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Computers & Security

A systematic survey on physical layer security oriented to reconfigurable intelligent surface empowered 6G

Shunliang Zhang, Weiqing Huang, Yinlong Liu

Published Sep 4, 2024• 25 citations
Publisher
DOI
10.1016/j.cose.2024.104100

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Bulletin of Electrical Engineering and Informatics•Sep 29, 2022•1 citation
In this paper, we investigate the physical layer security capabilities of reconfigurable intelligent surface (RIS) empowered wireless systems. In more detail, we consider a general system model, in which the links between the transmitter (TX) and the RIS as well as the links between the RIS and the legitimate receiver are modeled as mixture Gamma (MG) random variables (RVs). Moreover, the link between the TX and eavesdropper is also modeled as a MG RV. Building upon this system model, we derive the probability of zero-secrecy capacity as well as the probability of information leakage. Finally, we extract the average secrecy rate for both cases of TX having full and partial channel state information knowledge.
Physical-layer security (PLS) is increasingly considered as a complementary protection layer for beyond-5G and 6G systems, where dense device deployments and stringent latency/energy constraints can increase the overhead of purely upper-layer cryptographic protection. Reconfigurable intelligent surfaces (RISs) offer a low-power means to reshape radio propagation and create channel advantages for legitimate users, potentially enhancing PLS. This paper provides an application-oriented overview of RIS-aided PLS in 6G networks. We first revisit the fundamental concepts of PLS, including secrecy capacity, wiretap-channel and fading-channel models, and classical techniques such as beamforming and artificial noise. We then summarize the role of RIS in 6G architectures and review how RIS can be integrated into single-user, multi-user, and cooperative networks, with particular attention to untrusted relay and IoT scenarios. A taxonomy is proposed to classify representative RIS-aided PLS schemes according to system model, threat model, design methodology, and processing architecture. Finally, we discuss how learning tools—DRL for sequential decision-making, GNNs for topology aware representations, and FL for privacy-preserving distributed training—can be combined with RIS-assisted PLS to cope with the scale and dynamics expected in 6G deployments.
This paper evaluates the physical layer security performance of a reconfigurable intelligent surface (RIS) enabled wireless network in the presence of a passive eavesdropper. To secure the information transmission, a cooperative jammer is proposed to generate interference signal that degrade the performance of the eavesdropper. The source-to-RIS and RIS-to-destination links are subjected to Rician and Rayliegh fading distributions with phase errors, respectively, while other transmission links in the network follow the Nakagami-m fading distributions. The system phase error of the RIS is estimated by the von Mises distribution. To quantify the secrecy performance of the concerned system, the exact closed-form expressions in terms of connection outage probability (COP), security outage probability (SOP), and secrecy throughput (ST) are derived. In addition, the asymptotic expression of the system COP is obtained at high signal-to-noise ratio (SNR), providing more insight about the system performance. The accuracy of the derived expression is justified by Monte Carlo simulation. Also, the results clarify the analysis of the security performance, taking into account the impact of system and channel parameters on the system.