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Reconfigurable Intelligent Surface–Aided Physical-Layer Security for 6G Networks

Shen Qian

Published Mar 31, 2026• 0 citations
OpenAlex

Abstract

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.

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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.
The potential of Reconfigurable Intelligent Surfaces (RISs) for energy-efficient and performance-boosted wireless communications is recently gaining remarkable research attention, motivating their consideration for various 5-th Generation (5G) Advanced and beyond applications. In this paper, we consider a Multiple-Input Multiple-Output (MIMO) Physical Layer Security (PLS) system with multiple data streams including one legitimate passive RIS and one malicious passive RIS, with the former being transparent to the multi-antenna eavesdropper and the latter’s presence being unknown at the legitimate multi-antenna transceivers. We first present a novel threat model for the RIS-boosted eavesdropping system and design a joint optimization framework for the eavesdropper’s receive combining matrix and the reflection coefficients of the malicious RIS. Focusing next on the secrecy rate maximization problem, we present an RIS-empowered PLS scheme that jointly designs the legitimate precoding matrix and number of data streams, the Artificial Noise (AN) covariance matrix, the receive combining matrix, and the reflection coefficients of the legitimate RIS. The proposed optimization algorithms, whose convergence to at least local optimum points is proved, are based on alternating maximization, minorization-maximization, and manifold optimization, including semi-closed form expressions for the optimization variables. Our extensive simulation results for two representative system setups reveal that, in the absence of a legitimate RIS, transceiver spatial filtering and AN are incapable of offering non-zero secrecy rates, even for malicious RISs with small numbers of elements. However, when anLLL-element legitimate RIS is deployed, confidential communication can be safeguarded against eavesdropping systems possessing even more than a5L5L5L-element malicious RIS.
Physical-layer security (PLS) is expected to play a crucial role in next-generation wirelessnetworks, where ultra-reliable and adaptive communication is required. Emergingtechnologies, particularly reconfigurable intelligent surfaces (RIS), offer new opportunitiesto enhance PLS by enabling programmable control of the wireless propagation environment.Designing effective RIS-assisted PLS frameworks under dynamic and imperfectchannel conditions therefore becomes a critical research challenge.In the first part of this thesis, we investigate an RIS-assisted secure uncrewed aerialvehicle (UAV) communication scheme with multiple colluding eavesdroppers, where theaverage secrecy rate (ASR) is enhanced through joint optimization of the UAV trajectory,artificial noise (AN) and information beamforming, as well as RIS phase shifts. To tacklethe high complexity of the resulting non-convex multi-variable problem, a block coordinatedescent (BCD) framework combined with successive convex approximation (SCA) andmajorization–minimization (MM) techniques is developed. Simulation results demonstratesignificant ASR improvements over benchmark schemes.In the second part, we propose a simultaneously transmitting and reflecting (STAR)-RIS-enabled full-duplex (FD) secure communication scheme. The proposed design notonly suppresses self-interference (SI) to a level comparable to conventional self-interferencecancellation (SIC) techniques, but also intelligently controls the jamming power receivedby the eavesdropper, thereby enhancing secrecy capacity. The transmission and reflectionphase shifts of the STAR-RIS are jointly optimized with beamforming vectors to simultaneouslyfacilitate SI suppression and jamming enhancement. Numerical results confirmthe superiority of the proposed scheme under different STAR-RIS operation modes.In the third part, we develop a STAR-RIS-aided integrated sensing and communication(ISAC) framework to address secure transmission in scenarios where the eavesdropper’schannel state information (CSI) is unavailable. Artificial noise signals are leveragedto simultaneously perform sensing and prevent information leakage, while a self-refiningmechanism is introduced to iteratively improve eavesdropper localization accuracy. Thetransmit beamforming and STAR-RIS coefficients are jointly optimized to enhance sensingperformance, mitigate SI in FD operation, and strengthen jamming effectiveness. Simulationresults in both static and mobile scenarios demonstrate that the proposed designsignificantly improves secrecy capacity through sensing-assisted channel acquisition.
In this article, the physical layer security (PLS) is investigated for reconfigurable intelligent surface (RIS)-aided wireless communication systems, where one RIS is deployed to assist the communications between a pair of transmitter (Alice) and receiver (Bob), under a passive eavesdropper (Eve) attack. For the Eve, different from the bounded channel state information uncertainty model, the distribution of the Eve’s location is introduced into the wiretap link. In the proposed system, considering that the Eve can overhear signals transmitted from Alice or reflected by the RIS, two scenarios are studied for RIS-aided secure communication systems: one is that the Eve distributes close to Alice without the RIS orientation, and the other is that the Eve locates close to Bob and in the presence of the RIS. After investigating the probability distribution functions of the Eve’s location and the wiretap link, the novel cumulative density functions (CDFs) of the received signal-to-noise ratios (SNRs) at the Eves are, respectively, derived for the two considered scenarios, taking into account the effects of RIS reflection coefficients, pathloss, and Eve’s location distribution. The closed-form expressions for the probability of the nonzero secrecy capacity and the ergodic secrecy capacity are obtained, providing insights into the impact of the Eve’s location uncertainty and the RIS design on the secrecy performance. Moreover, based on the derived CDFs for received SNRs at Eves, the secrecy outage probabilities are, respectively, analyzed. Specifically, under the constraint of the secrecy outage probability, the closed forms of the minimum required SNRs at Bob and the number of RIS elements are also obtained. Simulation and analytical results corroborate the derived expressions and reveal the tradeoff between the system’s energy efficiency and the number of RIS elements.
The Internet of Things (IoT) within 6G wireless systems is anticipated to enable ubiquitous wireless machine-type communication and extensive information collection. Owing to the broadcast nature of wireless transmission, IoT networks are vulnerable to various passive and active security threats. Reconfigurable intelligent surfaces (RISs), capable of smartly reconfiguring propagation environments, have been proposed as a solution to these security challenges. RISs can play either a constructive or destructive role depending on whether they are controlled by legitimate users or adversaries; thus, they can be utilized to enhance or diminish secrecy performance for IoT networks. Specifically, by leveraging RIS as a tool, it can enhance the secrecy rate, secret key generation rate, and signal-to-interference-noise ratio (SINR). Conversely, RISs can also be weaponized to compromise secrecy transmission via pilot spoofing, reduce the secret key rate by disrupting the reciprocity of legitimate channels, and degrade the quality of service (QoS) by inducing correlated jamming. This article reviews recent studies on RIS-involved secure communications for IoT networks. Additionally, we discuss the constructive and destructive impacts of RISs. Finally, we outline promising research directions, including secure transmission schemes, attack performance analysis, and countermeasures.
Physical layer security (PLS) is pivotal for beyond 5G networks in response to the escalating demand for secure and reliable communication across various applications, which remain susceptible to eavesdropping and computational attacks. This study presents an innovative aerial reconfigurable intelligent surface (A-RIS) assisted PLS scheme, wherein a RIS-equipped unmanned aerial vehicle (UAV) amplifies the intended legitimate user's signal while concurrently attenuating the eavesdropper's signal to enhance the secrecy outage probability (SOP). We develop closed-form solutions for the SOP and propose an optimal virtual RIS segmentation strategy, which is subsequently employed in a 3D A-RIS deployment approach to minimize the overall SOP. The numerical findings corroborate the analytical derivations and solutions, revealing that the proposed A-RIS partitioning and 3D A-RIS deployment approach yield superior security compared to conventional PLS benchmarks.