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

2025-09-18

AI Summary

To address the physical-layer security bottleneck in RF-FSO hybrid networks for IoT applications, this paper proposes a multi-reconfigurable intelligent surface (RIS) cooperative enhancement mechanism, jointly optimizing the RF link (modeled by Rician fading) and the FSO link (characterized by Málaga turbulence and pointing error). Closed-form expressions for the secrecy outage probability (SOP), average secrecy capacity, and effective secrecy throughput are derived using Meijer’s G-function and validated via Monte Carlo simulations. The key innovations include: (i) the first integration of multiple RISs into an RF-FSO secure architecture; and (ii) the introduction of heterogeneous-difference detection to mitigate pointing errors. Compared with conventional schemes, the proposed approach reduces SOP by 47.67%, significantly enhancing security robustness under complex channel conditions. This work reveals the pivotal enabling role of RISs in securing 6G-enabled IoT communications.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Machine Learning: Multi-instance/Multi-view Learning
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

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 Málaga 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.

Problem

• Enhancing IoT network security using multi-RIS structures
• Mitigating eavesdropping risks in RF-FSO integrated communication systems
• Improving secrecy performance against physical layer attacks

Innovation

• Multi-RIS structures enhance RF-FSO security
• Closed-form expressions derived using Meijer's G
• Heterodyne detection mitigates FSO pointing errors