A Primer on Graph-Theoretic Models and Metrics
Using Graphs for Modeling and Assessing Robustness
ResearchPublished Mar 26, 2024
Using Graphs for Modeling and Assessing Robustness
ResearchPublished Mar 26, 2024
As weapon systems become more complex, the need increases for mathematical tools to assess their robustness to random failures and attacks with the requisite rigor. The increasing digitization of engineering records in single, authoritative databases enables the use of more-sophisticated modeling tools. For nuclear programs, the need for improved assessment tools is most acute in the areas of nuclear certification, nuclear surety, and cybersecurity risk assessment.
This primer on graph theory provides tools to improve the rigor, reproducibility, and scalability of analytical tools that support cybersecurity assessment, nuclear surety, and nuclear safety certification. It is intended to help analysts use the power of graph theory to assess weapon systems and give those receiving such analysis a better context for understanding how to use the resultant insights.
The work summarizes the key areas of graph theory pertinent to nuclear certification, nuclear surety, and cybersecurity risk assessment. Much of the discussion is a summary of the literature, some of which contains quite recent discoveries. The authors combine the insights from the literature with their own experiences in modeling similar problems with graph theory and explain when a graph is a useful model of a system and when it is not.
This research was prepared for the Department of the Air Force and conducted within the Force Modernization and Employment Program of RAND Project AIR FORCE.
This publication is part of the RAND research report series. Research reports present research findings and objective analysis that address the challenges facing the public and private sectors. All RAND research reports undergo rigorous peer review to ensure high standards for research quality and objectivity.
This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.
RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.