This article presents a comprehensive, publication-ready theoretical synthesis and framework addressing the security challenges of migrating to and operating within multi-tenant cloud environments under the paradigm of Zero Trust Architecture (ZTA). The study integrates interdisciplinary perspectives — cloud migration security, identity and access management (IAM), lateral movement detection and mitigation, distributed denial of service (DDoS) defense, load balancing optimization, deception and resilience strategies, and the application of artificial intelligence to behavioral analytics — to construct a cohesive research agenda and prescriptive architecture for practitioners and researchers. Drawing on a curated set of contemporary doctoral dissertations, peer-reviewed surveys, domain white papers, industry blogs, and governmental guidance, the framework articulates the theoretical rationale for adopting ZTA in cloud migrations, details identity-centric controls and AI-augmented IAM mechanisms, explicates lateral movement attack vectors and evidence-reasoning detection models suitable for edge-to-cloud topologies, examines DDoS defensive architectures and their interplay with multi-tenant load balancing, and proposes layered deception and resilience techniques to harden tenant isolation and minimize blast radius. The methodology is conceptual and analytical; it synthesizes existing empirical and theoretical findings to generate testable propositions, design patterns, and operational guidance for secure cloud transformations. The article concludes with a detailed discussion of implementation trade-offs, limitations of current research, regulatory and operational considerations, and a roadmap for future empirical validation. This contribution aims to bridge the gap between high-level ZTA advocacy and the implementable defensive mechanisms required for complex, shared cloud ecosystems.

Zero Trust Architecture, cloud migration security, lateral movement detection, identity and access management

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