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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"

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Watch What You Pretrain For: Targeted, Transferable Adversarial Examples on Self-Supervised Speech Recognition models R. Olivier H. Abdullah Bhiksha Raj AAML 77 1 0 17 Sep 2022
Towards Bridging the Performance Gaps of Joint Energy-based Models Xiulong Yang Qing Su Shihao Ji VLM 71 15 0 16 Sep 2022
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness Mazda Moayeri Kiarash Banihashem Soheil Feizi OOD 129 23 0 15 Sep 2022
Part-Based Models Improve Adversarial Robustness Chawin Sitawarin Kornrapat Pongmala Yizheng Chen Nicholas Carlini David Wagner 110 12 0 15 Sep 2022
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos Volkan Cevher 104 21 0 15 Sep 2022
PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial Attack Junxuan Huang Yatong An Lu Cheng Bai Chen Junsong Yuan Chunming Qiao 3DPC 57 1 0 14 Sep 2022
Robust Transferable Feature Extractors: Learning to Defend Pre-Trained Networks Against White Box Adversaries Alexander Cann Ian Colbert I. Amer AAML 26 1 0 14 Sep 2022
TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective Attack Yanyun Wang Dehui Du Haibo Hu Zi Liang Yuanhao Liu AAML AI4TS 107 3 0 14 Sep 2022
CARE: Certifiably Robust Learning with Reasoning via Variational Inference Jiawei Zhang Linyi Li Ce Zhang Yue Liu AAML OOD 122 8 0 12 Sep 2022
The Space of Adversarial Strategies Ryan Sheatsley Blaine Hoak Eric Pauley Patrick McDaniel AAML 98 6 0 09 Sep 2022
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples Nuo Xu Kaleel Mahmood Haowen Fang Ethan Rathbun Caiwen Ding Wujie Wen AAML 104 13 0 07 Sep 2022
Defending Against Backdoor Attack on Graph Nerual Network by Explainability B. Jiang Zhao Li AAML GNN 121 17 0 07 Sep 2022
Revisiting Outer Optimization in Adversarial Training Ali Dabouei Fariborz Taherkhani Sobhan Soleymani Nasser M. Nasrabadi AAML 90 4 0 02 Sep 2022
Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning Zhiyuan He Yijun Yang Pin-Yu Chen Qiang Xu Tsung-Yi Ho AAML 71 9 0 31 Aug 2022
Unrestricted Adversarial Samples Based on Non-semantic Feature Clusters Substitution Ming-Kuai Zhou Xiaobing Pei AAML 47 0 0 31 Aug 2022
Towards Adversarial Purification using Denoising AutoEncoders Dvij Kalaria Aritra Hazra P. Chakrabarti DiffM 56 5 0 29 Aug 2022
SA: Sliding attack for synthetic speech detection with resistance to clipping and self-splicing JiaCheng Deng Dong Li Yan Diqun Rangding Wang Zeng Jiaming AAML 67 0 0 27 Aug 2022
A Perturbation Resistant Transformation and Classification System for Deep Neural Networks Nathaniel R. Dean D. Sarkar AAML 24 0 0 25 Aug 2022
Black-box Attacks Against Neural Binary Function Detection Josh Bundt Michael Davinroy Ioannis Agadakos Alina Oprea William K. Robertson AAML 58 1 0 24 Aug 2022
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries Dongbin Na Sangwoo Ji Jong Kim AAML 82 17 0 24 Aug 2022
Auditing Membership Leakages of Multi-Exit Networks Zheng Li Yiyong Liu Xinlei He Ning Yu Michael Backes Yang Zhang AAML 73 34 0 23 Aug 2022
Adversarial Vulnerability of Temporal Feature Networks for Object Detection Svetlana Pavlitskaya Nikolai Polley Michael Weber J. Marius Zöllner AAML 65 3 0 23 Aug 2022
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition Jiachen Sun Weili Nie Zhiding Yu Z. Morley Mao Chaowei Xiao DiffM 72 25 0 21 Aug 2022
Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries Manaar Alam Shubhajit Datta Debdeep Mukhopadhyay Arijit Mondal P. Chakrabarti AAML 30 5 0 18 Aug 2022
An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks Raz Lapid Zvika Haramaty Moshe Sipper AAML MLAU 73 12 0 17 Aug 2022
On the Privacy Effect of Data Enhancement via the Lens of Memorization Xiao-Li Li Qiongxiu Li Zhan Hu Xiaolin Hu 95 15 0 17 Aug 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models Dong Huang Qi Bu Yuhao Qing Haowen Pi Sen Wang Heming Cui OOD AAML 60 0 0 17 Aug 2022
An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models Brendon G. Anderson Tanmay Gautam Somayeh Sojoudi OOD 53 2 0 15 Aug 2022
Unifying Gradients to Improve Real-world Robustness for Deep Networks Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML 88 3 0 12 Aug 2022
A Sublinear Adversarial Training Algorithm Yeqi Gao Lianke Qin Zhao Song Yitan Wang GAN 77 25 0 10 Aug 2022
Ad Hoc Teamwork in the Presence of Adversaries Ted Fujimoto Samrat Chatterjee A. Ganguly 75 3 0 09 Aug 2022
Federated Adversarial Learning: A Framework with Convergence Analysis Xiaoxiao Li Zhao Song Jiaming Yang FedML 92 21 0 07 Aug 2022
Attacking Adversarial Defences by Smoothing the Loss Landscape Panagiotis Eustratiadis Henry Gouk Da Li Timothy M. Hospedales AAML 83 4 0 01 Aug 2022
Robust Real-World Image Super-Resolution against Adversarial Attacks N. Babaguchi John R. Smith Pengxu Wei T. Plagemann Rong Yan AAML 110 27 0 31 Jul 2022
Robust Trajectory Prediction against Adversarial Attacks Yulong Cao Danfei Xu Xinshuo Weng Zhuoqing Mao Anima Anandkumar Chaowei Xiao Marco Pavone AAML 74 30 0 29 Jul 2022
Shift-tolerant Perceptual Similarity Metric Abhijay Ghildyal Feng Liu 63 41 0 27 Jul 2022
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness Jindong Gu Hengshuang Zhao Volker Tresp Philip Torr AAML 122 78 0 25 Jul 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 108 18 0 24 Jul 2022
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness Chaoning Zhang Kang Zhang Chenshuang Zhang Axi Niu Jiu Feng Chang D. Yoo In So Kweon SSL 96 25 0 22 Jul 2022
Towards Efficient Adversarial Training on Vision Transformers Boxi Wu Jindong Gu Zhifeng Li Deng Cai Xiaofei He Wei Liu ViT AAML 112 40 0 21 Jul 2022
Rethinking Textual Adversarial Defense for Pre-trained Language Models Jiayi Wang Rongzhou Bao Zhuosheng Zhang Hai Zhao AAML SILM 61 11 0 21 Jul 2022
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training Sekitoshi Kanai Shin'ya Yamaguchi Masanori Yamada Hiroshi Takahashi Kentaro Ohno Yasutoshi Ida AAML 87 9 0 21 Jul 2022
Tailoring Self-Supervision for Supervised Learning WonJun Moon Ji-Hwan Kim Jae-Pil Heo SSL 55 10 0 20 Jul 2022
Bounding generalization error with input compression: An empirical study with infinite-width networks A. Galloway A. Golubeva Mahmoud Salem Mihai Nica Yani Andrew Ioannou Graham W. Taylor MLT AI4CE 81 4 0 19 Jul 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 143 76 0 19 Jul 2022
Decorrelative Network Architecture for Robust Electrocardiogram Classification Christopher Wiedeman Ge Wang OOD 88 2 0 19 Jul 2022
Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations H. Malik Shahina Kunhimon Muzammal Naseer Salman Khan Fahad Shahbaz Khan AAML 63 8 0 18 Jul 2022
Adversarial Contrastive Learning via Asymmetric InfoNCE Qiying Yu Jieming Lou Xianyuan Zhan Qizhang Li W. Zuo Yang Liu Jingjing Liu AAML 79 23 0 18 Jul 2022
Automated Repair of Neural Networks Dor Cohen O. Strichman KELM NAI AAML 25 4 0 17 Jul 2022
Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using Stackelberg Game Xiao-Shan Gao Shuang Liu Lijia Yu AAML 78 0 0 17 Jul 2022