A Multi-Dimensional Design Model for Secure Multi-tenant Architecture in Cloud Computing: Synergising Hyper-Isolation, Zero Trust, and Cryptographic Integrity
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Abstract
The rapid proliferation of cloud computing has established multi-tenancy as the primary architectural paradigm for ensuring cost-efficiency and resource optimization. However, the sharing of physical infrastructure—including memory, CPU caches, and network bandwidth—among mutually distrusting tenants introduces profound security challenges, such as cross-tenant side-channel attacks and unauthorized data exfiltration. This review article proposes a robust design model for secure multi-tenant architecture, termed the "Deep Isolation Framework." We synthesize current research on hardware-assisted virtualization, container orchestration, and micro-VM technologies to evaluate their efficacy in multi-tenant environments. Furthermore, we investigate the integration of Zero Trust Architecture (ZTA) and Post-Quantum Cryptography (PQC) as essential components for future-proofing cloud security. This paper follows a systematic literature review methodology, analyzing 50+ high-impact research papers from the last decade. Our comparative analysis reveals a critical performance-security trade-off, where we propose a modular approach to balance isolation strictness with operational latency. The findings provide a comprehensive blueprint for cloud service providers to build resilient, secure-by-design infrastructures that mitigate the "noisy neighbor" effect and ensure absolute tenant privacy in an increasingly adversarial digital landscape.
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This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License. Authors retain the copyright of their work and grant the Journal of Global Research in Electronics and Communications (JGREC) the right of first publication. This license permits unrestricted use, distribution, adaptation, and reproduction in any medium or format, provided the original author(s), source, and publication are properly credited. Users may copy, redistribute, remix, transform, and build upon the published material for any purpose, including commercial use, in accordance with the terms of the CC BY 4.0 License.