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Black-box attack methods aim to infer suitable attack patterns to targeted DNN models by only using output feedback of the models and the corresponding input queries.
The mnist database of handwritten digits
Yann LeCun · 1998
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Stochastic first-and zeroth-order methods for nonconvex stochastic programming
Saeed Ghadimi and Guanghui Lan · 2013
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Accelerating stochastic gradient descent using predictive variance reduction
Rie Johnson and Tong Zhang · 2013
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Introductory lectures on convex optimization: A basic course , volume 87
Yurii Nesterov · 2013
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2014
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Explaining and harnessing adversarial examples
Ian Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Introduction to online convex optimization
Elad Hazan et al · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 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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Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models
Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, and Cho-Jui Hsieh · 2017
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Transferability of adversarial attacks in model-agnostic meta-learning
Riley Edmunds, Noah Golmant, Vinay Ramasesh, Phillip Kuznetsov, Piyush Patil, and Raul Puri · 2017
Practical black-box attacks against machine learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z Berkay Celik, and Ananthram Swami · 2017
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Decision-based adversarial attacks: Reliable attacks against black-box machine learning models
W. Brendel, J. Rauber, and M. Bethge · 2018
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A frank-wolfe framework for efficient and effective adversarial attacks
Jinghui Chen, Jinfeng Yi, and Quanquan Gu · 2018
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Black-box adversarial attacks with limited queries and information
Andrew Ilyas, Logan Engstrom, Anish Athalye, and Jessy Lin · 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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Cited alongside, same era.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Cited alongside, same era.
Simple black-box adversarial attacks on deep neural networks
Nina Narodytska and Shiva Kasiviswanathan · 2017
Cited alongside, same era.
Random gradient-free minimization of convex functions
Yurii Nesterov and Vladimir Spokoiny · 2017
Cited alongside, same era.
Prior convictions: Black-box adversarial attacks with bandits and priors
Andrew Ilyas, Logan Engstrom, and Aleksander Madry
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On first-order meta-learning algorithms
Alex Nichol, Joshua Achiam, and John Schulman · 2018
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Query-efficient hard-label black-box attack: An optimization-based approach
Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, JinFeng Yi, and Cho-Jui Hsieh · 2019
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Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks
Chun-Chen Tu, Paishun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, and Shin-Ming Cheng · 2019
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Adversarial attacks on graph neural networks via meta learning
Daniel Zügner and Stephan Günnemann · 2019
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