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