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
REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun Chawin Sitawarin Jerry Li David A. Wagner AAML 29 14 0 12 Dec 2022
General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments Xiaogang Xu Hengshuang Zhao Philip H. S. Torr Jiaya Jia AAML 24 2 0 11 Dec 2022
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 30 3 0 08 Dec 2022
Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning Hongbin Liu Wenjie Qu Jinyuan Jia Neil Zhenqiang Gong SSL 28 6 0 06 Dec 2022
Benchmarking Adversarially Robust Quantum Machine Learning at Scale Maxwell T. West S. Erfani C. Leckie M. Sevior Lloyd C. L. Hollenberg Muhammad Usman AAML OOD 22 33 0 23 Nov 2022
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack Yunfeng Diao He-Nan Wang Tianjia Shao Yong-Liang Yang Kun Zhou David C. Hogg Meng Wang AAML 32 6 0 21 Nov 2022
Boosting the Transferability of Adversarial Attacks with Global Momentum Initialization Jiafeng Wang Zhaoyu Chen Kaixun Jiang Dingkang Yang Lingyi Hong Pinxue Guo Yan Wang Wenqiang Zhang AAML 21 27 0 21 Nov 2022
Towards Good Practices in Evaluating Transfer Adversarial Attacks Zhengyu Zhao Hanwei Zhang Renjue Li R. Sicre Laurent Amsaleg Michael Backes AAML 21 20 0 17 Nov 2022
Textual Manifold-based Defense Against Natural Language Adversarial Examples D. M. Nguyen Anh Tuan Luu AAML 17 17 0 05 Nov 2022
An Adversarial Robustness Perspective on the Topology of Neural Networks Morgane Goibert Thomas Ricatte Elvis Dohmatob AAML 11 2 0 04 Nov 2022
Adversarial Attack on Radar-based Environment Perception Systems Amira Guesmi Ihsen Alouani AAML 33 2 0 02 Nov 2022
Accelerating Certified Robustness Training via Knowledge Transfer Pratik Vaishnavi Kevin Eykholt Amir Rahmati 16 7 0 25 Oct 2022
Revisiting Sparse Convolutional Model for Visual Recognition Xili Dai Mingyang Li Pengyuan Zhai Shengbang Tong Xingjian Gao Shao-Lun Huang Zhihui Zhu Chong You Y. Ma FAtt 35 27 0 24 Oct 2022
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation Fan Yin Yao Li Cho-Jui Hsieh Kai-Wei Chang AAML 60 4 0 22 Oct 2022
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey Huiyun Cao Wenlong Zou Yinkun Wang Ting Song Mengjun Liu AAML 44 4 0 19 Oct 2022
Scaling Adversarial Training to Large Perturbation Bounds Sravanti Addepalli Samyak Jain Gaurang Sriramanan R. Venkatesh Babu AAML 27 22 0 18 Oct 2022
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Yi Mo Dongxian Wu Yifei Wang Yiwen Guo Yisen Wang ViT 39 52 0 14 Oct 2022
Visual Prompting for Adversarial Robustness Aochuan Chen P. Lorenz Yuguang Yao Pin-Yu Chen Sijia Liu VLM VPVLM 25 32 0 12 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 25 5 0 11 Oct 2022
Towards Out-of-Distribution Adversarial Robustness Adam Ibrahim Charles Guille-Escuret Ioannis Mitliagkas Irina Rish David M. Krueger P. Bashivan OOD 29 6 0 06 Oct 2022
Strength-Adaptive Adversarial Training Chaojian Yu Dawei Zhou Li Shen Jun Yu Bo Han Mingming Gong Nannan Wang Tongliang Liu OOD 17 2 0 04 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 24 30 0 03 Oct 2022
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks Kevin Hector Mathieu Dumont Pierre-Alain Moëllic J. Dutertre AAML 19 4 0 28 Sep 2022
Watch What You Pretrain For: Targeted, Transferable Adversarial Examples on Self-Supervised Speech Recognition models R. Olivier H. Abdullah Bhiksha Raj AAML 21 1 0 17 Sep 2022
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher 39 19 0 15 Sep 2022
CARE: Certifiably Robust Learning with Reasoning via Variational Inference Jiawei Zhang Linyi Li Ce Zhang Bo-wen Li AAML OOD 40 8 0 12 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 29 12 0 07 Sep 2022
Unrestricted Adversarial Samples Based on Non-semantic Feature Clusters Substitution Ming-Kuai Zhou Xiaobing Pei AAML 16 0 0 31 Aug 2022
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries Dongbin Na Sangwoo Ji Jong Kim AAML 27 17 0 24 Aug 2022
Adversarial Vulnerability of Temporal Feature Networks for Object Detection Svetlana Pavlitskaya Nikolai Polley Michael Weber J. Marius Zöllner AAML 14 2 0 23 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 22 0 0 17 Aug 2022
Robust Real-World Image Super-Resolution against Adversarial Attacks N. Babaguchi John R. Smith Pengxu Wei T. Plagemann Rong Yan AAML 18 25 0 31 Jul 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 36 18 0 24 Jul 2022
Towards Efficient Adversarial Training on Vision Transformers Boxi Wu Jindong Gu Zhifeng Li Deng Cai Xiaofei He Wei Liu ViT AAML 35 37 0 21 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 51 71 0 19 Jul 2022
Decorrelative Network Architecture for Robust Electrocardiogram Classification Christopher Wiedeman Ge Wang OOD 13 2 0 19 Jul 2022
Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations H. Malik Shahina Kunhimon Muzammal Naseer Salman Khan F. Khan AAML 20 8 0 18 Jul 2022
Threat Model-Agnostic Adversarial Defense using Diffusion Models Tsachi Blau Roy Ganz Bahjat Kawar Alex M. Bronstein Michael Elad AAML DiffM 27 26 0 17 Jul 2022
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models Ronghui Mu Wenjie Ruan Leandro Soriano Marcolino Q. Ni 3DPC 24 10 0 15 Jul 2022
Provably Adversarially Robust Nearest Prototype Classifiers Václav Voráček Matthias Hein AAML 20 11 0 14 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing Yijiang Pang Boyang Liu Jiayu Zhou OOD AAML 19 1 0 11 Jul 2022
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy R. Olivier Bhiksha Raj AAML 29 5 0 08 Jul 2022
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 36 16 0 28 Jun 2022
On the Limitations of Stochastic Pre-processing Defenses Yue Gao Ilia Shumailov Kassem Fawaz Nicolas Papernot AAML SILM 34 30 0 19 Jun 2022
Landscape Learning for Neural Network Inversion Ruoshi Liu Chen-Guang Mao Purva Tendulkar Hongya Wang Carl Vondrick 32 8 0 17 Jun 2022
Analysis and Extensions of Adversarial Training for Video Classification K. A. Kinfu René Vidal AAML 25 13 0 16 Jun 2022
Efficiently Training Low-Curvature Neural Networks Suraj Srinivas Kyle Matoba Himabindu Lakkaraju F. Fleuret AAML 23 15 0 14 Jun 2022
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale Gaoyuan Zhang Songtao Lu Yihua Zhang Xiangyi Chen Pin-Yu Chen Quanfu Fan Lee Martie L. Horesh Min-Fong Hong Sijia Liu OOD 24 12 0 13 Jun 2022
NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference Attacks Nuo Xu Binghui Wang Ran Ran Wujie Wen Parv Venkitasubramaniam AAML 18 5 0 11 Jun 2022
ReFace: Real-time Adversarial Attacks on Face Recognition Systems Shehzeen Samarah Hussain Todd P. Huster Chris Mesterharm Paarth Neekhara Kevin R. An Malhar Jere Harshvardhan Digvijay Sikka F. Koushanfar AAML 8 6 0 09 Jun 2022