Date of Award

Spring 5-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Cyber Defense (PhDCD)

First Advisor

Varghese Vaidyan

Second Advisor

Cherie Noteboom

Third Advisor

Cody Welu

Abstract

The integration of Internet of Things (IoT) devices into space information networks introduces unprecedented security challenges, necessitating advanced methods for information systems risk assessments. Some proposed approaches in terrestrial networks, predominantly based on Euclidean distance metrics, often fall short of capturing the nuanced and multidimensional nature of risks and vulnerabilities in the unique context of space environments. This paper proposes a novel risk management methodology that leverages both Euclidean distance metrics and probabilistic Monte Carlo-based models for evaluating the likelihood/frequency and impact/severity of vulnerabilities within space IoT systems. Leveraging vulnerability data from established sources such as the NIST and VARIoT databases, the approach simulates the use of the methodology in a device scenario, allowing for a deterministic and probabilistic assessment of vulnerability criticality. The key contributions of this work lie in its departure from strictly deterministic and distance-based methods, offering a stochastic framework that better reflects the uncertainty and complexity of space-based IoT networks. By incorporating probabilistic simulations, the model provides more accurate and adaptable criticality ratings, enhancing decision-making processes to secure space information systems. The importance of this research is underscored by its potential to simplify and redefine risk management in space IoT systems, providing a more resilient and context-aware framework better suited to the evolving threat landscape for novice risk analysts. This work represents a significant advancement in the field, setting the stage for future developments in secure space IoT deployments.

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