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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
Understanding the Error in Evaluating Adversarial Robustness Pengfei Xia Ziqiang Li Hongjing Niu Bin Li AAML ELM 76 5 0 07 Jan 2021
Adversarial Robustness by Design through Analog Computing and Synthetic Gradients Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krzakala AAML 131 13 0 06 Jan 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Mohamed Bennai Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 139 101 0 04 Jan 2021
Improving Adversarial Robustness in Weight-quantized Neural Networks Chang Song Elias Fallon Hai Helen Li AAML 61 19 0 29 Dec 2020
A Simple Fine-tuning Is All You Need: Towards Robust Deep Learning Via Adversarial Fine-tuning Ahmadreza Jeddi M. Shafiee A. Wong AAML 84 40 0 25 Dec 2020
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 206 11 0 22 Dec 2020
Discovering Robust Convolutional Architecture at Targeted Capacity: A Multi-Shot Approach Xuefei Ning Jiaqi Zhao Wenshuo Li Tianchen Zhao Yin Zheng Huazhong Yang Yu Wang AAML 95 5 0 22 Dec 2020
Self-Progressing Robust Training Minhao Cheng Pin-Yu Chen Sijia Liu Shiyu Chang Cho-Jui Hsieh Payel Das AAML VLM 74 9 0 22 Dec 2020
On Success and Simplicity: A Second Look at Transferable Targeted Attacks Zhengyu Zhao Zhuoran Liu Martha Larson AAML 167 126 0 21 Dec 2020
RAILS: A Robust Adversarial Immune-inspired Learning System Ren Wang Tianqi Chen Stephen Lindsly A. Rehemtulla Alfred Hero I. Rajapakse AAML 43 7 0 18 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers Jonathan W. Helland Nathan M. VanHoudnos AAML 54 4 0 18 Dec 2020
A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks Qingsong Yao Zecheng He Yi Lin Kai Ma Yefeng Zheng S. Kevin Zhou AAML MedIm 109 16 0 17 Dec 2020
Characterizing the Evasion Attackability of Multi-label Classifiers Zhuo Yang Yufei Han Xiangliang Zhang AAML 45 10 0 17 Dec 2020
Incentivizing Truthfulness Through Audits in Strategic Classification Andrew Estornell Sanmay Das Yevgeniy Vorobeychik MLAU 37 9 0 16 Dec 2020
A Closer Look at the Robustness of Vision-and-Language Pre-trained Models Linjie Li Zhe Gan Jingjing Liu VLM 96 44 0 15 Dec 2020
FoggySight: A Scheme for Facial Lookup Privacy Ivan Evtimov Pascal Sturmfels Tadayoshi Kohno PICV FedML 76 24 0 15 Dec 2020
Adaptive Verifiable Training Using Pairwise Class Similarity Shiqi Wang Kevin Eykholt Taesung Lee Jiyong Jang Ian Molloy OOD 33 1 0 14 Dec 2020
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints X. Li Xiangrui Li Deng Pan D. Zhu AAML 71 17 0 14 Dec 2020
Generating Out of Distribution Adversarial Attack using Latent Space Poisoning Ujjwal Upadhyay Prerana Mukherjee 78 7 0 09 Dec 2020
Reinforcement Based Learning on Classification Task Could Yield Better Generalization and Adversarial Accuracy Shashi Kant Gupta OOD 27 3 0 08 Dec 2020
Data-Dependent Randomized Smoothing Motasem Alfarra Adel Bibi Philip Torr Guohao Li UQCV 110 35 0 08 Dec 2020
Overcomplete Representations Against Adversarial Videos Shao-Yuan Lo Jeya Maria Jose Valanarasu Vishal M. Patel AAML 77 8 0 08 Dec 2020
Backpropagating Linearly Improves Transferability of Adversarial Examples Yiwen Guo Qizhang Li Hao Chen FedML AAML 82 117 0 07 Dec 2020
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection Byunggill Joe Jihun Hamm Sung Ju Hwang Sooel Son I. Shin AAML OOD 57 0 0 07 Dec 2020
Evaluating adversarial robustness in simulated cerebellum Liu Yuezhang Bo Li Qifeng Chen AAML 15 0 0 05 Dec 2020
Advocating for Multiple Defense Strategies against Adversarial Examples Alexandre Araujo Laurent Meunier Rafael Pinot Benjamin Négrevergne AAML 46 9 0 04 Dec 2020
Practical No-box Adversarial Attacks against DNNs Qizhang Li Yiwen Guo Hao Chen AAML 79 59 0 04 Dec 2020
FAT: Federated Adversarial Training Giulio Zizzo Ambrish Rawat M. Sinn Beat Buesser FedML 89 43 0 03 Dec 2020
FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques Han Qiu Yi Zeng Tianwei Zhang Yong Jiang Meikang Qiu AAML 44 15 0 03 Dec 2020
Content-Adaptive Pixel Discretization to Improve Model Robustness Ryan Feng Wu-chi Feng Atul Prakash AAML 37 0 0 03 Dec 2020
Interpretable Graph Capsule Networks for Object Recognition Jindong Gu Volker Tresp FAtt 73 36 0 03 Dec 2020
$Towards Defending Multiple $\ell_p$-norm Bounded Adversarial Perturbations via Gated Batch Normalization$ Towards Defending Multiple $\ell_p$ -norm Bounded Adversarial Perturbations via Gated Batch Normalization Aishan Liu Shiyu Tang Xinyun Chen Lei Huang Zhuozhuo Tu Xianglong Liu Dacheng Tao AAML 110 35 0 03 Dec 2020
From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation Nikhil Kapoor Andreas Bär Serin Varghese Jan David Schneider Fabian Hüger Peter Schlicht Tim Fingscheidt AAML 74 10 0 02 Dec 2020
How Robust are Randomized Smoothing based Defenses to Data Poisoning? Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD AAML 113 32 0 02 Dec 2020
Adversarial Robustness Across Representation Spaces Pranjal Awasthi George Yu Chun-Sung Ferng Andrew Tomkins Da-Cheng Juan OOD AAML 85 11 0 01 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 82 95 0 30 Nov 2020
Robust and Private Learning of Halfspaces Badih Ghazi Ravi Kumar Pasin Manurangsi Thao Nguyen 86 12 0 30 Nov 2020
FaceGuard: A Self-Supervised Defense Against Adversarial Face Images Debayan Deb Xiaoming Liu Anil K. Jain CVBM AAML PICV 98 27 0 28 Nov 2020
Deterministic Certification to Adversarial Attacks via Bernstein Polynomial Approximation Ching-Chia Kao Jhe-Bang Ko Chun-Shien Lu AAML 57 1 0 28 Nov 2020
Incorporating Hidden Layer representation into Adversarial Attacks and Defences Haojing Shen Sihong Chen Ran Wang Xizhao Wang AAML 61 0 0 28 Nov 2020
Voting based ensemble improves robustness of defensive models Devvrit Minhao Cheng Cho-Jui Hsieh Inderjit Dhillon OOD FedML AAML 73 12 0 28 Nov 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 70 5 0 27 Nov 2020
Use the Spear as a Shield: A Novel Adversarial Example based Privacy-Preserving Technique against Membership Inference Attacks Mingfu Xue Chengxiang Yuan Can He Zhiyu Wu Yushu Zhang Yanfeng Guo Weiqiang Liu MIACV 16 12 0 27 Nov 2020
Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness Yilun Jin Lixin Fan Kam Woh Ng Ce Ju Qiang Yang AAML OOD 27 1 0 27 Nov 2020
Exposing the Robustness and Vulnerability of Hybrid 8T-6T SRAM Memory Architectures to Adversarial Attacks in Deep Neural Networks Abhishek Moitra Priyadarshini Panda AAML 52 2 0 26 Nov 2020
Adversarial Evaluation of Multimodal Models under Realistic Gray Box Assumption Ivan Evtimov Russ Howes Brian Dolhansky Hamed Firooz Cristian Canton Ferrer AAML 49 10 0 25 Nov 2020
On Adversarial Robustness of 3D Point Cloud Classification under Adaptive Attacks Jiachen Sun Karl Koenig Yulong Cao Qi Alfred Chen Z. Morley Mao 3DPC 92 20 0 24 Nov 2020
Omni: Automated Ensemble with Unexpected Models against Adversarial Evasion Attack Rui Shu Tianpei Xia Laurie A. Williams Tim Menzies AAML 70 16 0 23 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 113 132 0 23 Nov 2020
A Neuro-Inspired Autoencoding Defense Against Adversarial Perturbations Can Bakiskan Metehan Cekic Ahmet Dundar Sezer Upamanyu Madhow AAML 52 0 0 21 Nov 2020