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 / 721 papers shown

Title
Explainability and Robustness of Deep Visual Classification Models Jindong Gu AAML 47 2 0 03 Jan 2023
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli Fahad Shahbaz Khan AAML 28 1 0 30 Dec 2022
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization Shiji Xin Yifei Wang Jingtong Su Yisen Wang OOD 23 7 0 18 Dec 2022
Confidence-aware Training of Smoothed Classifiers for Certified Robustness Jongheon Jeong Seojin Kim Jinwoo Shin AAML 21 7 0 18 Dec 2022
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 29 18 0 16 Dec 2022
Adversarial Example Defense via Perturbation Grading Strategy Shaowei Zhu Wanli Lyu Bin Li Z. Yin Bin Luo AAML 32 1 0 16 Dec 2022
On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practices Salah Ghamizi Maxime Cordy Michail Papadakis Yves Le Traon OOD 11 2 0 15 Dec 2022
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 29 5 0 15 Dec 2022
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models Chengzhi Mao Scott Geng Junfeng Yang Xin Eric Wang Carl Vondrick VLM 44 60 0 14 Dec 2022
Adversarially Robust Video Perception by Seeing Motion Lingyu Zhang Chengzhi Mao Junfeng Yang Carl Vondrick VGen AAML 44 2 0 13 Dec 2022
Robust Perception through Equivariance Chengzhi Mao Lingyu Zhang Abhishek Joshi Junfeng Yang Hongya Wang Carl Vondrick BDL AAML 29 7 0 12 Dec 2022
REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun Chawin Sitawarin Jerry Li David Wagner AAML 31 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 Torr Jiaya Jia AAML 32 2 0 11 Dec 2022
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 34 4 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
Adversarial Rademacher Complexity of Deep Neural Networks Jiancong Xiao Yanbo Fan Ruoyu Sun Zhimin Luo AAML 17 22 0 27 Nov 2022
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles Shengcai Liu Fu Peng Jiaheng Zhang AAML 39 11 0 23 Nov 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 30 33 0 23 Nov 2022
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack Yunfeng Diao He Wang Tianjia Shao Yong-Liang Yang Kun Zhou David C. Hogg Meng Wang AAML 42 7 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 33 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 27 20 0 17 Nov 2022
Textual Manifold-based Defense Against Natural Language Adversarial Examples D. M. Nguyen Anh Tuan Luu AAML 27 17 0 05 Nov 2022
An Adversarial Robustness Perspective on the Topology of Neural Networks Morgane Goibert Thomas Ricatte Elvis Dohmatob AAML 13 2 0 04 Nov 2022
Adversarial Attack on Radar-based Environment Perception Systems Amira Guesmi Ihsen Alouani AAML 33 2 0 02 Nov 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 22 14 0 27 Oct 2022
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Richard I. Hartley Peter Tu AAML 24 5 0 26 Oct 2022
Accelerating Certified Robustness Training via Knowledge Transfer Pratik Vaishnavi Kevin Eykholt Amir Rahmati 24 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 Yi 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 69 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 54 5 0 19 Oct 2022
Scaling Adversarial Training to Large Perturbation Bounds Sravanti Addepalli Samyak Jain Gaurang Sriramanan R. Venkatesh Babu AAML 33 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 45 52 0 14 Oct 2022
Visual Prompting for Adversarial Robustness Aochuan Chen P. Lorenz Yuguang Yao Pin-Yu Chen Sijia Liu VLM VPVLM 40 32 0 12 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 33 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 31 6 0 06 Oct 2022
Strength-Adaptive Adversarial Training Chaojian Yu Dawei Zhou Li Shen Jun Yu Bo Han Biwei Huang 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 32 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 27 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 26 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
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 32 1 0 14 Sep 2022
CARE: Certifiably Robust Learning with Reasoning via Variational Inference Jiawei Zhang Linyi Li Ce Zhang Bo-wen Li AAML OOD 43 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 34 12 0 07 Sep 2022
Defending Against Backdoor Attack on Graph Nerual Network by Explainability B. Jiang Zhao Li AAML GNN 64 16 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 35 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 32 0 0 17 Aug 2022
Ad Hoc Teamwork in the Presence of Adversaries Ted Fujimoto Samrat Chatterjee A. Ganguly 35 2 0 09 Aug 2022
Robust Real-World Image Super-Resolution against Adversarial Attacks N. Babaguchi John R. Smith Pengxu Wei T. Plagemann Rong Yan AAML 26 25 0 31 Jul 2022