Course Modules

The project plans to initially develop six self-contained and adaptive modules as shown in figure below, including (1) Cyber Threat Intelligence (CTI) and malware attack stages, (2) Malware knowledge representation and CTI sharing, (3) Malware data collection and feature identification, (4) AI assisted malware detection, (5) Malware classification and attribution, (6) Advanced malware research topic and case studies. Here, each module consists of multiple lectures and lab sessions, and will have all the pre- requisite information to be used independently. Detailed module descriptions are available in the instructor files. 

Before enrolling in a course that teaches the proposed modules, students should have understanding of following pre-requisites concepts - 

• Introduction to Machine Learning/Artificial Intelligence - Students are supposed to have taken an undergraduate introduction to machine learning/artificial intelligence, generally taught to computer science majors at various universities. 

• Introduction to Cybersecurity - The proposed modules expect students to have basic cybersecurity foundations, which are completed in three foundational knowledge units (Cybersecurity Foundations, Cybersecurity Principles, IT Systems Components) as discussed in the NSA/DHS CAE-CDE designation requirements.

*Please request access via email at our Contacts page for marked instructor files.