Cybersecurity—MS

Cybersecurity Is a National Priority

Trusted software engineering. Critical infrastructure protection. Network security management. Cybersecurity is a broad field and a national priority. The cybersecurity sector is projected to grow from $75 billion in 2015 to $175 billion by 2020.

The Cybersecurity master’s program at Michigan Tech answers the demand with a collaborative program through the departments of Computer Science, Electrical and Computer Engineering, and the College of Computing. Students develop a unique focus for the careers—and the future—they want to create.


Center of Academic Excellence in Cybersecurity (CAE-C) seal

National Center of Academic Excellence in Cyber Defense (CAE-CD)

Michigan Tech is a National Center of Academic Excellence in Cyber Defense (CAE–CD) designated by the National Security Agency (NSA). The Institute of Computing and Cybersystem's (ICC) Center for Cybersecurity is the CAE cyber center at Michigan Tech.


What Sets Us Apart

  • Michigan Tech’s MS in Cybersecurity curriculum combines both theory and applied research across multiple computing disciplines. Graduates are prepared to succeed as cybersecurity professionals and researchers.
  • The Cybersecurity MS program incorporates academic and industry experience across multiple disciplines, with blended learning in theoretical and applied research. Shared resources and centers create a learning environment with strong research opportunities where students can thrive.
  • Students select one of four degree tracks for focused cybersecurity studies in Trusted Software Engineering, Critical Infrastructure Protection, Network Security Management, or Artificial Intelligence.
  • Students select one of three degree completion options: Thesis, Report, or Coursework.
  • Our faculty research is funded by the National Science Foundation (NSF), Department of Energy (DOE), National Institutes of Health (NIH),  Defense Advanced Research Projects Agency (DARPA), Microsoft, Google, and others. Five faculty members and an alumnus are NSF CAREER Award recipients.
  • Michigan Tech is one of only a few universities in the region that offers a cybersecurity graduate program.

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)

Network Security Managers are among the highest-paid in the cybersecurity field, with an average salary range of $100,215 to $71,433, more in larger organizations. 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 Completion Options