2025/02/17 by Nathan Daniel Schiele, Schiele, Nathan Daniel, Olga Gadyatskaya +1 · 1 citation
Computer Science · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Information and Cyber Security #Network Security and Intrusion Detection
paper · pdf · doi:10.48550/arxiv.2502.11920
openalex publication_date 2025/02/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Attack-defense trees (ADTs) are a prominent graphical threat modeling method that is highly recommended for analyzing and communicating security-related information. Despite this, existing empirical studies of attack trees have established their acceptability only for users with highly technical (computer science) backgrounds while raising questions about their suitability for threat modeling stakeholders with a limited technical background. Our research addresses this gap by investigating the impact of the users' technical background on ADT acceptability in an empirical study. Our Method Evaluation Model-based study consisted of n = 102 participants (53 with a strong computer science background and 49 with a limited computer science background) who were asked to complete a series of ADT-related tasks. By analyzing their responses and comparing the results, we reveal that a very limited technical background is sufficient for ADT acceptability. This finding underscores attack trees' viability as a threat modeling method.