Advancing a Speech Act-Based Model to Improve Future Quality of Information Security Policies Using Large Language Models

Employee compliance with Information Security Policies (ISPs) depends on communicating clear and comprehensible content. However, existing research has shown that many ISPs are of poor communicative quality. Large Language Models (LLMs) could enhance ISPs if fine-tuned on high-quality data, but to do such fine-tuning requires a conceptual model for classifying the data and evaluating the resulting text. Therefore, as a step in this direction, the aim of this article is to develop a conceptual model of ISPs using Speech Act Theory as a theoretical lens to enable assessments of the communicative quality of ISPs. We used conceptual modeling and document analysis to develop the model based on 600 ISP statements from ten British National Health Service ISPs. We used selected parts from the SEQUAL framework to evaluate the model. The evaluation pointed to potential areas for improving the model’s semantic, empirical, physical, and deontic qualities. By incorporating these improvements, the final class diagram contains 21 classes, six of which address ISP statement quality as speech acts.

Authors

Publication Details

Journal
Complex Systems Informatics and Modeling Quarterly
Published
2026-04-30
DOI
https://doi.org/10.7250/csimq.2026-46.03
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
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article

Advancing a Speech Act-Based Model to Improve Future Quality of Information Security Policies Using Large Language Models

John Krogstie, Fredrik Karlsson, Leila Aro-Sati, Shang Gao
Complex Systems Informatics and Modeling Quarterly
Information and Cyber Security
article

Advancing a Speech Act-Based Model to Improve Future Quality of Information Security Policies Using Large Language Models

John Krogstie, Fredrik Karlsson, Leila Aro-Sati, Shang Gao
article en

Abstract

Employee compliance with Information Security Policies (ISPs) depends on communicating clear and comprehensible content. However, existing research has shown that many ISPs are of poor communicative quality. Large Language Models (LLMs) could enhance ISPs if fine-tuned on high-quality data, but to do such fine-tuning requires a conceptual model for classifying the data and evaluating the resulting text. Therefore, as a step in this direction, the aim of this article is to develop a conceptual model of ISPs using Speech Act Theory as a theoretical lens to enable assessments of the communicative quality of ISPs. We used conceptual modeling and document analysis to develop the model based on 600 ISP statements from ten British National Health Service ISPs. We used selected parts from the SEQUAL framework to evaluate the model. The evaluation pointed to potential areas for improving the model’s semantic, empirical, physical, and deontic qualities. By incorporating these improvements, the final class diagram contains 21 classes, six of which address ISP statement quality as speech acts.

Complex Systems Informatics and Modeling Quarterly(46)
No poverty
Openalex Percentile: Top 6%
Information and Cyber Security
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