Design and Utility of a Graphical User Interface for Hierarchical Attack Representation Models

Authors

  • Ruoqi Guo School of Electrical Engineering & Computer Science, The University of Queensland, UQ Brisbane, QLD 4072, Australia Author

DOI:

https://doi.org/10.71222/qaj4yk62

Keywords:

cybersecurity visualization, human-computer interaction, graphical security models, HARM, attack graph, cybersecurity education, visual analytics

Abstract

The increasing complexity of cyber threats poses significant cognitive challenges for security analysts and creates communication barriers between technical experts and non-technical stakeholders. While graphical security models like the Hierarchical Attack Representation Model (HARM) offer a scalable solution for analysis, their practical utility is often hindered by the lack of intuitive interfaces. This paper presents the design, implementation, and evaluation of a novel web-based Graphical User Interface (GUI) for HARM, built to enhance network security analysis through effective visualization. Grounded in human-computer interaction (HCI) principles, the interface integrates the HARM model with the Harmat analysis engine, allowing users to interactively build, visualize, and analyze multi-layered attack paths. We detail the system's architecture and key design choices, such as the dual-layer canvas for attack graphs and attack trees, visual iconography, and a logical layout aimed at reducing cognitive load. Furthermore, we discuss the broader implications of this tool beyond technical analysis, exploring its potential as an educational platform for cybersecurity training and as a communication medium to facilitate risk-based decision-making in organizational contexts. The results demonstrate that a well-designed visual interface not only improves the efficiency of security analysis but also makes complex security concepts more accessible to a wider audience.

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Published

19 January 2026

How to Cite

Guo, R. (2026). Design and Utility of a Graphical User Interface for Hierarchical Attack Representation Models. Business and Social Sciences Proceedings , 4, 66-75. https://doi.org/10.71222/qaj4yk62