v1v2v3v4 (latest)

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 / 1,929 papers shown

Title
Pyramid Adversarial Training Improves ViT Performance Charles Herrmann Kyle Sargent Lu Jiang Ramin Zabih Huiwen Chang Ce Liu Dilip Krishnan Deqing Sun ViT 118 59 0 30 Nov 2021
Adaptive Image Transformations for Transfer-based Adversarial Attack Zheng Yuan Jie Zhang Shiguang Shan OOD 89 27 0 27 Nov 2021
Clustering Effect of (Linearized) Adversarial Robust Models Yang Bai Xin Yan Yong Jiang Shutao Xia Yisen Wang OOD AAML 79 5 0 25 Nov 2021
Robustness against Adversarial Attacks in Neural Networks using Incremental Dissipativity B. Aquino Arash Rahnama Peter M. Seiler Lizhen Lin Vijay Gupta AAML 58 8 0 25 Nov 2021
Unity is strength: Improving the Detection of Adversarial Examples with Ensemble Approaches Francesco Craighero Fabrizio Angaroni Fabio Stella Chiara Damiani M. Antoniotti Alex Graudenzi AAML 72 8 0 24 Nov 2021
Subspace Adversarial Training Tao Li Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML OOD 108 59 0 24 Nov 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 69 2 0 22 Nov 2021
Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks Kaiyuan Liu Xingyu Li Yu-Rui Lai Hong Xie Hang Su Jiacheng Wang Chunxu Guo J. Guan Yi Zhou AAML 89 4 0 21 Nov 2021
Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability Yifeng Xiong Jiadong Lin Min Zhang John E. Hopcroft Kun He AAML 126 115 0 21 Nov 2021
Fooling Adversarial Training with Inducing Noise Zhirui Wang Yifei Wang Yisen Wang 78 14 0 19 Nov 2021
Towards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method Tao Bai Jun Zhao Jinlin Zhu Shoudong Han Jiefeng Chen Yue Liu Alex C. Kot AAML 46 5 0 19 Nov 2021
A Review of Adversarial Attack and Defense for Classification Methods Yao Li Minhao Cheng Cho-Jui Hsieh T. C. Lee AAML 76 69 0 18 Nov 2021
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness Jongheon Jeong Sejun Park Minkyu Kim Heung-Chang Lee Do-Guk Kim Jinwoo Shin AAML 85 57 0 17 Nov 2021
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception Joel Dapello J. Feather Hang Le Tiago Marques David D. Cox Josh H. McDermott J. DiCarlo SueYeon Chung AAML OOD 68 25 0 12 Nov 2021
Data Augmentation Can Improve Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 65 295 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 87 18 0 09 Nov 2021
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search Pengfei Xia Ziqiang Li Bin Li AAML 121 3 0 09 Nov 2021
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks Lijia Yu Xiao-Shan Gao AAML 116 5 0 08 Nov 2021
Sequential Randomized Smoothing for Adversarially Robust Speech Recognition R. Olivier Bhiksha Raj AAML 133 11 0 05 Nov 2021
LTD: Low Temperature Distillation for Robust Adversarial Training Erh-Chung Chen Che-Rung Lee AAML 127 27 0 03 Nov 2021
Recent Advancements in Self-Supervised Paradigms for Visual Feature Representation Mrinal Anand Aditya Garg SSL 46 2 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 102 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 105 78 0 02 Nov 2021
When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? Lijie Fan Sijia Liu Pin-Yu Chen Gaoyuan Zhang Chuang Gan AAML VLM 95 125 0 01 Nov 2021
Holistic Deep Learning Dimitris Bertsimas Kimberly Villalobos Carballo L. Boussioux M. Li Alex Paskov I. Paskov 83 3 0 29 Oct 2021
Adversarial Robustness with Semi-Infinite Constrained Learning Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani Alejandro Ribeiro AAML OOD 184 46 0 29 Oct 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 71 18 0 29 Oct 2021
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks Hao Xue Kaixiong Zhou Tianlong Chen Kai Guo Helen Zhou Yi Chang Xin Wang AAML 76 15 0 28 Oct 2021
Towards Evaluating the Robustness of Neural Networks Learned by Transduction Jiefeng Chen Xi Wu Yang Guo Yingyu Liang S. Jha ELM AAML 92 15 0 27 Oct 2021
Towards Robust Reasoning over Knowledge Graphs Zhaohan Xi Ren Pang Changjiang Li S. Ji Xiapu Luo Xusheng Xiao Ting Wang 36 0 0 27 Oct 2021
Improving Local Effectiveness for Global robust training Jingyue Lu M. P. Kumar AAML 49 0 0 26 Oct 2021
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions I. Alsmadi Kashif Ahmad Mahmoud Nazzal Firoj Alam Ala I. Al-Fuqaha Abdallah Khreishah A. Algosaibi AAML 64 16 0 26 Oct 2021
A Frequency Perspective of Adversarial Robustness Shishira R. Maiya Max Ehrlich Vatsal Agarwal Ser-Nam Lim Tom Goldstein Abhinav Shrivastava AAML 72 40 0 26 Oct 2021
Defensive Tensorization Adrian Bulat Jean Kossaifi S. Bhattacharya Yannis Panagakis Timothy M. Hospedales Georgios Tzimiropoulos Nicholas D. Lane Maja Pantic AAML 35 4 0 26 Oct 2021
Adversarial Robustness in Multi-Task Learning: Promises and Illusions Salah Ghamizi Maxime Cordy Mike Papadakis Yves Le Traon OOD AAML 90 18 0 26 Oct 2021
Ensemble Federated Adversarial Training with Non-IID data Shuang Luo Didi Zhu Zexi Li Chao-Xiang Wu FedML 66 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 Amit K. Roy-Chowdhury S. Krishnamurthy AAML 114 25 0 24 Oct 2021
A Layer-wise Adversarial-aware Quantization Optimization for Improving Robustness Chang Song Riya Ranjan H. Li MQ 67 4 0 23 Oct 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 139 302 0 18 Oct 2021
Adversarial Attacks on ML Defense Models Competition Yinpeng Dong Qi-An Fu Xiao Yang Wenzhao Xiang Tianyu Pang ... Zhennan Wu Yang Guo Jiequan Cui Xiaogang Xu Pengguang Chen AAML 62 2 0 15 Oct 2021
Adversarial Purification through Representation Disentanglement Tao Bai Jun Zhao Lanqing Guo Bihan Wen AAML 37 1 0 15 Oct 2021
Interactive Analysis of CNN Robustness Stefan Sietzen Mathias Lechner Judy Borowski Ramin Hasani Manuela Waldner AAML 81 10 0 14 Oct 2021
Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks Shawn Shan A. Bhagoji Haitao Zheng Ben Y. Zhao AAML 170 51 0 13 Oct 2021
Boosting the Certified Robustness of L-infinity Distance Nets Bohang Zhang Du Jiang Di He Liwei Wang OOD 93 30 0 13 Oct 2021
Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness Xiao Yang Yinpeng Dong Wenzhao Xiang Tianyu Pang Hang Su Jun Zhu AAML 66 4 0 13 Oct 2021
On the Security Risks of AutoML Ren Pang Zhaohan Xi S. Ji Xiapu Luo Ting Wang AAML 54 10 0 12 Oct 2021
Parameterizing Activation Functions for Adversarial Robustness Sihui Dai Saeed Mahloujifar Prateek Mittal AAML 84 32 0 11 Oct 2021
Intriguing Properties of Input-dependent Randomized Smoothing Peter Súkeník A. Kuvshinov Stephan Günnemann AAML UQCV 74 22 0 11 Oct 2021
Adversarial Token Attacks on Vision Transformers Ameya Joshi Gauri Jagatap Chinmay Hegde ViT 104 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 139 102 0 07 Oct 2021