Efficient Defenses Against Adversarial Attacks-Reference-Cited by-同舟云学术

Efficient Defenses Against Adversarial Attacks

Published:2017-11-03 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security
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Author:

Zantedeschi Valentina¹,Nicolae Maria-Irina²,Rawat Ambrish²

Affiliation:

1. Univ Lyon, UJM-Saint-Etienne, CNRS, Saint-Etienne, France & IBM Research Ireland, Dublin, Ireland

2. IBM Research Ireland, Dublin, Ireland

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3128572.3140449

Reference42 articles.

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2. Battista Biggio Igino Corona Davide Maiorca Blaine Nelson Nedim Šrndić Pavel Laskov Giorgio Giacinto and Fabio Roli. 2013. Evasion attacks against machine learning at test time Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer 387--402. Battista Biggio Igino Corona Davide Maiorca Blaine Nelson Nedim Šrndić Pavel Laskov Giorgio Giacinto and Fabio Roli. 2013. Evasion attacks against machine learning at test time Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer 387--402.

3. Battista Biggio Giorgio Fumera and Fabio Roli. 2014. Security Evaluation of Pattern Classifiers Under Attack. Vol. 26 (2014) 984--996. https://www.researchgate.net/publication/240383291_Security_Evaluation_of_Pattern_Classifiers_Under_Attack. Battista Biggio Giorgio Fumera and Fabio Roli. 2014. Security Evaluation of Pattern Classifiers Under Attack. Vol. 26 (2014) 984--996. https://www.researchgate.net/publication/240383291_Security_Evaluation_of_Pattern_Classifiers_Under_Attack.

4. Nicholas Carlini and David Wagner. 2016. Defensive Distillation is Not Robust to Adversarial Examples. CoRR Vol. abs/1607.04311 (2016). http://arxiv.org/abs/1607.04311 Nicholas Carlini and David Wagner. 2016. Defensive Distillation is Not Robust to Adversarial Examples. CoRR Vol. abs/1607.04311 (2016). http://arxiv.org/abs/1607.04311

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