A Quantitative Research Study on Probability Risk Assessments in Critical Infrastructure and Homeland Security
Helms School of Government
Doctor of Philosophy in Criminal Justice (PhD)
homeland security, critical infrastructure, probabilistic safety assessment (PSA), T-H-O-risks, domino effect, social network analysis (SNA), failure mode effect, and criticality analysis (FMECA)
Lee, Alfred B., "A Quantitative Research Study on Probability Risk Assessments in Critical Infrastructure and Homeland Security" (2022). Doctoral Dissertations and Projects. 3865.
This dissertation encompassed quantitative research on probabilistic risk assessment (PRA) elements in homeland security and the impact on critical infrastructure and key resources. There are 16 crucial infrastructure sectors in homeland security that represent assets, system networks, virtual and physical environments, roads and bridges, transportation, and air travel. The design included the Bayes theorem, a process used in PRAs when determining potential or probable events, causes, outcomes, and risks. The goal is to mitigate the effects of domestic terrorism and natural and man-made disasters, respond to events related to critical infrastructure that can impact the United States, and help protect and secure natural gas pipelines and electrical grid systems. This study provides data from current risk assessment trends in PRAs that can be applied and designed in elements of homeland security and the criminal justice system to help protect critical infrastructures. The dissertation will highlight the aspects of the U.S. Department of Homeland Security National Infrastructure Protection Plan (NIPP). In addition, this framework was employed to examine the criminal justice triangle, explore crime problems and emergency preparedness solutions to protect critical infrastructures, and analyze data relevant to risk assessment procedures for each critical infrastructure identified. Finally, the study addressed the drivers and gaps in research related to protecting and securing natural gas pipelines and electrical grid systems.