Expert Evaluation of a User Behavior Micro-Segmentation Framework for Work-From-Home Environments

Abstract

The rapid shift to WFH practices in higher education has increased cyber security risks influenced by user behavior, usability challenges, and contextual constraints. Although several cyber security frameworks have been proposed to address these risks, many lack empirical validation in real academic environments. This study evaluated a behavior-centered cyber security framework designed for university WFH contexts using expert review to assess its feasibility, relevance, and contextual suitability. A mixed-methods expert-based evaluation was conducted, combining structured quantitative ratings with qualitative feedback from cyber security and higher education ICT professionals. Quantitative data were analysed using descriptive statistics and non-parametric tests, while qualitative responses were examined using thematic analysis. The results showed that experts rated the framework as highly relevant and deployable for academic WFH environments, particularly in terms of risky behavior identification and contextual adaptability. Lower ratings were associated with implementation effort, reflecting practical organisational considerations rather than conceptual weaknesses. The study provides empirical evidence supporting the feasibility and applicability of behavior-centered cyber security frameworks in remote academic work environments and demonstrates the value of expert-based mixed-methods evaluation for validating socio-technical security frameworks prior to deployment.