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
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems Guangke Chen Sen Chen Lingling Fan Xiaoning Du Zhe Zhao Fu Song Yang Liu AAML 12 193 0 03 Nov 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 25 9 0 31 Oct 2019
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning Xuanqing Liu Si Si Xiaojin Zhu Yang Li Cho-Jui Hsieh AAML 27 76 0 30 Oct 2019
Understanding and Quantifying Adversarial Examples Existence in Linear Classification Xupeng Shi A. Ding AAML 14 3 0 27 Oct 2019
Detection of Adversarial Attacks and Characterization of Adversarial Subspace Mohammad Esmaeilpour P. Cardinal Alessandro Lameiras Koerich AAML 11 17 0 26 Oct 2019
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training? Ali Shafahi Amin Ghiasi Furong Huang Tom Goldstein AAML 19 39 0 25 Oct 2019
Adversarial Example Detection by Classification for Deep Speech Recognition Saeid Samizade Z. Tan Chao Shen X. Guan AAML 14 35 0 22 Oct 2019
An Alternative Surrogate Loss for PGD-based Adversarial Testing Sven Gowal J. Uesato Chongli Qin Po-Sen Huang Timothy A. Mann Pushmeet Kohli AAML 39 88 0 21 Oct 2019
Deep Neural Rejection against Adversarial Examples Angelo Sotgiu Ambra Demontis Marco Melis Battista Biggio Giorgio Fumera Xiaoyi Feng Fabio Roli AAML 12 68 0 01 Oct 2019
Role of Spatial Context in Adversarial Robustness for Object Detection Aniruddha Saha Akshayvarun Subramanya Koninika Patil Hamed Pirsiavash ObjD AAML 23 53 0 30 Sep 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 24 91 0 29 Sep 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 22 18 0 27 Sep 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 20 103 0 25 Sep 2019
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack Minhao Cheng Simranjit Singh Patrick H. Chen Pin-Yu Chen Sijia Liu Cho-Jui Hsieh AAML 122 219 0 24 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 14 125 0 20 Sep 2019
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 28 199 0 11 Sep 2019
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses Xiao Wang Siyue Wang Pin-Yu Chen Yanzhi Wang Brian Kulis Xue Lin S. Chin AAML 6 42 0 20 Aug 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 34 176 0 17 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 21 230 0 24 Jul 2019
Towards Adversarially Robust Object Detection Haichao Zhang Jianyu Wang AAML ObjD 23 130 0 24 Jul 2019
Structure-Invariant Testing for Machine Translation Pinjia He Clara Meister Z. Su 21 104 0 19 Jul 2019
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions Yao Qin Nicholas Frosst S. Sabour Colin Raffel G. Cottrell Geoffrey E. Hinton GAN AAML 17 71 0 05 Jul 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 29 474 0 03 Jul 2019
Accurate, reliable and fast robustness evaluation Wieland Brendel Jonas Rauber Matthias Kümmerer Ivan Ustyuzhaninov Matthias Bethge AAML OOD 11 111 0 01 Jul 2019
Evolving Robust Neural Architectures to Defend from Adversarial Attacks Shashank Kotyan Danilo Vasconcellos Vargas OOD AAML 24 36 0 27 Jun 2019
Defending Adversarial Attacks by Correcting logits Yifeng Li Lingxi Xie Ya-Qin Zhang Rui Zhang Yanfeng Wang Qi Tian AAML 29 5 0 26 Jun 2019
A Computationally Efficient Method for Defending Adversarial Deep Learning Attacks R. Sahay Rehana Mahfuz Aly El Gamal AAML 11 5 0 13 Jun 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 25 535 0 09 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad B. Li AAML 25 35 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 20 61 0 08 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 26 42 0 07 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 15 15 0 05 Jun 2019
Multi-way Encoding for Robustness Donghyun Kim Sarah Adel Bargal Jianming Zhang Stan Sclaroff AAML 15 2 0 05 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 28 3 0 01 Jun 2019
Bypassing Backdoor Detection Algorithms in Deep Learning T. Tan Reza Shokri FedML AAML 22 149 0 31 May 2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness Adnan Siraj Rakin Zhezhi He Li Yang Yanzhi Wang Liqiang Wang Deliang Fan AAML 32 21 0 30 May 2019
Certifiably Robust Interpretation in Deep Learning Alexander Levine Sahil Singla S. Feizi FAtt AAML 20 63 0 28 May 2019
Adversarially Robust Learning Could Leverage Computational Hardness Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody AAML 14 24 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 10 77 0 27 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 11 97 0 25 May 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 25 157 0 23 May 2019
What Do Adversarially Robust Models Look At? Takahiro Itazuri Yoshihiro Fukuhara Hirokatsu Kataoka Shigeo Morishima 16 5 0 19 May 2019
Robustification of deep net classifiers by key based diversified aggregation with pre-filtering O. Taran Shideh Rezaeifar T. Holotyak S. Voloshynovskiy AAML 22 1 0 14 May 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 17 374 0 30 Apr 2019
Adversarial Defense Through Network Profiling Based Path Extraction Yuxian Qiu Jingwen Leng Cong Guo Quan Chen C. Li M. Guo Yuhao Zhu AAML 16 50 0 17 Apr 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 8 35 0 12 Apr 2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks Yinpeng Dong Tianyu Pang Hang Su Jun Zhu SILM AAML 19 827 0 05 Apr 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan X. Lin AAML FAtt 12 43 0 03 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 9 151 0 01 Apr 2019
Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 14 219 0 28 Mar 2019