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Empirical assessment of the perception of graphical threat model acceptability

Published 3 days agoVersion 1arXiv:2512.03351

Authors

Nathan D. Schiele, Olga Gadyatskaya

Categories

cs.CR

Abstract

Threat modeling (TM) is an important aspect of risk analysis and secure software engineering. Graphical threat models are a recommended tool to analyze and communicate threat information. However, the comparison of different graphical threat models, and the acceptability of these threat models for an audience with a limited technical background, is not well understood, despite these users making up a sizable portion of the cybersecurity industry. We seek to compare the acceptability of three general, graphical threat models, Attack-Defense Trees (ADTs), Attack Graphs (AGs), and CORAS, for users with a limited technical background. We conducted a laboratory study with 38 bachelor students who completed tasks with the three threat models across three different scenarios assigned using a Latin square design. Threat model submissions were qualitatively analyzed, and participants filled out a perception questionnaire based on the Method Evaluation Model (MEM). We find that both ADTs and CORAS are broadly acceptable for a wide range of scenarios, and both could be applied successfully by users with a limited technical background; further, we also find that the lack of a specific tool for AGs may have impacted the perceived usefulness of AGs. We can recommend that users with a limited technical background use ADTs or CORAS as a general graphical TM method. Further research on the acceptability of AGs to such an audience and the effect of a dedicated TM tool support is needed.

Empirical assessment of the perception of graphical threat model acceptability

3 days ago
v1
2 authors

Categories

cs.CR

Abstract

Threat modeling (TM) is an important aspect of risk analysis and secure software engineering. Graphical threat models are a recommended tool to analyze and communicate threat information. However, the comparison of different graphical threat models, and the acceptability of these threat models for an audience with a limited technical background, is not well understood, despite these users making up a sizable portion of the cybersecurity industry. We seek to compare the acceptability of three general, graphical threat models, Attack-Defense Trees (ADTs), Attack Graphs (AGs), and CORAS, for users with a limited technical background. We conducted a laboratory study with 38 bachelor students who completed tasks with the three threat models across three different scenarios assigned using a Latin square design. Threat model submissions were qualitatively analyzed, and participants filled out a perception questionnaire based on the Method Evaluation Model (MEM). We find that both ADTs and CORAS are broadly acceptable for a wide range of scenarios, and both could be applied successfully by users with a limited technical background; further, we also find that the lack of a specific tool for AGs may have impacted the perceived usefulness of AGs. We can recommend that users with a limited technical background use ADTs or CORAS as a general graphical TM method. Further research on the acceptability of AGs to such an audience and the effect of a dedicated TM tool support is needed.

Authors

Nathan D. Schiele, Olga Gadyatskaya

arXiv ID: 2512.03351
Published Dec 3, 2025

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