ECE 5555
Transcript Abbreviation:
Secured Autonomy
Course Description:
The course covers different security measures for safeguarding against cyberattacks, detecting cyberattacks, and mitigating the effects of cyberattacks on autonomous control systems.
Course Levels:
Undergraduate (1000-5000 level)
Graduate (5000-8000 level)
Designation:
Required
Elective
General Education Course:
(N/A)
Cross-Listings:
(N/A)
Credit Hours (Minimum if “Range”selected):
3.00
Max Credit Hours:
(N/A)
Select if Repeatable:
Off
Maximum Repeatable Credits:
(N/A)
Total Completions Allowed:
(N/A)
Allow Multiple Enrollments in Term:
No
Course Length:
14 weeks (autumn or spring)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Distance Learning (100% online)
Prerequisites and Co-requisites:
Prereq: 3050 and 3551; or Grad standing in Engineering, Math, or Statistics.
Electronically Enforced:
No
Exclusions:
(N/A)
Course Goals / Objectives:
Familiarity with deriving mathematical models of typical engineering systems to be controlled
Master various cyberattack detection algorithms that can be launched on autonomous control systems
Be competent in deriving algorithms that defend against cyberattacks in autonomous control systems
Apply knowledge gained in mathematics, statistics, physical sciences, and engineering courses to derive algorithms that defend against cyberattacks in autonomous control systems
Exposure to implementation of secure control algorithms using Simulink or hardware testbeds (e.g., Arduino, Raspberry Pi, or microcontrollers)
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC out-of-class | REC in-class | Weekly LAB out-of-class | Weekly LAB in-class |
|---|---|---|---|---|---|
| Introduction to closed loop control systems, state space model in discrete time, and hierarchical control systems | 7.0 | 0.0 | 0 | 0.0 | 0 |
| Control architecture and challenges in complex autonomous systems | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Review of statistical concepts, mean, covariance, law of large numbers, classification and regression | 7.0 | 0.0 | 0 | 0.0 | 0 |
| Review of vulnerabilities in control systems; passive, active, and proactive measures for security | 4.0 | 0.0 | 0 | 0.0 | 0 |
| Attack detection, signature based anomaly detection, change detection, dynamic watermarking, digital twin technology | 10.0 | 0.0 | 0 | 0.0 | 0 |
| Attack mitigation through active interventions | 9.0 | 0.0 | 0 | 0.0 | 0 |
| Total | 40 | 0 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Homeworks | 40% |
| Project | 40% |
| Midterm | 20% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| No Textbooks and Other Course Materials Entered. | ||
ABET-CAC Criterion 3 Outcomes:
(N/A)
ABET-ETAC Criterion 3 Outcomes:
(N/A)
ABET-EAC Criterion 3 Outcomes:
| Significant contribution (7+ hours) | 1 | an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
| Substantial contribution (3-6 hours) | 6 | an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
| Some contribution (1-2 hours) | 7 | an ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
Embedded Literacies Info: