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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

Title
One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy Jingkang Wang R. Jia Gerald Friedland Yangqiu Song C. Spanos AAML 40 4 0 23 Oct 2018
Adversarial Risk Bounds via Function Transformation Justin Khim Po-Ling Loh AAML 90 50 0 22 Oct 2018
Cost-Sensitive Robustness against Adversarial Examples Xiao Zhang David Evans AAML 76 26 0 22 Oct 2018
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm Tsui-Wei Weng Huan Zhang Pin-Yu Chen A. Lozano Cho-Jui Hsieh Luca Daniel 51 10 0 19 Oct 2018
Provable Robustness of ReLU networks via Maximization of Linear Regions Francesco Croce Maksym Andriushchenko Matthias Hein 92 166 0 17 Oct 2018
Projecting Trouble: Light Based Adversarial Attacks on Deep Learning Classifiers Nicole Nichols Robert J. Jasper AAML 51 15 0 16 Oct 2018
Security Matters: A Survey on Adversarial Machine Learning Guofu Li Pengjia Zhu Jin Li Zhemin Yang Ning Cao Zhiyi Chen AAML 90 25 0 16 Oct 2018
Deep Reinforcement Learning Yuxi Li VLM OffRL 194 144 0 15 Oct 2018
Is PGD-Adversarial Training Necessary? Alternative Training via a Soft-Quantization Network with Noisy-Natural Samples Only T. Zheng Changyou Chen K. Ren AAML 57 6 0 10 Oct 2018
The Outer Product Structure of Neural Network Derivatives Craig Bakker Michael J. Henry Nathan Oken Hodas 18 3 0 09 Oct 2018
Feature Prioritization and Regularization Improve Standard Accuracy and Adversarial Robustness Chihuang Liu Joseph Jaja AAML 67 12 0 04 Oct 2018
Can Adversarially Robust Learning Leverage Computational Hardness? Saeed Mahloujifar Mohammad Mahmoody AAML OOD 74 48 0 02 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 102 49 0 02 Oct 2018
Improved robustness to adversarial examples using Lipschitz regularization of the loss Chris Finlay Adam M. Oberman B. Abbasi 80 34 0 01 Oct 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network Xuanqing Liu Yao Li Chongruo Wu Cho-Jui Hsieh AAML OOD 93 171 0 01 Oct 2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks Kenneth T. Co Luis Muñoz-González Sixte de Maupeou Emil C. Lupu AAML 74 67 0 30 Sep 2018
CAAD 2018: Generating Transferable Adversarial Examples Yash Sharma Tien-Dung Le M. Alzantot AAML SILM 85 7 0 29 Sep 2018
Characterizing Audio Adversarial Examples Using Temporal Dependency Zhuolin Yang Yue Liu Pin-Yu Chen Basel Alomair AAML 69 165 0 28 Sep 2018
Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards Mhafuzul Islam M. Chowdhury Hongda Li Hongxin Hu AAML 34 12 0 27 Sep 2018
Low Frequency Adversarial Perturbation Chuan Guo Jared S. Frank Kilian Q. Weinberger AAML 84 168 0 24 Sep 2018
Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization Bao Wang A. Lin Weizhi Zhu Penghang Yin Andrea L. Bertozzi Stanley J. Osher AAML 41 20 0 23 Sep 2018
Unrestricted Adversarial Examples Tom B. Brown Nicholas Carlini Chiyuan Zhang Catherine Olsson Paul Christiano Ian Goodfellow AAML 81 103 0 22 Sep 2018
Playing the Game of Universal Adversarial Perturbations Julien Perolat Mateusz Malinowski Bilal Piot Olivier Pietquin AAML 69 25 0 20 Sep 2018
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples Deqiang Li Ramesh Baral Tao Li Han Wang Qianmu Li Shouhuai Xu AAML 63 21 0 18 Sep 2018
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks Siyue Wang Tianlin Li Pu Zhao Wujie Wen David Kaeli S. Chin Xinyu Lin AAML 76 70 0 13 Sep 2018
Query-Efficient Black-Box Attack by Active Learning Pengcheng Li Jinfeng Yi Lijun Zhang AAML MLAU 73 55 0 13 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 82 62 0 11 Sep 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 117 350 0 10 Sep 2018
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability Kai Y. Xiao Vincent Tjeng Nur Muhammad (Mahi) Shafiullah Aleksander Madry AAML OOD 74 202 0 09 Sep 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks Ambra Demontis Marco Melis Maura Pintor Matthew Jagielski Battista Biggio Alina Oprea Cristina Nita-Rotaru Fabio Roli SILM AAML 66 11 0 08 Sep 2018
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples Dan Peng Zizhan Zheng Xiaofeng Zhang AAML 57 5 0 08 Sep 2018
Are adversarial examples inevitable? Ali Shafahi Wenjie Huang Christoph Studer Soheil Feizi Tom Goldstein SILM 88 283 0 06 Sep 2018
Bridging machine learning and cryptography in defence against adversarial attacks O. Taran Shideh Rezaeifar Svyatoslav Voloshynovskiy AAML 57 22 0 05 Sep 2018
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks Siwakorn Srisakaokul Yuhao Zhang Zexuan Zhong Wei Yang Tao Xie Bo Li AAML 87 19 0 31 Aug 2018
Reinforcement Learning for Autonomous Defence in Software-Defined Networking Yi Han Benjamin I. P. Rubinstein Tamas Abraham T. Alpcan O. Vel S. Erfani David Hubczenko C. Leckie Paul Montague AAML 55 69 0 17 Aug 2018
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 101 123 0 16 Aug 2018
Adversarial Vision Challenge Wieland Brendel Jonas Rauber Alexey Kurakin Nicolas Papernot Behar Veliqi M. Salathé Sharada Mohanty Matthias Bethge AAML 79 58 0 06 Aug 2018
Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu Sijia Liu Pu Zhao Pin-Yu Chen Huan Zhang Quanfu Fan Deniz Erdogmus Yanzhi Wang Xinyu Lin AAML 126 162 0 05 Aug 2018
Security and Privacy Issues in Deep Learning Ho Bae Jaehee Jang Dahuin Jung Hyemi Jang Heonseok Ha Hyungyu Lee Sungroh Yoon SILM MIACV 145 79 0 31 Jul 2018
Rob-GAN: Generator, Discriminator, and Adversarial Attacker Xuanqing Liu Cho-Jui Hsieh GAN 66 6 0 27 Jul 2018
Evaluating and Understanding the Robustness of Adversarial Logit Pairing Logan Engstrom Andrew Ilyas Anish Athalye AAML 75 141 0 26 Jul 2018
Limitations of the Lipschitz constant as a defense against adversarial examples Todd P. Huster C. Chiang R. Chadha AAML 60 84 0 25 Jul 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 107 229 0 18 Jul 2018
Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions Adnan Siraj Rakin Jinfeng Yi Boqing Gong Deliang Fan AAML MQ 80 50 0 18 Jul 2018
Adaptive Adversarial Attack on Scene Text Recognition Xiaoyong Yuan Pan He Xiaolin Li Dapeng Oliver Wu AAML 73 23 0 09 Jul 2018
Implicit Generative Modeling of Random Noise during Training for Adversarial Robustness Priyadarshini Panda Kaushik Roy AAML 50 4 0 05 Jul 2018
Local Gradients Smoothing: Defense against localized adversarial attacks Muzammal Naseer Salman H. Khan Fatih Porikli AAML 104 162 0 03 Jul 2018
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 91 462 0 03 Jul 2018
Detection based Defense against Adversarial Examples from the Steganalysis Point of View Jiayang Liu Weiming Zhang Yiwei Zhang Dongdong Hou Yujia Liu Hongyue Zha Nenghai Yu AAML 101 100 0 21 Jun 2018
Gradient Adversarial Training of Neural Networks Ayan Sinha Zhao Chen Vijay Badrinarayanan Andrew Rabinovich AAML 63 33 0 21 Jun 2018