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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Membership Inference Attacks and Defenses in Neural Network Pruning Xiaoyong Yuan Lan Zhang AAML 16 44 0 07 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 19 4 0 03 Feb 2022
Query Efficient Decision Based Sparse Attacks Against Black-Box Deep Learning Models Viet Vo Ehsan Abbasnejad D. Ranasinghe AAML 22 14 0 31 Jan 2022
Boundary Defense Against Black-box Adversarial Attacks Manjushree B. Aithal Xiaohua Li AAML 17 6 0 31 Jan 2022
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Mengting Xu Tao Zhang Zhongnian Li Daoqiang Zhang AAML 30 1 0 29 Jan 2022
Efficient and Robust Classification for Sparse Attacks M. Beliaev Payam Delgosha Hamed Hassani Ramtin Pedarsani AAML 16 2 0 23 Jan 2022
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection Siyuan Liang Baoyuan Wu Yanbo Fan Xingxing Wei Xiaochun Cao AAML 22 70 0 22 Jan 2022
On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles Qingzhao Zhang Shengtuo Hu Jiachen Sun Qi Alfred Chen Z. Morley Mao AAML 35 133 0 13 Jan 2022
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks Weiran Lin Keane Lucas Lujo Bauer Michael K. Reiter Mahmood Sharif AAML 29 5 0 28 Dec 2021
Learning Robust and Lightweight Model through Separable Structured Transformations Xian Wei Yanhui Huang Yang Xu Mingsong Chen Hai Lan Yuanxiang Li Zhongfeng Wang Xuan Tang OOD 24 0 0 27 Dec 2021
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? Xinhsuai Dong Anh Tuan Luu Min-Bin Lin Shuicheng Yan Hanwang Zhang SILM AAML 20 55 0 22 Dec 2021
A Theoretical View of Linear Backpropagation and Its Convergence Ziang Li Yiwen Guo Haodi Liu Changshui Zhang AAML 16 3 0 21 Dec 2021
All You Need is RAW: Defending Against Adversarial Attacks with Camera Image Pipelines Yuxuan Zhang B. Dong Felix Heide AAML 26 8 0 16 Dec 2021
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 194 345 0 15 Dec 2021
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks Jaehui Hwang Huan Zhang Jun-Ho Choi Cho-Jui Hsieh Jong-Seok Lee AAML 17 5 0 15 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 15 13 0 14 Dec 2021
Triangle Attack: A Query-efficient Decision-based Adversarial Attack Xiaosen Wang Zeliang Zhang Kangheng Tong Dihong Gong Kun He Zhifeng Li Wei Liu AAML 24 56 0 13 Dec 2021
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 29 12 0 12 Dec 2021
RamBoAttack: A Robust Query Efficient Deep Neural Network Decision Exploit Viet Vo Ehsan Abbasnejad D. Ranasinghe AAML 17 9 0 10 Dec 2021
Mutual Adversarial Training: Learning together is better than going alone Jiang-Long Liu Chun Pong Lau Hossein Souri S. Feizi Ramalingam Chellappa OOD AAML 35 24 0 09 Dec 2021
SoK: Anti-Facial Recognition Technology Emily Wenger Shawn Shan Haitao Zheng Ben Y. Zhao PICV 32 13 0 08 Dec 2021
Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection Jiangjiang Liu Alexander Levine Chun Pong Lau Ramalingam Chellappa S. Feizi AAML 24 76 0 08 Dec 2021
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial Robustness Konstantinos P. Panousis S. Chatzis Sergios Theodoridis BDL AAML 60 11 0 05 Dec 2021
On the Existence of the Adversarial Bayes Classifier (Extended Version) Pranjal Awasthi Natalie Frank M. Mohri 21 24 0 03 Dec 2021
Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines Jiachen Sun Akshay Mehra B. Kailkhura Pin-Yu Chen Dan Hendrycks Jihun Hamm Z. Morley Mao AAML 28 21 0 01 Dec 2021
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial Domain Adaptation Tianyue Zheng Zhe Chen Shuya Ding Chao Cai Jun-Jie Luo AAML 33 5 0 01 Dec 2021
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial Robustness Jia-Li Yin Lehui Xie Wanqing Zhu Ximeng Liu Bo-Hao Chen TTA AAML 19 3 0 01 Dec 2021
Mitigating Adversarial Attacks by Distributing Different Copies to Different Users Jiyi Zhang Hansheng Fang W. Tann Ke Xu Chengfang Fang E. Chang AAML 21 3 0 30 Nov 2021
Pyramid Adversarial Training Improves ViT Performance Charles Herrmann Kyle Sargent Lu Jiang Ramin Zabih Huiwen Chang Ce Liu Dilip Krishnan Deqing Sun ViT 26 56 0 30 Nov 2021
Subspace Adversarial Training Tao Li Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML OOD 38 56 0 24 Nov 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 19 2 0 22 Nov 2021
Data Augmentation Can Improve Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 17 269 0 09 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 32 17 0 09 Nov 2021
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks Lijia Yu Xiao-Shan Gao AAML 16 5 0 08 Nov 2021
LTD: Low Temperature Distillation for Robust Adversarial Training Erh-Chung Chen Che-Rung Lee AAML 24 26 0 03 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks Maksym Yatsura J. H. Metzen Matthias Hein OOD 26 14 0 02 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 27 76 0 02 Nov 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 19 18 0 29 Oct 2021
Adversarial Robustness in Multi-Task Learning: Promises and Illusions Salah Ghamizi Maxime Cordy Mike Papadakis Yves Le Traon OOD AAML 25 18 0 26 Oct 2021
Ensemble Federated Adversarial Training with Non-IID data Shuang Luo Didi Zhu Zexi Li Chao-Xiang Wu FedML 25 7 0 26 Oct 2021
ADC: Adversarial attacks against object Detection that evade Context consistency checks Mingjun Yin Shasha Li Chengyu Song M. Salman Asif A. Roy-Chowdhury S. Krishnamurthy AAML 24 22 0 24 Oct 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 30 293 0 18 Oct 2021
Parameterizing Activation Functions for Adversarial Robustness Sihui Dai Saeed Mahloujifar Prateek Mittal AAML 42 32 0 11 Oct 2021
Adversarial Token Attacks on Vision Transformers Ameya Joshi Gauri Jagatap C. Hegde ViT 30 19 0 08 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 46 100 0 07 Oct 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 56 18 0 07 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble Yihao Wang AAML UQCV 9 1 0 07 Oct 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise Souvik Kundu Massoud Pedram P. Beerel AAML 14 70 0 06 Oct 2021
MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles Yuejun Guo Qiang Hu Maxime Cordy Michail Papadakis Yves Le Traon AAML 24 2 0 27 Sep 2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks Mikhail Aleksandrovich Pautov Nurislam Tursynbek Marina Munkhoeva Nikita Muravev Aleksandr Petiushko Ivan V. Oseledets AAML 44 15 0 22 Sep 2021