Abstract—Authentication mechanisms are pivotal for ensuring secure communication in modern network environments, which are characterized by increasing complexity and heterogeneity, such as wireless networks, the Internet of Things (IoT), and Visible Light Communication (VLC). This paper presents a comprehensive review of contemporary authentication techniques, focusing on the integration of Physical Layer Security (PLS), Machine Learning (ML), and scalable cryptographic solutions to address evolving security challenges. The study categorizes authentication approaches into cryptographic-based, biometric-based, and PLS-enhanced methods, analyzing their principles, strengths, and limitations. Key advancements include the application of Multiple Input Multiple Output (MIMO) and cooperative relaying in wireless networks for mitigating eavesdropping and supporting high-mobility scenarios. In VLC systems, innovative solutions such as “Optic Fingerprints” and nanomaterial-based enhancements leverage unique physical-layer properties to strengthen authentication. Additionally, scalable and lightweight protocols, incorporating technologies like Physical Unclonable Functions (PUFs) and TinyML, are proposed to address the constraints of resource-limited IoT devices and massive network deployments. This paper highlights critical challenges, including the trade-offs between computational efficiency and security, scalability in dense networks, and the transition to quantum-resistant authentication mechanisms. By adopting a multidisciplinary approach, this study offers insights into developing adaptive and robust authentication frameworks that align with the demands of next-generation networks. The findings underscore the need for collaborative research and standardization to ensure the seamless deployment of secure and efficient authentication systems.
 

Keywords—authentication mechanisms, Physical Layer Security (PLS), Machine Learning (ML), Internet of Things (IoT), Visible Light Communication (VLC)

Cite: Shen Qian, “A Review on Advancing Authentication Mechanisms: Integrating Physical Layer Security, Machine Learning, and Scalable Solutions," Journal of Communications, vol. 20, no. 2, pp. 176-183, 2025.


Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).