Evaluating The Role of Fuzzy Logic in Enhancing Zero-Trust Security Models in Cloud Environments

This paper evaluates the integration of fuzzy logic into Zero-Trust security models to address the uniquesecurity challenges posed by cloud environments. While traditional Zero-Trust models provide robustmechanisms like secure access, continuous monitoring, and policy enforcement, they often strugglewith issues such as dynamic IPs, distributed applications, and inconsistent policy enforcement acrosshybrid cloud infrastructures. By incorporating fuzzy logic, which is adept at handling uncertainty andimprecise data, we propose an enhanced Zero-Trust model that improves authentication times, reducesfalse positives and negatives, and accelerates response times to threats. Experimental results show asignificant reduction in system overhead, improved anomaly detection rates, higher policy enforcementsuccess, and increased user satisfaction, indicating that fuzzy logic offers a more adaptive, efficient, andsecure solution for cloud-based Zero-Trust architectures.