EXPLORING NETWORK SEGMENTATION TECHNIQUES FOR ENHANCED SECURITY IN MULTI-TENANT CLOUD ENVIRONMENTS

Abstract

Network segmentation plays a critical role in enhancing the security posture of multi-tenant cloud environments by limiting lateral movement and isolating workloads, thereby reducing the attack surface. This paper explores the significance of micro-segmentation as a foundational technique, emphasizing its ability to provide granular security control within cloud infrastructures. We examine various segmentation methods, including policy-based segmentation, Software-Defined Networking (SDN), host-based firewalls, and Zero Trust Architectures (ZTA), highlighting their benefits and challenges. Additionally, the paper delves into advanced segmentation techniques that leverage emerging technologies, such as AI-driven dynamic segmentation, behavioural segmentation, blockchain-based segmentation, and Secure Access Service Edge (SASE), which provide enhanced adaptability and scalability in the face of evolving threats. Through a detailed analysis, we demonstrate how these segmentation strategies, both individually and in combination, can strengthen cloud security, improve compliance, and optimize resource utilization. Despite the clear advantages, the paper also addresses the limitations of these techniques, such as increased operational overhead, resource demands, and scalability challenges, offering insights into future research directions to overcome these barriers.