Threat Modeling for Enterprise Cybersecurity Architecture
Author
Abstract

The traditional threat modeling methodologies work well on a small scale, when evaluating targets such as a data field, a software application, or a system component—but they do not allow for comprehensive evaluation of an entire enterprise architecture. They also do not enumerate and consider a comprehensive set of actual threat actions observed in the wild. Because of the lack of adequate threat modeling methodologies for determining cybersecurity protection needs on an enterprise scale, cybersecurity executives and decision makers have traditionally relied upon marketing pressure as the main input into decision making for investments in cybersecurity capabilities (tools). A new methodology, originally developed by the Department of Defense then further expanded by the Department of Homeland Security, for the first time allows for a threat-based, end-to-end evaluation of cybersecurity architectures and determination of gaps or areas in need of future investments. Although in the public domain, this methodology has not been used outside of the federal government. This paper examines the new threat modeling approach that allows organizations to look at their cybersecurity protections from the standpoint of an adversary. The methodology enumerates threat actions that have been observed in the wild using a cyber threat framework and scores cybersecurity architectural capabilities for their ability to protect, detect, and recover from each threat action. The results of the analysis form a matrix called capability coverage map that visually represents the coverage, gaps, and overlaps against threat actions. The threat actions can be further prioritized using a threat heat map – a visual representation of the prevalence and maneuverability of threat actions that can be overlaid on top of a coverage map.

Year of Publication
2022
Date Published
apr
Publisher
IEEE
Conference Location
Charlottesville, VA, USA
ISBN Number
978-1-66545-111-6
URL
https://ieeexplore.ieee.org/document/9799322/
DOI
10.1109/SIEDS55548.2022.9799322
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