergne AAML OOD 48 36 0 25 Mar 2019
A Formalization of Robustness for Deep Neural Networks T. Dreossi Shromona Ghosh Alberto L. Sangiovanni-Vincentelli Sanjit A. Seshia GAN 71 30 0 24 Mar 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 48 3 0 24 Mar 2019
On the Robustness of Deep K-Nearest Neighbors Chawin Sitawarin David Wagner AAML OOD 140 58 0 20 Mar 2019
On Certifying Non-uniform Bound against Adversarial Attacks Chen Liu Ryota Tomioka Volkan Cevher AAML 79 19 0 15 Mar 2019
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets Penghang Yin J. Lyu Shuai Zhang Stanley Osher Y. Qi Jack Xin MQ LLMSV 154 320 0 13 Mar 2019
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation Cong Xie Oluwasanmi Koyejo Indranil Gupta FedML AAML 75 261 0 10 Mar 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 100 2 0 10 Mar 2019
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier Guanxiong Liu Issa M. Khalil Abdallah Khreishah GAN AAML 65 19 0 06 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 89 41 0 03 Mar 2019
TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents Panagiota Kiourti Kacper Wardega Susmit Jha Wenchao Li AAML 66 53 0 01 Mar 2019
On the Effectiveness of Low Frequency Perturbations Yash Sharma G. Ding Marcus A. Brubaker AAML 92 126 0 28 Feb 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN Ke Sun Zhanxing Zhu Zhouchen Lin AAML 62 20 0 28 Feb 2019
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors Ke Sun Zhanxing Zhu Zhouchen Lin AAML 76 18 0 28 Feb 2019
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 112 125 0 28 Feb 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 142 117 0 27 Feb 2019
Disentangled Deep Autoencoding Regularization for Robust Image Classification Zhenyu Duan Martin Renqiang Min Erran L. Li Mingbo Cai Yi Tian Xu Bingbing Ni 24 2 0 27 Feb 2019
Verification of Non-Linear Specifications for Neural Networks Chongli Qin Krishnamurthy Dvijotham Dvijotham Brendan O'Donoghue Rudy Bunel Robert Stanforth Sven Gowal J. Uesato G. Swirszcz Pushmeet Kohli AAML 68 44 0 25 Feb 2019
Adversarial attacks hidden in plain sight Jan Philip Göpfert André Artelt H. Wersing Barbara Hammer AAML 46 17 0 25 Feb 2019
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence Yi Han David Hubczenko Paul Montague O. Vel Tamas Abraham Benjamin I. P. Rubinstein C. Leckie T. Alpcan S. Erfani AAML 54 6 0 25 Feb 2019
On the Sensitivity of Adversarial Robustness to Input Data Distributions G. Ding Kry Yik-Chau Lui Xiaomeng Jin Luyu Wang Ruitong Huang OOD 64 60 0 22 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 95 211 0 21 Feb 2019