Zero Trust Architecture for 5G Networks

Authors: Varinder Kumar Sharma

DOI: https://doi.org/10.37082/IJIRMPS.v12.i6.232707

Short DOI: https://doi.org/

Country: United States

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Abstract: The deployment of 5G networks represents a pivotal advancement in wireless communication technology, enabling ultra-reliable low-latency communication (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communication (mMTC). These innovations support transformative applications, including autonomous vehicles, smart cities, telemedicine, and industrial IoT. However, alongside these benefits, the architectural complexity and expanded attack surface of 5G networks introduce a new set of security challenges. Unlike traditional cellular networks, 5G features disaggregated control and user planes, software-defined networking (SDN), network function virtualization (NFV), multi-access edge computing (MEC), and network slicing—all of which increase exposure to cyber threats and weaken the effectiveness of perimeter-based security strategies. In this context, Zero Trust Architecture (ZTA) emerges as a necessary paradigm shift, built on the principle of "never trust, always verify," offering a robust security foundation for next-generation mobile networks.
This research paper comprehensively examines the design, integration, and performance of Zero Trust Architecture within 5G networks, focusing on its ability to provide dynamic, identity-aware, and context-driven access control across the 5G system architecture. The study evaluates the implementation of core ZTA principles—such as continuous authentication, micro-segmentation, strict access policy enforcement, real-time monitoring, and least-privilege access—in the context of 5G’s unique architectural components. It proposes a layered ZTA framework aligned with the 3GPP 5G system architecture, integrating Policy Decision Points (PDPs) and Policy Enforcement Points (PEPs) within network functions, such as the Access and Mobility Management Function (AMF), the Session Management Function (SMF), and the User Plane Function (UPF). The framework also incorporates AI-powered Identity and Access Management (IAM) systems and anomaly detection models for proactive security analytics and enforcement.

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Paper Id: 232707

Published On: 2024-11-09

Published In: Volume 12, Issue 6, November-December 2024

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