Machine Learning in Cybersecurity

Catalog description

This doctoral course explores machine learning models and algorithms for today's business world and in cybersecurity in particular. The course focuses on both understanding the theory of machine learning approaches, and their reliance on trustworthy and unbiased data. Doctoral students will be expected to research the emerging role of machine learning and artificial intelligence in cybersecurity, predict its impact in cybersecurity globally, and develop an application. Topics include supervised, unsupervised, and deep learning, fundamental algorithms such as linear regression, decision tree learning, classification and support vector machines, and researching applications for these techniques. Students research and discuss how machine learning and natural language processing (NLP) are used in cybersecurity, both for attack by adversaries and defense by government and industry. Students must achieve a minimum grade of B-.