Design of Zero Trust Architecture with Fuzzy Logic for Robust Cyber Security

Abstract

In the evolving cybersecurity landscape, the Zero Trust Architecture (ZTA) paradigm has gained prominence, advocating "never trust, always verify" for every user and device accessing network resources. However, traditional ZTA approaches often need help with the complexities and ambiguities of real-world scenarios, which can lead to inadequate security measures. This paper introduces a novel framework that integrates Fuzzy Logic into ZTA, aiming to enhance the precision and adaptability of security policies. Fuzzy logic, known for its capacity to handle imprecision and uncertainty, creates a dynamic risk assessment model that evaluates contextual factors such as user behavior, device status, and access patterns. The proposed framework includes a detailed mathematical model that defines fuzzy sets and rules, allowing for a nuanced evaluation of potential threats and determining access permissions. The study demonstrates through simulations and comparative analysis that integrating Fuzzy Logic into ZTA significantly improves security robustness and decision-making accuracy. The findings suggest that this approach can better handle cybersecurity threats' fluid and complex nature. The paper concludes by discussing potential future enhancements, including the incorporation of machine learning techniques to refine the security model further.