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Adversarial classification
Nilesh Dalvi, Pedro Domingos, Sumit Sanghai, Deepak Verma, et al · 2004
Earlier work this paper cites.
Evasion attacks against machine learning at test time
Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Šrndić, Pavel Laskov, Giorgio Giacinto, and Fabio Roli · 2013
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Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Imagenet large scale visual recognition challenge
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Intriguing properties of neural networks
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2016

Kurakin, Alexey, Goodfellow, Ian, Bengio, Samy

Adversarial examples are malicious inputs designed to fool machine learning models.

They often transfer from one model to another, allowing attackers to mount black box attacks without knowledge of the target model's parameters.
Adversarial training is the process of explicitly training a model on adversarial examples, in order to make it more robust to attack or to reduce its test error on clean inputs.
So far, adversarial training has primarily been applied to small problems.

Adversarial classification
Nilesh Dalvi, Pedro Domingos, Sumit Sanghai, Deepak Verma, et al · 2004
Earlier work this paper cites.
Evasion attacks against machine learning at test time
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Earlier work this paper cites.
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