A high-speed simulation and cybersecurity regression testing platform for industrial control systems
Date of Award
2023
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Electrical and Computer Engineering
Committee Chair
Tommy Morris
Committee Member
David Coe
Committee Member
Rhonda Gaede
Committee Member
Avimanyu Sahoo
Committee Member
Leon Jololian
Subject(s)
Computer security--Software, Computer security--Industrial applications
Abstract
Modeling and simulation techniques are used extensively in both industry and science. Individual parts of larger systems are typically modeled and simulated using different techniques and tools making it difficult to study the more extensively coupled heterogeneous system. In order to show the vulnerabilities of a physical system to cybersecurity risks, the complex interdependence between the cyber and physical systems must be modeled. This paper discusses the development of a high-speed high-fidelity Supervisory Control and Data Acquisition (SCADA) simulation platform that 1) enables regression testing of both cybersecurity applications and other SCADA applications and 2) enables the creation of data lakes. The framework can run simulations up to 300x faster than real-time. Additionally, a cybersecurity regression testing suite was developed based on real world observations of attacks against industrial control systems. The coupling of the regression testing suite with the high-speed simulation framework allows for extensive evaluation of systems security posture and the collection of data while a system is both operating normally and under cyber attack.
Recommended Citation
Wright, Shelton, "A high-speed simulation and cybersecurity regression testing platform for industrial control systems" (2023). Dissertations. 351.
https://louis.uah.edu/uah-dissertations/351