Doctoral Dissertations

Abstract

"Cyber-physical systems link cyber infrastructure with physical processes through an integrated network of physical components, sensors, actuators, and computers that are interconnected by communication links. Modern critical infrastructures such as smart grids, intelligent water distribution networks, and intelligent transportation systems are prominent examples of cyber-physical systems. Developed countries are entirely reliant on these critical infrastructures, hence the need for rigorous assessment of the trustworthiness of these systems. The objective of this research is quantitative modeling of dependability attributes -- including reliability and survivability -- of cyber-physical systems, with domain-specific case studies on smart grids and intelligent water distribution networks. To this end, we make the following research contributions: i) quantifying, in terms of loss of reliability and survivability, the effect of introducing computing and communication technologies; and ii) identifying and quantifying interdependencies in cyber-physical systems and investigating their effect on fault propagation paths and degradation of dependability attributes.

Our proposed approach relies on observation of system behavior in response to disruptive events. We utilize a Markovian technique to formalize a unified reliability model. For survivability evaluation, we capture temporal changes to a service index chosen to represent the extent of functionality retained. In modeling of interdependency, we apply correlation and causation analyses to identify links and use graph-theoretical metrics for quantifying them. The metrics and models we propose can be instrumental in guiding investments in fortification of and failure mitigation for critical infrastructures. To verify the success of our proposed approach in meeting these goals, we introduce a failure prediction tool capable of identifying system components that are prone to failure as a result of a specific disruptive event. Our prediction tool can enable timely preventative actions and mitigate the consequences of accidental failures and malicious attacks"--Abstract, page iii.

Advisor(s)

Sedigh, Sahra
Hurson, A. R.

Committee Member(s)

Choi, Minsu
Stanley, R. Joe
Zawodniok, Maciej Jan, 1975-

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Computer Engineering

Sponsor(s)

United States. Department of Transportation
United States. Department of Education
National Science Foundation (U.S.)
Missouri University of Science and Technology. Intelligent Systems Center
Missouri University of Science and Technology. Center for Infrastructure Engineering Studies

Comments

This work was supported in part by the US Departments of Transportation and Education, the National Science Foundation, the Missouri S&T Intelligent Systems Center, and the Center for Infrastructure Engineering Studies.

Research Center/Lab(s)

Intelligent Systems Center

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2017

Pagination

xiii, 108 pages

Note about bibliography

Includes bibliographic references (pages 100-107).

Rights

© 2017 Koosha Marashi, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11576

Electronic OCLC #

1105575701

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