AI-enabled cybersecurity framework for future 5G wireless infrastructures.

The deployment of fifth-generation (5G) wireless networks is transforming digital connectivity through ultra-low latency, high data rates, and massive device support. However, enabling technologies such as network slicing, virtualization, edge computing, and dense Internet of Things (IoT) integration significantly expand the attack surface, necessitating advanced cybersecurity strategies. This study proposes a comprehensive multi-layered cybersecurity framework tailored for 5G infrastructures. The framework incorporates device-level trust validation, secure network slice configuration and isolation, dynamic policy enforcement at the orchestration layer, and AI-driven threat detection to provide end-to-end protection across the 5G architecture. Unlike traditional reactive security models, the proposed approach adopts security-by-design principles to proactively mitigate threats. The framework's effectiveness is evaluated through extensive simulations and benchmarking against established standards, including the NIST Zero Trust Architecture and 3GPP TS 33.501. Results demonstrate a threat detection rate of up to 97.6%, low-latency performance under high-load and adversarial conditions, and scalable operation with large-scale device connectivity. Despite these results, challenges remain in ensuring consistent policy enforcement across distributed edge nodes, achieving interoperability among heterogeneous devices, and balancing performance with stringent security requirements. The study concludes by highlighting future research directions, including quantum-resilient cryptography and self-healing, AI-enhanced security mechanisms, to address evolving threats in future 6G networks.