A Multi-Layered Security Model: The Human Factor, Identification, and Secure Network Communications

Modern cybersecurity challenges span multiple layers, from human behavior and identity management to network communication and device security. This paper proposes a unified multi-layered security framework that integrates human-centric, identity-centric, and communication-centric defenses into a coherent architecture. Drawing on insights from diverse domains (industrial control systems, IoT, healthcare, blockchain, and quantum communications), we identify common defense-in-depth principles and interdependencies across layers. The study highlights the persistent gaps in current research, which often focuses on isolated layers or domain-specific models, and addresses these gaps by synthesizing a cross-domain framework. We develop a mixed-method methodology to compare and integrate multi-layer security mechanisms, and we implement a proof-of-concept risk assessment engine to evaluate the framework’s effectiveness. Preliminary results from this implementation demonstrate that combining layers yields significantly improved detection performance and resilience compared to single-layer baselines. The framework’s contributions include a comprehensive literature-driven model, an operational validation in a simulated environment, and guidelines for deploying multi-layer defenses in complex, interconnected infrastructures. Empirical findings confirm that an integrated multi-layer approach can adapt to varied threat scenarios and reduce vulnerabilities, underscoring the value of coordinated controls across technical and human factors. The proposed framework lays a foundation for future work on scalable, cross-layer cybersecurity architectures that better protect contemporary cyber-physical systems.