Teaching Adversarial Machine Learning: Educating the Next Generation of Technical and Security Professionals

Abstract

The growth in machine learning has created an opportunity to expand education to include the study of "adversarial" machine learning, specifically in undergraduate and graduate courses for cybersecurity professionals and machine learning experts. This paper presents tools available in teaching these concepts. This information also helps system designers reduce design flaws, as well as design against malicious attacks. This paper recommends using these tools to improve offensive cyber security practices that may harden machine learning systems. These tools include newly developed machine learning libraries that make this approach a practical alternative.