Date of Graduation
12-2021
Document Type
Thesis
Degree Name
Master of Science in Computer Science (MS)
Degree Level
Graduate
Department
Computer Science & Computer Engineering
Advisor/Mentor
Panda, Brajendra N.
Committee Member
Thompson, Dale R.
Second Committee Member
Gauch, John M.
Keywords
Critical Infrastructure Systems; Damage Source Identification; Digital Twins
Abstract
Cyber-Physical Systems (CPS) are becoming increasingly prevalent for both Critical Infrastructure and the Industry 4.0 initiative. Bad values within components of the software portion of CPS, or the computer systems, have the potential to cause major damage if left unchecked, and so detection and locating of where these occur is vital. We further define features of these computer systems and create a use-based system topology. We then introduce a function to monitor system integrity and the presence of bad values as well as an algorithm to locate them. We then show an improved version, taking advantage of several system properties to increase efficiency. We additionally delve into the use of digital twins for simulating potential bad values faster-than-real-time. Finally, we show evidence of our non-digital twin model’s effectiveness through simulation.
Citation
Davis, N. (2021). Component Damage Source Identification for Critical Infrastructure Systems. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/4265
Included in
Graphics and Human Computer Interfaces Commons, Numerical Analysis and Scientific Computing Commons, Systems Architecture Commons, Theory and Algorithms Commons
