On Adaptive Attacks to Adversarial Example Defenses

19 February 2020

Wieland Brendel

Papers citing "On Adaptive Attacks to Adversarial Example Defenses"

50 / 540 papers shown

Title
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
Improving Robustness with Image Filtering M. Terzi Mattia Carletti Gian Antonio Susto AAML 29 0 0 21 Dec 2021
Deep Reinforcement Learning Policies Learn Shared Adversarial Features Across MDPs Ezgi Korkmaz 19 25 0 16 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 19 5 0 15 Dec 2021
Robustifying automatic speech recognition by extracting slowly varying features Matías P. Pizarro D. Kolossa Asja Fischer AAML 17 2 0 14 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 23 13 0 14 Dec 2021
SoK: Anti-Facial Recognition Technology Emily Wenger Shawn Shan Haitao Zheng Ben Y. Zhao PICV 32 13 0 08 Dec 2021
Image classifiers can not be made robust to small perturbations Zheng Dai David K Gifford VLM AAML 21 1 0 07 Dec 2021
Generalized Likelihood Ratio Test for Adversarially Robust Hypothesis Testing Bhagyashree Puranik Upamanyu Madhow Ramtin Pedarsani AAML 22 4 0 04 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 33 21 0 01 Dec 2021
Adaptive Image Transformations for Transfer-based Adversarial Attack Zheng Yuan Jie Zhang Shiguang Shan OOD 16 25 0 27 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 13 8 0 24 Nov 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 21 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 26 3 0 21 Nov 2021
Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability Yifeng Xiong Jiadong Lin Min Zhang J. Hopcroft Kun He AAML 38 111 0 21 Nov 2021
TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems Bao Gia Doan Minhui Xue Shiqing Ma Ehsan Abbasnejad D. Ranasinghe AAML 41 53 0 19 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 23 55 0 17 Nov 2021
Detecting AutoAttack Perturbations in the Frequency Domain P. Lorenz P. Harder Dominik Strassel M. Keuper J. Keuper AAML 11 13 0 16 Nov 2021
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search Pengfei Xia Ziqiang Li Bin Li AAML 38 3 0 09 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
Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach A. Sarkar Anirban Sarkar Sowrya Gali V. Balasubramanian AAML 27 7 0 30 Oct 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 21 18 0 29 Oct 2021
A Survey on Threat Situation Awareness Systems: Framework, Techniques, and Insights Hooman Alavizadeh Julian Jang S. Y. Enoch Harith Al-Sahaf I. Welch S. Çamtepe Dong Seong Kim 8 7 0 29 Oct 2021
Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks Hassan Dbouk Naresh R Shanbhag AAML 21 7 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 15 15 0 27 Oct 2021
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu Qixuan Yu Yang Zhang Shan-Hung Wu Ouyang Xu David D. Cox Yingyan Lin AAML OOD 25 29 0 26 Oct 2021
Frequency Centric Defense Mechanisms against Adversarial Examples Sanket B. Shah Param Raval Harin Khakhi M. Raval AAML 14 7 0 26 Oct 2021
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Jingwei Sun Ang Li Louis DiValentin Amin Hassanzadeh Yiran Chen H. Li FedML OOD AAML 13 76 0 26 Oct 2021
A Regularization Method to Improve Adversarial Robustness of Neural Networks for ECG Signal Classification Linhai Ma Liang Liang 17 21 0 19 Oct 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 36 293 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 13 2 0 15 Oct 2021
Bugs in our Pockets: The Risks of Client-Side Scanning H. Abelson Ross J. Anderson S. Bellovin Josh Benaloh M. Blaze ... Ronald L. Rivest J. Schiller B. Schneier Vanessa J. Teague Carmela Troncoso 62 39 0 14 Oct 2021
Boosting the Certified Robustness of L-infinity Distance Nets Bohang Zhang Du Jiang Di He Liwei Wang OOD 32 29 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 19 4 0 13 Oct 2021
Certified Patch Robustness via Smoothed Vision Transformers Hadi Salman Saachi Jain Eric Wong Aleksander Mkadry AAML 70 58 0 11 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
Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation Manjushree B. Aithal Xiaohua Li AAML 52 6 0 30 Sep 2021
Introducing the DOME Activation Functions Mohamed E. Hussein Wael AbdAlmageed 30 1 0 30 Sep 2021
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 186 273 0 28 Sep 2021
Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view Inconsistency Sohaib Kiani S. Awan Chao Lan Fengjun Li Bo Luo GAN AAML 20 7 0 25 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 49 15 0 22 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 38 16 0 20 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 35 4 0 16 Sep 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency Yonggan Fu Yang Katie Zhao Qixuan Yu Chaojian Li Yingyan Lin AAML 49 12 0 11 Sep 2021
SEC4SR: A Security Analysis Platform for Speaker Recognition Guangke Chen Zhe Zhao Fu Song Sen Chen Lingling Fan Yang Liu AAML 19 12 0 04 Sep 2021
Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks Landan Seguin A. Ndirango Neeli Mishra SueYeon Chung Tyler Lee OOD 25 2 0 26 Aug 2021
Certifiers Make Neural Networks Vulnerable to Availability Attacks Tobias Lorenz M. Kwiatkowska Mario Fritz AAML SILM 12 2 0 25 Aug 2021
Adversarially Robust One-class Novelty Detection Shao-Yuan Lo Poojan Oza Vishal M. Patel AAML 25 29 0 25 Aug 2021
Bridged Adversarial Training Hoki Kim Woojin Lee Sungyoon Lee Jaewook Lee AAML GAN 16 9 0 25 Aug 2021
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier Chong Xiang Saeed Mahloujifar Prateek Mittal VLM AAML 24 73 0 20 Aug 2021