The Feasibility of Deep Learning Use for Adversarial Model Extraction in the Cybersecurity Domain

Michal Choras, Marek Pawlicki, Rafal Kozik. The Feasibility of Deep Learning Use for Adversarial Model Extraction in the Cybersecurity Domain. In Hujun Yin, David Camacho, Peter Tiño, Antonio J. Tallón-Ballesteros, Ronaldo Menezes, Richard Allmendinger, editors, Intelligent Data Engineering and Automated Learning - IDEAL 2019 - 20th International Conference, Manchester, UK, November 14-16, 2019, Proceedings, Part II. Volume 11872 of Lecture Notes in Computer Science, pages 353-360, Springer, 2019. [doi]

Abstract

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