Integrative Federated Learning and Zero-Trust Approach for Secure Wireless Communications
Muhammad Asad, Safa Otoum
Abstract
The integration of federated learning and zero-trust security offers a promising solution for enhancing wireless communication security. This comprehensive exploration examines the distinct functionalities of these methodologies and their synergistic potential in fortifying security measures. Given the escalating complexity of cyber threats, there is an urgent need for robust, adaptable security frameworks, a requirement that can be addressed by this innovative combination. By leveraging the decentralized data processing capabilities of federated learning and the comprehensive security controls of zero-trust models, resistance against potential breaches can be significantly bolstered. The work also acknowledges and proposes solutions for inherent challenges in the implementation. The conclusion emphasizes the immense potential of this synergy to revolutionize wireless communication security, providing a robust platform for future research.