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The intriguing phenomenon of adversarial examples has attracted significant attention in machine learning and what might be more surprising to the community is the existence of universal adversarial perturbations (UAPs), i.e.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Robustness of classifiers: from adversarial to random noise
Alhussein Fawzi, Seyed-Mohsen Moosavi-Dezfooli, and Pascal Frossard · 2016
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Deepfool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard · 2016
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Towards evaluating the robustness of neural networks
Nicholas Carlini and David Wagner · 2017
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Universal adversarial perturbations against semantic image segmentation
Jan Hendrik Metzen, Mummadi Chaithanya Kumar, Thomas Brox, and Volker Fischer · 2017
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Adversarial machine learning at scale
Alexey Kurakin, Ian Goodfellow, and Samy Bengio · 2017
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Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard · 2017
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Analysis of universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, Pascal Frossard, and Stefano Soatto · 2017
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Fast feature fool: A data independent approach to universal adversarial perturbations
Konda Reddy Mopuri, Utsav Garg, and R. Venkatesh Babu · 2017
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Threat of adversarial attacks on deep learning in computer vision: A survey
Naveed Akhtar and Ajmal Mian · 2018
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Defense against universal adversarial perturbations
Naveed Akhtar, Jian Liu, and Ajmal Mian · 2018
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Learning universal adversarial perturbations with generative models
Jamie Hayes and George Danezis · 2018
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With friends like these, who needs adversaries?
Saumya Jetley, Nicholas Lord, and Philip Torr · 2018
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Art of singular vectors and universal adversarial perturbations
Valentin Khrulkov and Ivan Oseledets · 2018
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Adversarial perturbations against real-time video classification systems
Shasha Li, Ajaya Neupane, Sujoy Paul, Chengyu Song, Srikanth V Krishnamurthy, Amit K Roy Chowdhury, and Ananthram Swami · 2018
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
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Generalizable data-free objective for crafting universal adversarial perturbations
Konda Reddy Mopuri, Aditya Ganeshan, and Venkatesh Babu Radhakrishnan · 2018
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Nag: Network for adversary generation
Konda Reddy Mopuri, Utkarsh Ojha, Utsav Garg, and R. Venkatesh Babu · 2018
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Ask, acquire, and attack: Data-free uap generation using class impressions
Konda Reddy Mopuri, Phani Krishna Uppala, and R. Venkatesh Babu · 2018
Cited alongside, same era.
Playing the game of universal adversarial perturbations
Julien Perolat, Mateusz Malinowski, Bilal Piot, and Olivier Pietquin · 2018
Cited alongside, same era.
Generative adversarial perturbations
Omid Poursaeed, Isay Katsman, Bicheng Gao, and Serge Belongie · 2018
Cited alongside, same era.
Adversarially robust generalization requires more data
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, and Aleksander Madry · 2018
Cited alongside, same era.
Universal adversarial attacks on text classifiers
Melika Behjati, Seyed-Mohsen Moosavi-Dezfooli, Mahdieh Soleymani Baghshah, and Pascal Frossard · 2019
Cited alongside, same era.
Universal adversarial triggers for attacking and analyzing nlp
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh · 2019
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You only propagate once: Accelerating adversarial training via maximal principle
Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, and Bin Dong · 2019
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Double targeted universal adversarial perturbations
Philipp Benz, Chaoning Zhang, Tooba Imtiaz, and In So Kweon · 2020
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Defending against universal attacks through selective feature regeneration
Tejas Borkar, Felix Heide, and Lina Karam · 2020
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Transferable universal adversarial perturbations using generative models
Atiye Sadat Hashemi, Andreas Bär, Saeed Mozaffari, and Tim Fingscheidt · 2020
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Zhikai Chen, Lingxi Xie, Shanmin Pang, Yong He, and Qi Tian · 2019
Cited alongside, same era.
Jiazhu Dai and Le Shu · 2019
Cited alongside, same era.
Universal adversarial perturbation for text classification
Hang Gao and Tim Oates · 2019
Cited alongside, same era.
A method for computing class-wise universal adversarial perturbations
Tejus Gupta, Abhishek Sinha, Nupur Kumari, Mayank Singh, and Balaji Krishnamurthy · 2019
Cited alongside, same era.
Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry · 2019
Cited alongside, same era.
Universal perturbation attack against image retrieval
Jie Li, Rongrong Ji, Hong Liu, Xiaopeng Hong, Yue Gao, and Qi Tian · 2019
Cited alongside, same era.
Universal adversarial perturbation via prior driven uncertainty approximation
Hong Liu, Rongrong Ji, Jie Li, Baochang Zhang, Yue Gao, Yongjian Wu, and Feiyue Huang · 2019
Cited alongside, same era.
Universal adversarial perturbations generative network for speaker recognition
Jiguo Li, Xinfeng Zhang, Chuanmin Jia, Jizheng Xu, Li Zhang, Yue Wang, Siwei Ma, and Wen Gao · 2020
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Regional homogeneity: Towards learning transferable universal adversarial perturbations against defenses
Yingwei Li, Song Bai, Cihang Xie, Zhenyu Liao, Xiaohui Shen, and Alan L Yuille · 2020
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Universal adversarial training
Ali Shafahi, Mahyar Najibi, Zheng Xu, John P Dickerson, Larry S Davis, and Tom Goldstein · 2020
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Universal adversarial attacks with natural triggers for text classification
Liwei Song, Xinwei Yu, Hsuan-Tung Peng, and Karthik Narasimhan · 2020
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Fast is better than free: Revisiting adversarial training
Eric Wong, Leslie Rice, and J Zico Kolter · 2020
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Decision-based universal adversarial attack
Jing Wu, Mingyi Zhou, Shuaicheng Liu, Yipeng Liu, and Ce Zhu · 2020
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Enabling fast and universal audio adversarial attack using generative model
Yi Xie, Zhuohang Li, Cong Shi, Jian Liu, Yingying Chen, and Bo Yuan · 2020
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Real-time, universal, and robust adversarial attacks against speaker recognition systems
Yi Xie, Cong Shi, Zhuohang Li, Jian Liu, Yingying Chen, and Bo Yuan · 2020
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Cd-uap: Class discriminative universal adversarial perturbation
Chaoning Zhang, Philipp Benz, Tooba Imtiaz, and In-So Kweon · 2020
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Understanding adversarial examples from the mutual influence of images and perturbations
Chaoning Zhang, Philipp Benz, Tooba Imtiaz, and In-So Kweon · 2020
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Udh: Universal deep hiding for steganography, watermarking, and light field messaging
Chaoning Zhang, Philipp Benz, Adil Karjauv, Geng Sun, and In Kweon · 2020
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Universal adversarial training with class-wise perturbations
Philipp Benz, Chaoning Zhang, Adil Karjauv, and In So Kweon · 2021
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Towards data-free universal adversarial perturbations with artificial images
Chaoning Zhang, Philipp Benz, Adil Karjauv, Jae Won Cho, and In So Kweon · 2021
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Universal adversarial perturbations through the lens of deep steganography: Towards a fourier perspective
Chaoning Zhang, Philipp Benz, Adil Karjauv, and In So Kweon · 2021
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