Zero-Trust Cloud Security Architectures with AI-Orchestrated Policy Enforcement. . .
Abstract
Modern cloud infrastructures powering U.S. critical sectors face escalating risks from sophisticated cyber adversaries exploiting misconfigurations and lateral-movement vulnerabilities.
This research introduces a Zero-Trust Cloud Security Architecture (ZTA) integrated with AI-driven policy orchestration to enforce adaptive trust boundaries, verify every transaction, and automate incident containment.
The system dynamically evaluates behavioral telemetry across microservices and applies machine-learning-based policy refinement for continuous compliance.
Experiments demonstrate a 41 % reduction in lateral-threat propagation time and 36 % faster anomaly remediation compared to static rule-based systems.
This research introduces a Zero-Trust Cloud Security Architecture (ZTA) integrated with AI-driven policy orchestration to enforce adaptive trust boundaries, verify every transaction, and automate incident containment.
The system dynamically evaluates behavioral telemetry across microservices and applies machine-learning-based policy refinement for continuous compliance.
Experiments demonstrate a 41 % reduction in lateral-threat propagation time and 36 % faster anomaly remediation compared to static rule-based systems.
Type
Publication
International Journal of Science and Engineering Applications (IJSEA)
This work proposes a Zero-Trust Cloud Security model enhanced by AI-based policy orchestration, designed to protect U.S. critical infrastructure from insider threats, misconfigurations, and adaptive attacks.
