Is this project an undergraduate, graduate, or faculty project?
Graduate
Project Type
individual
Campus
Daytona Beach
Authors' Class Standing
Paulo Carreon, Graduate student
Lead Presenter's Name
Paulo Carreon
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Dr. Hongyun Chen
Abstract
Quantitative Assessment of Cybersecurity Risk Variability Across Transportation Modes examines how cybersecurity risks differ across major transportation sectors and addresses the lack of a structured, cross modal analysis in existing transportation cybersecurity research. As transportation systems increasingly rely on digital infrastructure, communication networks, operational technologies, and interconnected platforms, they become more exposed to cyber threats that can affect safety, mobility, operations, and public trust. Despite the growing importance of this issue, there is still limited research that quantitatively compares how cyber risks vary across transportation modes such as road and intelligent transportation systems, aviation, rail and transit, and maritime systems. The purpose of this project is to identify and evaluate the variability of cybersecurity risk across transportation modes using a structured incident based dataset and quantitative analysis methods. To accomplish this, a cleaned and standardized transportation cybersecurity dataset was developed from documented cyber incidents and coded using consistent variables related to targeted systems, subsystem exposure, vulnerabilities, threat types, detection timing, severity, duration, cost impact, success level, and operational consequences. Statistical analysis and chart based comparisons were then used to examine patterns, differences, and trends across transportation sectors. Preliminary and final results indicate that cybersecurity risk is not evenly distributed across transportation modes, with certain sectors showing higher concentrations of severe vulnerabilities, stronger threat exposure, and greater operational consequences than others. These findings help demonstrate that transportation cybersecurity should not be treated as a uniform issue, but rather as a mode specific risk management challenge requiring targeted strategies for resilience, planning, and workforce development. This work contributes to the field by offering a quantitative framework for comparing cybersecurity risk across transportation systems and provides a foundation for future research, policy development, and cybersecurity informed transportation engineering practice.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Quantitative Assessment of Cybersecurity Risk Variability Across Transportation Modes
Quantitative Assessment of Cybersecurity Risk Variability Across Transportation Modes examines how cybersecurity risks differ across major transportation sectors and addresses the lack of a structured, cross modal analysis in existing transportation cybersecurity research. As transportation systems increasingly rely on digital infrastructure, communication networks, operational technologies, and interconnected platforms, they become more exposed to cyber threats that can affect safety, mobility, operations, and public trust. Despite the growing importance of this issue, there is still limited research that quantitatively compares how cyber risks vary across transportation modes such as road and intelligent transportation systems, aviation, rail and transit, and maritime systems. The purpose of this project is to identify and evaluate the variability of cybersecurity risk across transportation modes using a structured incident based dataset and quantitative analysis methods. To accomplish this, a cleaned and standardized transportation cybersecurity dataset was developed from documented cyber incidents and coded using consistent variables related to targeted systems, subsystem exposure, vulnerabilities, threat types, detection timing, severity, duration, cost impact, success level, and operational consequences. Statistical analysis and chart based comparisons were then used to examine patterns, differences, and trends across transportation sectors. Preliminary and final results indicate that cybersecurity risk is not evenly distributed across transportation modes, with certain sectors showing higher concentrations of severe vulnerabilities, stronger threat exposure, and greater operational consequences than others. These findings help demonstrate that transportation cybersecurity should not be treated as a uniform issue, but rather as a mode specific risk management challenge requiring targeted strategies for resilience, planning, and workforce development. This work contributes to the field by offering a quantitative framework for comparing cybersecurity risk across transportation systems and provides a foundation for future research, policy development, and cybersecurity informed transportation engineering practice.