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Adversarial Machine Learning at Scale

4 November 2016

Papers citing "Adversarial Machine Learning at Scale"

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Title
Towards Understanding Adversarial Robustness of Optical Flow Networks Simon Schrodi Tonmoy Saikia Thomas Brox AAML 97 16 0 30 Mar 2021
Automating Defense Against Adversarial Attacks: Discovery of Vulnerabilities and Application of Multi-INT Imagery to Protect Deployed Models Josh Kalin David Noever Matthew Ciolino Dom Hambrick Gerry V. Dozier AAML 210 1 0 29 Mar 2021
On the Adversarial Robustness of Vision Transformers Rulin Shao Zhouxing Shi Jinfeng Yi Pin-Yu Chen Cho-Jui Hsieh ViT 115 146 0 29 Mar 2021
Enhancing the Transferability of Adversarial Attacks through Variance Tuning Xiaosen Wang Kun He AAML 114 401 0 29 Mar 2021
Recent Advances in Large Margin Learning Yiwen Guo Changshui Zhang AAML AI4CE 121 13 0 25 Mar 2021
Deepfake Forensics via An Adversarial Game Zhi Wang Yiwen Guo W. Zuo AAML 66 36 0 25 Mar 2021
Vulnerability of Appearance-based Gaze Estimation Mingjie Xu Haofei Wang Yunfei Liu Feng Lu AAML 67 2 0 24 Mar 2021
Robust and Accurate Object Detection via Adversarial Learning Xiangning Chen Cihang Xie Mingxing Tan Li Zhang Cho-Jui Hsieh Boqing Gong AAML 72 72 0 23 Mar 2021
Robustness via Cross-Domain Ensembles Teresa Yeo Oğuzhan Fatih Kar Alexander Sax Amir Zamir UQCV OOD 57 25 0 19 Mar 2021
SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition Systems Yuxuan Chen Jiangshan Zhang Xuejing Yuan Shengzhi Zhang Kai Chen Wenyuan Xu Shanqing Guo AAML 78 17 0 19 Mar 2021
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition Yaodong Yu Zitong Yang Yan Sun Jacob Steinhardt Yi-An Ma 74 17 0 17 Mar 2021
Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap? Nathan Inkawhich Kevin J. Liang Jingyang Zhang Huanrui Yang H. Li Yiran Chen AAML 42 5 0 17 Mar 2021
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Jungbeom Lee Eunji Kim Sungroh Yoon 85 229 0 16 Mar 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 100 34 0 15 Mar 2021
BreakingBED -- Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks M. Vemparala Alexander Frickenstein Nael Fasfous Lukas Frickenstein Qi Zhao ... Daniel Ehrhardt Yuankai Wu C. Unger N. S. Nagaraja W. Stechele AAML 35 7 0 14 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 125 449 0 14 Mar 2021
Generating Unrestricted Adversarial Examples via Three Parameters Hanieh Naderi Leili Goli S. Kasaei 88 9 0 13 Mar 2021
Adversarial Machine Learning Security Problems for 6G: mmWave Beam Prediction Use-Case Evren Çatak Ferhat Ozgur Catak A. Moldsvor AAML 51 23 0 12 Mar 2021
Multi-Task Federated Reinforcement Learning with Adversaries Aqeel Anwar A. Raychowdhury AAML FedML 63 21 0 11 Mar 2021
Deep Learning for Android Malware Defenses: a Systematic Literature Review Yue Liu Chakkrit Tantithamthavorn Li Li Yepang Liu AAML 88 81 0 09 Mar 2021
Improving Transformation-based Defenses against Adversarial Examples with First-order Perturbations Haimin Zhang Min Xu AAML 58 0 0 08 Mar 2021
Applying Machine Learning in Self-Adaptive Systems: A Systematic Literature Review Omid Gheibi Danny Weyns Federico Quin AI4CE 27 67 0 06 Mar 2021
A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attacks Yudi Dong Huaxia Wang Yu-dong Yao AAML GAN 31 5 0 03 Mar 2021
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers Colin Paterson Haoze Wu John M. Grese R. Calinescu C. Păsăreanu Clark W. Barrett AAML 77 23 0 02 Mar 2021
A Survey On Universal Adversarial Attack Chaoning Zhang Philipp Benz Chenguo Lin Adil Karjauv Jing Wu In So Kweon AAML 96 93 0 02 Mar 2021
Smoothness Analysis of Adversarial Training Sekitoshi Kanai Masanori Yamada Hiroshi Takahashi Yuki Yamanaka Yasutoshi Ida AAML 106 6 0 02 Mar 2021
Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning Gerardo Ibarra-Vázquez Gustavo Olague Mariana Chan-Ley Cesar Puente C. Soubervielle-Montalvo AAML 40 13 0 01 Mar 2021
Token-Modification Adversarial Attacks for Natural Language Processing: A Survey Tom Roth Yansong Gao A. Abuadbba Surya Nepal Wei Liu AAML 110 12 0 01 Mar 2021
Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective Tianlong Chen Yu Cheng Zhe Gan Jingjing Liu Zhangyang Wang 82 52 0 28 Feb 2021
Effective Universal Unrestricted Adversarial Attacks using a MOE Approach Alina Elena Baia G. D. Bari V. Poggioni AAML 72 8 0 27 Feb 2021
Multiplicative Reweighting for Robust Neural Network Optimization Noga Bar Tomer Koren Raja Giryes OOD NoLa 90 9 0 24 Feb 2021
Adversarial Robustness with Non-uniform Perturbations Ece Naz Erdemir Jeffrey Bickford Luca Melis Sergul Aydore AAML 64 27 0 24 Feb 2021
Non-Singular Adversarial Robustness of Neural Networks Yu-Lin Tsai Chia-Yi Hsu Chia-Mu Yu Pin-Yu Chen AAML OOD 65 5 0 23 Feb 2021
Rethinking Natural Adversarial Examples for Classification Models Xiao-Li Li Jianmin Li Ting Dai Jie Shi Jun Zhu Xiaolin Hu AAML VLM 130 13 0 23 Feb 2021
A PAC-Bayes Analysis of Adversarial Robustness Paul Viallard Guillaume Vidot Amaury Habrard Emilie Morvant AAML 80 15 0 19 Feb 2021
Center Smoothing: Certified Robustness for Networks with Structured Outputs Aounon Kumar Tom Goldstein OOD AAML UQCV 84 19 0 19 Feb 2021
Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks Matthew Ciolino Josh Kalin David Noever AAML 206 2 0 19 Feb 2021
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids Jiangnan Li Yingyuan Yang Jinyuan Stella Sun K. Tomsovic Hairong Qi AAML 127 15 0 17 Feb 2021
Improving Hierarchical Adversarial Robustness of Deep Neural Networks A. Ma Aladin Virmaux Kevin Scaman Juwei Lu AAML 59 5 0 17 Feb 2021
Just Noticeable Difference for Deep Machine Vision Jian Jin Xingxing Zhang Xin Fu Huan Zhang Weisi Lin Jian Lou Yao Zhao VLM 266 31 0 16 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs Soheil Feizi AAML 102 47 0 15 Feb 2021
Perceptually Constrained Adversarial Attacks Muhammad Zaid Hameed András Gyorgy 63 12 0 14 Feb 2021
Adversarial defense for automatic speaker verification by cascaded self-supervised learning models Haibin Wu Xu Li Andy T. Liu Zhiyong Wu Helen Meng Hung-yi Lee AAML 86 41 0 14 Feb 2021
Realizable Universal Adversarial Perturbations for Malware Raphael Labaca-Castro Luis Muñoz-González Feargus Pendlebury Gabi Dreo Rodosek Fabio Pierazzi Lorenzo Cavallaro AAML 70 6 0 12 Feb 2021
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis Fengting Li Xuankai Liu Xiaoli Zhang Qi Li Kun Sun Kang Li AAML 73 13 0 10 Feb 2021
Towards Bridging the gap between Empirical and Certified Robustness against Adversarial Examples Jay Nandy Sudipan Saha Wynne Hsu Mong Li Lee Xiaosu Zhu AAML 87 4 0 09 Feb 2021
Target Training Does Adversarial Training Without Adversarial Samples Blerta Lindqvist AAML 30 0 0 09 Feb 2021
Security and Privacy for Artificial Intelligence: Opportunities and Challenges Ayodeji Oseni Nour Moustafa Helge Janicke Peng Liu Z. Tari A. Vasilakos AAML 67 52 0 09 Feb 2021
Benford's law: what does it say on adversarial images? João G. Zago Fabio L. Baldissera Eric A. Antonelo Rodrigo T. Saad AAML 35 3 0 09 Feb 2021
Adversarially Guided Actor-Critic Yannis Flet-Berliac Johan Ferret Olivier Pietquin Philippe Preux Matthieu Geist 77 73 0 08 Feb 2021