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Adaptive Zero Trust Policy Management Framework in 5G Networks

Author

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  • Abdulrahman K. Alnaim

    (Department of Management Information Systems, School of Business, King Faisal University, Hofuf 31982, Saudi Arabia)

Abstract

The rapid evolution and deployment of 5G networks have introduced complex security challenges due to their reliance on dynamic network slicing, ultra-low latency communication, decentralized architectures, and highly diverse use cases. Traditional perimeter-based security models are no longer sufficient in these highly fluid and distributed environments. In response to these limitations, this study introduces SecureChain-ZT , a novel Adaptive Zero Trust Policy Framework (AZTPF) that addresses emerging threats by integrating intelligent access control, real-time monitoring, and decentralized authentication mechanisms. SecureChain-ZT advances conventional Zero Trust Architecture (ZTA) by leveraging machine learning, reinforcement learning, and blockchain technologies to achieve autonomous policy enforcement and threat mitigation. Unlike static ZT models that depend on predefined rule sets, AZTPF continuously evaluates user and device behavior in real time, detects anomalies through AI-powered traffic analysis, and dynamically updates access policies based on contextual risk assessments. Comprehensive simulations and experiments demonstrate the robustness of the framework. SecureChain-ZT achieves an authentication accuracy of 97.8% and reduces unauthorized access attempts from 17.5% to just 2.2%. Its advanced detection capabilities achieve a threat detection accuracy of 99.3% and block 95.6% of attempted cyber intrusions. The implementation of blockchain-based identity verification reduces spoofing incidents by 97%, while microsegmentation limits lateral movement attacks by 75%. The proposed SecureChain-ZT model achieved an authentication accuracy of 98.6%, reduced false acceptance and rejection rates to 1.2% and 0.2% respectively, and improved policy update time to 180 ms. Compared to traditional models, the overall latency was reduced by 62.6%, and threat detection accuracy increased to 99.3%. These results highlight the model’s effectiveness in both cybersecurity enhancement and real-time service responsiveness. This research contributes to the advancement of Zero Trust security models by presenting a scalable, resilient, and adaptive policy enforcement framework that aligns with the demands of next-generation 5G infrastructures. The proposed SecureChain-ZT model not only enhances cybersecurity but also ensures service reliability and responsiveness in complex and mission-critical environments.

Suggested Citation

  • Abdulrahman K. Alnaim, 2025. "Adaptive Zero Trust Policy Management Framework in 5G Networks," Mathematics, MDPI, vol. 13(9), pages 1-32, May.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:9:p:1501-:d:1647892
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    References listed on IDEAS

    as
    1. Sirshak Sarkar & Gaurav Choudhary & Shishir Kumar Shandilya & Azath Hussain & Hwankuk Kim, 2022. "Security of Zero Trust Networks in Cloud Computing: A Comparative Review," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    2. Abdulrahman K. Alnaim & Ahmed M. Alwakeel, 2025. "Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks," Mathematics, MDPI, vol. 13(8), pages 1-34, April.
    3. Rodrigo Asensio-Garriga & Alejandro Molina Zarca & Jordi Ortiz & Ana Hermosilla & Hugo Ramón Pascual & Antonio Pastor & Antonio Skarmeta, 2025. "ZSM Framework for Autonomous Security Service Level Agreement Life-Cycle Management in B5G Networks," Future Internet, MDPI, vol. 17(2), pages 1-28, February.
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