Design and Analysis of an Adaptive Physical Layer Security Architecture for Human-Centric and Machine-Integrated Communication Over Imperfect Transmission Channels
Keywords:
Physical Layer Security, Adaptive Security Architecture, Human-Centric Communication, Channel ImperfectionsAbstract
The evolution of next-generation communication systems has intensified the convergence of human-centric sensing, machine-to-machine interaction, and heterogeneous wireless environments, thereby exposing transmission channels to multifaceted security vulnerabilities. Traditional cryptographic mechanisms, while robust at higher layers, often fail to address dynamic threats emerging at the physical layer, particularly in environments characterized by channel imperfections, mobility, and resource-constrained devices. This research proposes and analyzes an adaptive physical layer security (PLS) architecture designed to enhance confidentiality, integrity, and authentication in human–machine integrated communication systems. The framework integrates channel reciprocity exploitation, physically unclonable functions (PUFs), biometric-driven authentication mechanisms, and adaptive key generation strategies to establish resilient security under stochastic channel conditions.
The proposed architecture builds upon foundational principles of wireless security evolution, including classical cryptographic theory (Diffie & Hellman, 1976), modern PLS classifications (Hamamreh et al., 2018), and emerging hardware-based trust anchors such as silicon PUFs (Gassend et al., 2002; Halak, 2018). Additionally, it incorporates insights from authentication system evaluation frameworks (Bonneau et al., 2012) to ensure systematic comparability of security effectiveness. The study also examines integration with IoT ecosystems (Kramp et al., 2013) and industrial communication paradigms (Hoffman, 2019), highlighting adaptive mechanisms for mitigating channel noise, interference, and adversarial eavesdropping.
Analytical modeling and comparative synthesis demonstrate that combining physical-layer randomness with hardware-rooted identity primitives significantly enhances resilience against replay, impersonation, and key extraction attacks. The results further indicate that adaptive PLS architectures outperform static security schemes in environments with high mobility and channel variability, particularly in 6G-oriented scenarios (Lipps et al., 2021). The research concludes that human–machine integrated communication systems require cross-layer security intelligence to maintain robust and scalable protection in imperfect transmission environments.
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