Adversarial and Clean Data Are Not Twins

Multi-column deep neural network for traffic sign classification

CireşAn, Dan, Meier, Ueli, Masci, Jonathan, and Schmidhuber, Jürgen · 2012

Earlier work this paper cites.

Intriguing properties of neural networks

Original

Szegedy, Christian, Zaremba, Wojciech, Sutskever, Ilya, Bruna, Joan, Erhan, Dumitru, Goodfellow, Ian J., and Fergus, Rob · 2013

Earlier work this paper cites.

Explaining and Harnessing Adversarial Examples

Goodfellow, I. J., Shlens, J., and Szegedy, C · 2014

Earlier work this paper cites.

Deep neural networks are easily fooled: High confidence predictions for unrecognizable images

Original

Nguyen, Anh Mai, Yosinski, Jason, and Clune, Jeff · 2014

Earlier work this paper cites.

Learning with a strong adversary

Original

Huang, Ruitong, Xu, Bing, Schuurmans, Dale, and Szepesvári, Csaba · 2015

Cited alongside, same era.

Adversarial Examples in the Physical world

Kurakin, A., Goodfellow, I., and Bengio, S · 2016

Cited alongside, same era.

Adversarial machine learning at scale

Original

Kurakin, Alexey, Goodfellow, Ian J., and Bengio, Samy · 2016

Cited alongside, same era.

Transferability in Machine Learning: From Phenomena To Black-Box Attacks Using Adversarial Samples

Papernot, N., McDaniel, P., and Goodfellow, I · 2016

Cited alongside, same era.

The limitations of deep learning in adversarial settings

Original

Papernot, Nicolas, McDaniel, Patrick, Jha, Somesh, Fredrikson, Matt, Celik, Z. Berkay, and Swami, Ananthram

Cited in the paper.

Distillation as a defense to adversarial perturbations against deep neural networks

Original

Papernot, Nicolas, McDaniel, Patrick Drew, Wu, Xi, Jha, Somesh, and Swami, Ananthram

Cited in the paper.

Learning a driving simulator

Original

Santana, Eder and Hotz, George · 2016

Later among the works it cites.

Adversarial Perturbations of Deep Neural Networks

Warde-Farley, D and Goodfellow, I · 2016

Later among the works it cites.

Dermatologist-level classification of skin cancer with deep neural networks

Esteva, Andre, Kuprel, Brett, Novoa, Roberto A., Ko, Justin, Swetter, Susan M., Blau, Helen M., and Thrun, Sebastian · 2017

Closest in time.