Operationalizing the Zero Trust Paradigm: A Multi-Criteria Decision-Making Framework for Secure Enterprise Browser Selection and Security Personnel Competency Evaluation

Abstract

Background: As organizations migrate to cloud-native environments, the traditional network perimeter has evaporated, replaced by the web browser as the primary business interface. This shift necessitates the adoption of Zero Trust Architectures (ZTA) and specialized Secure Enterprise Browsers (SEB). However, the efficacy of these technologies is contingent upon both the selection of appropriate software tools and the competency of the security personnel managing them.

Methods: This study proposes a dual-track decision-support framework. First, it integrates Multi-Criteria Decision-Making (MCDM) methods, specifically TOPSIS with Interval Neutrosophic Sets and Fuzzy ELECTRE, to evaluate SEB solutions based on security, usability, and cost. Second, it applies SWARA and ARAS methods to structure the selection process for cybersecurity personnel, ensuring alignment between human capability and technical requirements.

Results: The application of the proposed framework demonstrates that while technical specifications (e.g., granular DLP controls) are critical, the weighting of "usability" in SEBs significantly impacts long-term Zero Trust compliance. Furthermore, the personnel selection model reveals that adaptive behavioral analysis skills are now more predictive of success than static technical certifications in a Zero Trust environment.

Conclusion: The study establishes that operationalizing Zero Trust requires a synchronized approach to technology and talent acquisition. By utilizing mathematical decision models, organizations can reduce subjectivity and enhance the resilience of their digital ecosystems against modern threats.