by Yee Wei Law - Saturday, 18 November 2023, 4:31 PM
Adversarial machine learning (AML) as a field can be traced back to [HJN+11].
The impact of adversarial examples on deep learning is well known within the computer vision community, and documented in a body of literature that has been growing exponentially since Szegedy et al.’s discovery [SZS+14].
The field is moving so fast that the taxonomy, terminology and threat models are still being standardised.
L. Huang, A. D. Joseph, B. Nelson, B. I. Rubinstein, and J. D. Tygar, Adversarial machine learning, in Proceedings of the 4th ACM Workshop on Security and Artificial
Intelligence, AISec ’11, Association for Computing Machinery, New York, NY, USA, 2011, p. 43 – 58. https://doi.org/10.1145/2046684.2046692.
[SZS+14]
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus, Intriguing properties of neural networks, in International Conference on Learning
Representations, 2014. Available at https://research.google/pubs/pub42503/.