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  Program Learning Outcomes

  Upon completion of the MS in Vehicle Cyber Engineering program, graduates will be able to: 

  1. Identify, formulate, and solve electrical engineering problems in vehicular systems that involve automotive communication busses, Electronic Control Units (ECUs), and sensor/human interface technologies.
  2. Perform risk assessment and threat analysis to vehicular cyber systems.
  3. Develop cybersecurity solutions for embedded vehicle systems and distributed intra-vehicle networks.
  4. Identify, formulate, and solve cybersecurity problems in the areas of vehicular networks, artificial intelligence, and supply chain.
  5. Design comprehensive cybersecurity solutions for integrated vehicular systems or subsystems that span over multiple attack vectors.
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  Admission Requirements

  Typical minimum requirements include an undergraduate GPA of at least 3.0 (or equivalent) and a bachelor's degree from an accredited university in Electrical Engineering, Robotics Engineering, Engineering (with a relevant focus), Computer Science, or a closely related discipline.  Applicants with cyber experience but who need additional technical knowledge to be successful in the master's-level courses, will be required to complete prerequisite courses or modules as part of a conditional admission.  These prerequisites will not advance a student toward his/her degree. Each applicant must also be approved by the department director/chair and the College of Engineering & Science dean's office.

  Although the Graduate Record Exam (GRE) is not required, a strong score on the GRE will strengthen the application.

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  Master of Science in Vehicle Cyber Engineering Requirements (30 credits)

  Students must maintain a GPA of at least 3.0 both overall and in the program. Grades below "C" will not advance the student towards graduation. Students with the Vehicle Cyber Engineering Graduate Certificate may apply all the courses toward this master's degree.

  Required Courses (30 credit hours)

  • CSSE 5545 Advanced Computer Security (3 credits)
  • CSSE 5760 Network Security (3 credits)
  • CSSE 5120 Intro to Data Science or ELEE 5750 Deep Learning or other approved technical elective (3 credits)
  • CYBE 5580 System Forensics or ELEE 5350 Machine Learning or VCE 5350 Applied Machine Learning (3 credits)
  • ELEE 5150 Secure Wireless Vehicular Networks (3 credits)
  • VCE 5110 Introduction to Cybersecurity (3 credits)
  • VCE 5400 Secure Vehicle Embedded Systems (3 credits)
  • VCE 5500 Secure Vehicle Electronics or ELEE 5500 Automotive Electronics (3 credits)
  • VCE 5530 Vehicular Hardware Security (3 credits)
  • VCE 5600 Capstone Design for Cyber Vehicle Engineering (3 credits)