Degree Tracks

Track 1: Trusted Software Engineering (TSE)

Trusted software is the foundation of cybersecurity. The Software Engineering Institute estimates that 90 percent of reported security incidents result from exploits against defects in software design or code. Students in the TSE track learn how to systematically apply scientific and technical knowledge to the design, implementation and testing of software to enable it to withstand attack, to provide security services, and to inspire trust by potential hosts.

Track 2: Critical Infrastructure Protection (CIP)

Advances in smart-grid technology create both improvements and entry points for hackers. Students in the CIP track focus on power grid cybersecurity with a critical mass of courses—industrial control security, network architecture, threat identification, anomaly detection, incident response, forensics, and recovery—that provides students with the knowledge and skills to carry out North America Electric Reliability Corporation (NERC) CIP compliance and industry best practices. 

Track 3: Network Security Management (NSM)

Students in the NSM track learn to develop and manage networks and services to meet computing-resources needs for organizations. Effective network and system management targets a variety of threats in different layers to stop them from entering or spreading on networks. Security teams design the networks, set up appropriate services, ensure resources are available, address performance concerns, study histories, and troubleshoot network and host problems.

Track 4: Artificial Intelligence (AI)

AI and machine learning (ML) are becoming versatile tools in cybersecurity to detect new threats, identify and combat bad bots, and improve both risk identification and intrusion detection. At the same time, AI and ML systems themselves have unique properties that can be the target of an attack such as model theft, model hijacking, data poisoning, and adversarial examples. In the AI track, you will learn the fundamentals of AI and machine learning and their use in cybersecurity. In addition, you will learn about attacks that target ML systems and how to develop countermeasures.

MS Degree Requirements

  • Complete 30 total approved credits
  • You must earn a grade of B or better in all courses

Core Course Requirements: 

  • Satisfy 12 credits of core-course requirements by completing the four courses below:
CS 4471/5471 Computer Security1
EE 4723 Network Security
CS 5001 National Cybersecurity Policy and Law
MA 3203


1Students on the CIP and NSM tracks may substitute SAT 4812 (Cybersecurity II) or EE 5455 (Cybersecurity for Industrial Control Systems) for CS 4471/CS 5471.

Concentration Course Requirements

  • Satisfy 12 credits concentration-course requirements by completing the four courses in your concentration below:
TSE CS 5472 Advanced Topics in Computer Security
TSE CS 4710 Model Driven Software Development
TSE CS 5321 Advanced Algorithms
TSE CS 5740 Development of Trusted Software
CIP EE 5500 Probability and Stochastic Processes
CIP EE 5231 Energy Control Center Applications
CIP EE 5451 Risk Assessment for Critical Infrastructure Protection
CIP EE 6210 Power System Dynamics and Stability
NSM SAT 5520 Machine Learning in Cyber Security
NSM SAT 5111 Security and Privacy
NSM SAT 5283 Information Governance and Risk Management
NSM SAT 5816 Digital Forensics
AI CS 4811 Artificial Intelligence

CS 5831 OR

SAT 5165

Advanced Data Mining

Intro to Big Data Analytics


CS 5841 OR

SAT 5520

Machine Learning

Machine Learning in Cybersecurity

AI CS 5472 Advanced Topics in Computer Security

MS Degree Completion Options