Enhancing Physical Layer Security in IoT-Based RF-FSO Integrated Networks: Multi-RIS Structures and their Impact on Secure Communication

Due to their ability to dynamically control the propagation environment, reconfigurable intelligent surfaces (RISs) offer a promising solution to address the challenges of $6$G wireless communication, especially in the context of Internet of Things (IoT) networks. This paper investigates a mixed communication model with multi-RIS-aided radio frequency (RF)-free space optics (FSO) to enhance the performance of IoT applications in complex environments. An eavesdropper is assumed to be present, attempting to intercept confidential information transmitted over the RF link. All RF links are modeled using Rician fading, while the FSO link accounts for M\'alaga turbulence with pointing errors, capturing real-world propagation conditions. Closed-form analytical expressions are derived for the secrecy outage probability, average secrecy capacity, and effective secrecy throughput in terms of Meijer's G function. To gain further insight, high signal-to-noise approximations of these metrics are also presented. Numerical results highlight the importance of heterodyne detection in mitigating the adverse effects of pointing errors on the FSO link. Moreover, integrating a multi-RIS structure into the proposed model significantly increases secrecy performance, achieving up to a $47.67\%$ improvement in SOP compared to conventional methods. Finally, the derived analytical results are validated through Monte Carlo simulations.