The M.S. program consist of six eight-week terms. Students enroll in four courses (12 credits) each semester, which is the equivalent of two courses each term. A total of 30 credit hours including two components: Advanced Engineering Core (24 semester hours) and Graduate Level Math Electives (6 semester hours).
Term – Dynamic A
Advanced Malware Reverse Engineering – Expose the student to various techniques and procedures employed in the practice of software analysis to detect and remove affected code. The areas explored will consist of trends in malicious code growth, common attack vectors, surface analysis of malware, run-time analysis of malware, system monitoring, debuggers, static reverse engineering of malware, and disassemblers to identify obfuscation techniques and Anti-reversing methods.
Social, Economic, and Policy Aspects of Cybersecurity
Term – Dynamic B
Advanced Digital Forensics – This course provides students with the advanced skills to track and counter a wide range of sophisticated threats including espionage, hacktivism, financial crime syndication, and APT groups. To understand advanced digital forensics engineering techniques, how to provide response to incidents occurring in enterprises and perform timeline analysis, memory forensics and intrusion forensics.
Network Security – Network security requirements, Number Theory, steganography, encryption design principles and algorithms, message authentication and digital signature principles and designs, and network system security design.
Term – Dynamic A
Introduction to Smart Grid and its Applications – This is multi-disciplinary course involving students and faculty from various disciplines such as computer and communication networks, power systems, controls, security and privacy, environmental sustainability, and economics.
Power Systems Economics and Markets – Introducing restructured electricity supply industry, discuss the concepts from microeconomics that are essential for the understanding of electricity markets, analyze the operation of power systems in a competitive environment. Students will be able to have solid understanding of the basics and help them develop innovative solutions to problems that vary in subtle ways from country to country, from market to market and from company to company.
Term – Dynamic B
Random Signal Principles – Noise, random processes, correlation, spectral analysis in the analysis and design of communication systems. Optimization techniques; minimum mean square error.
Cyberphysical Systems Security – The course covers introductory topics in cyber-physical systems security. The goal is to expose students to fundamental security primitives specific to cyber-physical systems and to apply them to a broad range of current and future security challenges. Much of the course is taught with the focus on one instance of cyber-physical systems (CPS)- Industrial control systems. However, students will be expected to generalize the concepts for other CPS.
Smart Grid Cyber Security and Intelligent Electronic Devices – Design, simulate and solve smart grid cyber security issues. Manmade and natural large scale disturbances. Smart grid cyber networked standards and new Intelligent Electronic Devices (IED). Prerequisite: Graduate standing.