Meet the growing demand for cybersecurity expertise in connected systems.
Program Format
100% Online
3 Total Courses
(9 credits)
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Upcoming Start Information
Start Date
May 11, 2026
App Deadline
April 20, 2026
Secure and Connected Cyber-Physical Systems – Graduate Certificate
The Graduate Certificate in Secure and Connected Cyber-Physical Systems is designed for students interested in modeling, designing and analyzing secure and networked cyber-physical systems (CPS).
This program equips you for cutting-edge cybersecurity roles across government agencies, research institutions and private corporations where expertise in Internet of Things (IoT), cloud systems and embedded technology is increasingly vital. Gain hands-on experience with current security protocols and emerging technologies.
Explore the Courses
Your Choice
Take the certificate as a standalone or as part of your online M.S. in Electrical and Computer Engineering.
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What You’ll Learn
This certificate prepares you to tackle complex challenges in the rapidly growing field of cyber-physical systems security. You’ll learn how to:
- Design and implement secure networked systems
- Analyze vulnerabilities in connected infrastructure
- Model and optimize communication networks
- Develop embedded cyber-physical systems
- Apply cryptography and network security protocols
“Our courses provide flexibility for online learners without compromising depth or engagement. They mirror the on-campus experience while offering the convenience of an online format.”
Vaibhav Srivastava
MSU ECE Associate Professor
Career Opportunities
Graduates of this certificate are prepared for advanced positions in:
- Cybersecurity engineering
- Network systems design
- IoT security architecture
- Government security operations
- Research and development
- Critical infrastructure protection
- Embedded systems security engineering
Explore our careers page to discover more career opportunities.
$99k
Cybersecurity professionals earn an average salary of $99,000 per year.
— Payscale
By applying all 9 credits toward the elective requirement of MSU’s online M.S. in Electrical and Computer Engineering, you create a distinctive professional profile that employers actively seek. This strategic pathway not only saves valuable time and resources, but also positions you as a technical leader with deep cybersecurity expertise and comprehensive engineering knowledge — exactly what organizations need to protect their most critical systems.
Learn More About the Online M.S. in ECE Program
Admission Summary
All it takes is three simple steps:
Step 2: Submit your documents: - Official transcripts from all previous universities
- Three letters of recommendation
- Academic statement (two pages discussing your graduate study plans)
- Personal statement (two pages introducing us to your background and motivation)
Step 3: Pay application fee: - $65 domestic students
- $75 international students
Learn more about our admission journey on the admission page.
Secure and Connected Cyber-Physical Systems Certificate Courses
Major security techniques, including authenticity, confidentiality, message integrity, non-repudiation, and the mechanisms to achieve them. Network security and system security practices, including authentication practice, email security, IP security, web security, and firewalls.
Modeling continuous and discrete dynamics of embedded cyber-physical systems (CPS). Hybrid systems. Composition of state machines. Concurrent models of computation. Design and implementation of CPS including sensors and actuators, embedded processors, Internet of Things (IoT), cloud IoT, multitasking, and scheduling. Analysis and verification of CPS. Emerging topics in CPS. Projects in support of lecture material.
Fundamental theories and protocols for communication networks, with an emphasis on statistical performance modeling of medium access control, data link control, routing, and transport layer protocols. Network analysis and design using optimization techniques and statistical tools including Markov process, queueing theory, and emerging machine learning methodologies such as reinforcement learning. Simulation-based and application-driven, hands-on class projects in support of lecture material.