Mr. Srikanth Reddy Jaidi

AI-Driven Zero-Trust Middleware for Secure Multi-Cloud and Microservice Integration

Abstract:

As communication networks and intelligent systems converge in distributed multi-cloud ecosystems, traditional perimeter-based middleware proves inadequate against over-permissioned APIs and lateral movement threats. This work introduces an AI-enhanced Adaptive Zero-Trust Middleware Framework designed to enforce context-aware policies in real time across heterogeneous integration points. By monitoring device health, user behavior, and geolocation, the framework ensures continuous verification and dynamic access control aligned with Zero-Trust principles.
The architecture integrates service mesh infrastructure with distributed Policy Decision Points, leveraging mTLS, SPIFFE, and OAuth 2.1, while embedding AI-driven policy learning for adaptive enforcement. Experimental validation in a multi-cloud testbed (AWS, Azure, GCP) showed marked improvements in threat detection, accuracy, and false positive reduction compared to baseline API gateways. Automated policy adaptation eliminated manual reconfiguration delays, improving breach response times and achieving comprehensive compliance coverage across healthcare, finance, and government standards.
Performance evaluation demonstrated optimized resource utilization, reduced response latency, and sustained throughput under high load. Sector-focused trials confirmed scalability for high-volume transactions, sensitive data protection, and regulatory resilience. By integrating machine learning for continuous threat-adaptive policy refinement, this middleware provides a future-ready approach to secure communication and intelligent integration in regulated, performance-sensitive multi-cloud deployments.
 

Profile:

Srikanth Reddy Jaidi is a seasoned Enterprise Application Integration Engineer with over 11 years of experience in designing, developing, and implementing API-driven architectures to modernize legacy systems and enhance operational efficiency. He is MuleSoft Certified and highly skilled in API management, integration platforms, and cloud-based solutions, with deep expertise in leveraging MuleSoft Anypoint Platform to deliver secure, scalable, and high-performing enterprise integrations.
Throughout his career, Srikanth has successfully led system modernization projects across industries, including telecommunications, healthcare, government services, and pharmaceuticals. At the Florida Department of Children and Families, he played a key role in modernizing legacy systems, ensuring compliance with HIPAA and CJIS standards, and building integration frameworks to support critical child welfare and self-sufficiency programs. At T-Mobile (Sprint), he was instrumental in deploying AI-powered virtual agents integrated with IBM Watson and MuleSoft to streamline customer journeys, reducing call volumes and enhancing customer self-service capabilities.

Srikanth brings strong technical proficiency in CloudHub 1.0 & 2.0, API Manager, Azure DevOps, Jenkins, GitHub Actions, DataWeave, Java, SQL, Oracle, Salesforce integration, and various enterprise messaging systems. His hands-on expertise extends to API security, CI/CD pipelines, enterprise architecture, error handling, performance tuning, and integration frameworks.

Recognized for his leadership and excellence, he has received multiple awards, including T-Mobile’s Consistent Reliability and Truly Human Award (2020 & 2021), Salesforce Excellence Award, and multiple “Star of the Month” recognitions for critical project contributions.

Srikanth holds a Master’s degree in Computer Science from Virginia International University and a Bachelor’s degree in Computer Science from Guru Nanak Engineering College. His unique blend of technical expertise, functional knowledge, and managerial experience enables him to transform complex business requirements into seamless integration solutions that drive measurable results.