Doctoral Dissertations
Keywords and Phrases
Cyber-Physical Systems; Drones; Flocking; Security; Smart Grid
Abstract
"Cyber-Physical Systems (CPS) are increasingly targeted by attackers using a wide and evolving array of methods. When these systems are distributed, every node represents a potential vulnerability, and secure system design must take this into account. Distributed CPSs also have the potential to better detect and handle attacks, by leveraging redundancies of physical measurements between adjacent nodes. The main purpose of this research is to determine the conditions that render a distributed CPS more resistant to attacks, and the conditions that render it more vulnerable. The work is centered around two separate applications: The Smart Grid and Autonomous Drone Swarms. In the first application power theft in the Smart Grid is studied and the difficulty of identifying small persistent attacks between semi-trusted nodes is established. A general approach to handling persistent economic attacks is proposed and analyzed. The second application intrusion of non-compliant drones into a system of flocking drones is considered. An approach to detecting intrusions is proposed and tested in simulations. In both applications the residual sum metric is proposed as a basis for detection"--Abstract, p. iii
Advisor(s)
McMillin, Bruce M.
Committee Member(s)
Cen, Nan
Kimball, Jonathan W.
Luo, Tony T.
Nadendla, V. Sriram Siddhardh
Department(s)
Computer Science
Degree Name
Ph. D. in Computer Science
Publisher
Missouri University of Science and Technology
Publication Date
Fall 2022
Pagination
ix, 61 pages
Note about bibliography
Includes_bibliographical_references_(pages 59-60)
Rights
© 2022 Simon Bech Thougaard, All Rights Reserved
Document Type
Dissertation - Open Access
File Type
text
Language
English
Thesis Number
T 12206
Recommended Citation
Thougaard, Simon Bech, "Persistent Stealthy Attacks and their Detection in Large Distributed Cyber-Physical Systems" (2022). Doctoral Dissertations. 3226.
https://scholarsmine.mst.edu/doctoral_dissertations/3226