ZERO TRUST SERVICE MESH ARCHITECTURE FOR SECURE ENTERPRISE FINANCIAL SYSTEMS

Abstract

Enterprise financial systems increasingly adopt cloud-native microservices and containerized infrastructures to improve scalability, resilience, operational agility, and service availability. However, distributed financial applications introduce sophisticated cybersecurity challenges, including unauthorized service communication, API attacks, lateral movement, insider threats, workload compromise, and identity-based cyberattacks. Conventional perimeter-based security mechanisms are insufficient because they primarily rely on trusted network boundaries without continuously validating service-to-service communications. Recent advances in Zero Trust Architecture (ZTA), Service Mesh technology, Machine Learning (ML), behavioral analytics, cloud-native security, and intelligent policy enforcement enable adaptive protection of enterprise financial systems. This paper proposes a Zero Trust Service Mesh Architecture for securing enterprise financial systems by integrating mutual Transport Layer Security (mTLS), intelligent trust evaluation, adaptive authorization, API security, cloud-native monitoring, and predictive threat analytics. The proposed framework continuously authenticates workloads, encrypts service communications, evaluates contextual cyber risks, and dynamically enforces security policies throughout distributed financial environments. Experimental analysis demonstrates significant improvements in cyberattack detection, service authentication accuracy, workload protection, operational resilience, regulatory compliance, and enterprise security compared with conventional network-centric security architectures. Keywords: Zero Trust Architecture, Service Mesh, Enterprise Financial Systems, Cloud Security, Machine Learning, Microservices Security, Mutual TLS, API Security, Behavioral Analytics, Distributed Systems.