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
TDGIA:Effective Injection Attacks on Graph Neural Networks Xu Zou Qinkai Zheng Yuxiao Dong Xinyu Guan Evgeny Kharlamov Jialiang Lu Jie Tang AAML 45 102 0 12 Jun 2021
Adversarial purification with Score-based generative models Jongmin Yoon Sung Ju Hwang Juho Lee DiffM 30 153 0 11 Jun 2021
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix Maximilian Lam Gu-Yeon Wei David Brooks Vijay Janapa Reddi Michael Mitzenmacher FedML 20 63 0 10 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 31 0 09 Jun 2021
Provably Robust Detection of Out-of-distribution Data (almost) for free Alexander Meinke Julian Bitterwolf Matthias Hein OODD 38 22 0 08 Jun 2021
Reveal of Vision Transformers Robustness against Adversarial Attacks Ahmed Aldahdooh W. Hamidouche Olivier Déforges ViT 17 57 0 07 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 23 9 0 31 May 2021
Analysis and Applications of Class-wise Robustness in Adversarial Training Qi Tian Kun Kuang Ke Jiang Fei Wu Yisen Wang AAML 23 46 0 29 May 2021
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training Yatong Bai Tanmay Gautam Yujie Gai Somayeh Sojoudi AAML 29 3 0 25 May 2021
Improved OOD Generalization via Adversarial Training and Pre-training Mingyang Yi Lu Hou Jiacheng Sun Lifeng Shang Xin Jiang Qun Liu Zhi-Ming Ma VLM 35 83 0 24 May 2021
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks Leo Schwinn René Raab A. Nguyen Dario Zanca Bjoern M. Eskofier AAML 14 60 0 21 May 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David Wagner Trevor Darrell AAML 26 27 0 18 May 2021
Sparta: Spatially Attentive and Adversarially Robust Activation Qing Guo Felix Juefei Xu Changqing Zhou Wei Feng Yang Liu Song Wang AAML 43 4 0 18 May 2021
High-Robustness, Low-Transferability Fingerprinting of Neural Networks Siyue Wang Xiao Wang Pin-Yu Chen Pu Zhao Xue Lin AAML 40 2 0 14 May 2021
Multi-Robot Coordination and Planning in Uncertain and Adversarial Environments Lifeng Zhou Pratap Tokekar 51 43 0 02 May 2021
Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense Haoxi Zhan Xiaobing Pei AAML 27 9 0 30 Apr 2021
Random Noise Defense Against Query-Based Black-Box Attacks Zeyu Qin Yanbo Fan H. Zha Baoyuan Wu AAML 29 60 0 23 Apr 2021
Removing Adversarial Noise in Class Activation Feature Space Dawei Zhou N. Wang Chunlei Peng Xinbo Gao Xiaoyu Wang Jun Yu Tongliang Liu AAML 30 28 0 19 Apr 2021
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems Yue Gao Ilia Shumailov Kassem Fawaz AAML 44 10 0 18 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 43 65 0 09 Apr 2021
A single gradient step finds adversarial examples on random two-layers neural networks Sébastien Bubeck Yeshwanth Cherapanamjeri Gauthier Gidel Rémi Tachet des Combes MLT 39 27 0 08 Apr 2021
Universal Adversarial Training with Class-Wise Perturbations Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 27 26 0 07 Apr 2021
Mitigating Gradient-based Adversarial Attacks via Denoising and Compression Rehana Mahfuz R. Sahay Aly El Gamal AAML 27 3 0 03 Apr 2021
On the Robustness of Vision Transformers to Adversarial Examples Kaleel Mahmood Rigel Mahmood Marten van Dijk ViT 33 219 0 31 Mar 2021
Towards Understanding Adversarial Robustness of Optical Flow Networks Simon Schrodi Tonmoy Saikia Thomas Brox AAML 44 15 0 30 Mar 2021
On the Adversarial Robustness of Vision Transformers Rulin Shao Zhouxing Shi Jinfeng Yi Pin-Yu Chen Cho-Jui Hsieh ViT 40 138 0 29 Mar 2021
Enhancing the Transferability of Adversarial Attacks through Variance Tuning Xiaosen Wang Kun He AAML 50 380 0 29 Mar 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness Yi Cai Xuefei Ning Huazhong Yang Yu Wang AAML 27 4 0 27 Mar 2021
Cyclic Defense GAN Against Speech Adversarial Attacks Mohammad Esmaeilpour P. Cardinal Alessandro Lameiras Koerich AAML 32 7 0 26 Mar 2021
Combating Adversaries with Anti-Adversaries Motasem Alfarra Juan C. Pérez Ali K. Thabet Adel Bibi Philip Torr Guohao Li AAML 34 27 0 26 Mar 2021
Adversarial Attacks are Reversible with Natural Supervision Chengzhi Mao Mia Chiquer Hao Wang Junfeng Yang Carl Vondrick BDL AAML 31 56 0 26 Mar 2021
Deepfake Forensics via An Adversarial Game Zhi Wang Yiwen Guo W. Zuo AAML 21 35 0 25 Mar 2021
Adversarially Optimized Mixup for Robust Classification Jason Bunk Srinjoy Chattopadhyay B. S. Manjunath S. Chandrasekaran AAML 30 8 0 22 Mar 2021
Boosting Adversarial Transferability through Enhanced Momentum Xiaosen Wang Jiadong Lin Han Hu Jingdong Wang Kun He AAML 16 76 0 19 Mar 2021
Bio-inspired Robustness: A Review Harshitha Machiraju Oh-hyeon Choung P. Frossard Michael H. Herzog AAML 42 1 0 16 Mar 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 38 34 0 15 Mar 2021
Cloth Manipulation Planning on Basis of Mesh Representations with Incomplete Domain Knowledge and Voxel-to-Mesh Estimation S. Arnold Daisuke Tanaka Kimitoshi Yamazaki 22 4 0 15 Mar 2021
Generating Unrestricted Adversarial Examples via Three Parameters Hanieh Naderi Leili Goli S. Kasaei 44 8 0 13 Mar 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Xu Cheng Xin Eric Wang Meng Zhou Jie Shi Quanshi Zhang AAML 72 22 0 12 Mar 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 41 58 0 08 Mar 2021
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN Desheng Wang Wei-dong Jin Yunpu Wu Aamir Khan GAN 36 8 0 08 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 33 41 0 05 Mar 2021
WaveGuard: Understanding and Mitigating Audio Adversarial Examples Shehzeen Samarah Hussain Paarth Neekhara Shlomo Dubnov Julian McAuley F. Koushanfar AAML 33 71 0 04 Mar 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude Fu Lee Wang Yanghao Zhang Yanbin Zheng Wenjie Ruan 31 1 0 04 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 36 271 0 02 Mar 2021
Evaluating the Robustness of Geometry-Aware Instance-Reweighted Adversarial Training Dorjan Hitaj Giulio Pagnotta I. Masi L. Mancini OOD AAML 26 22 0 02 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 27 6 0 01 Mar 2021
Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay Shalmali Joshi Himabindu Lakkaraju 25 108 0 26 Feb 2021
Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks Huichen Li Linyi Li Xiaojun Xu Xiaolu Zhang Shuang Yang Yue Liu AAML 35 17 0 25 Feb 2021
Understanding Robustness in Teacher-Student Setting: A New Perspective Zhuolin Yang Zhaoxi Chen Tiffany Cai Xinyun Chen Yue Liu Yuandong Tian AAML 35 2 0 25 Feb 2021