Cybersecurity—MS

Core Courses

4 courses/12 credits

• CS 4471/5471 Computer Security or SAT 5111 Security and Privacy  
• CS 4723 Network Security
• CS 4001/5001 National Cybersecurity Policy and Law
• CS 5350 Modern Cryptography or MA 3203 Introduction to Cryptography

General Courses

Any CS, EE, or SAT 4000 or 5000 level courses.

• EET 4501 Applied Machine Learning
• UN 5550 Introduction to Data Science
• BA 5200 Information Systems Management and Data Analytics
• SAT 5988 Practical Experience in Cybersecurity (up to 6 credits, requires instructor approval)

Specialization Courses

At least 9 credits

• CS 4710 Model Driven Software Development
• CS 5472 Advanced Topics in Computer Security
• CS 4740/5740 Development of Trusted Software
• CS 5751 Dependable and Secure CPS-IoT
• EE 5315 Cyber Security of Automotive Systems I
• EE 5455 Cybersecurity for Industrial Control Systems
• SAT 5283 Information Governance and Risk Management
• SAT 4520/5520 Machine Learning in Cyber Security
• SAT 5816 Digital Forensics
• SAT 5817 Security Penetration Test and Audit

Trusted Software Engineering

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 Software Engineering 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.

• CS 4710 Model Driven Software Development
• CS 4711 Software Processes and Management
• CS 4740/5740 Development of Trusted Software
• CS 5751 Dependable and Secure CPS-IoT
• SAT 5817 Security Penetration Test and Audit

System Security

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. 

• CS 4411 Operating Systems
• CS 4130 Compiler Design and Optimization
• CS 4431 Computer Architecture
• CS 5472 Advanced Topics in Computer Security
• SAT 5816 Digital Forensics

Applied Network Security

Students in the Network Security 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.

• CS 4811 Artifical Intelligence
• CS 5472 Advanced Topics in Computer Security
• CS 5481 Systems Performance Analysis or SAT 5520
• CS 5831 Advanced Data Mining or SAT 5165 Introduction to Big Data Analysis

Artificial Intelligence

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.

• CS 4811 Artificial Intelligence
• CS 5472 Advanced Topics in Computer Security
• CS 5481 Systems Performance Analysis or SAT 5520
• CS 5831 Advanced Data Mining or SAT 5165 Introduction to Big Data Analysis