Physical Layer Security (PLS) is a promising approach for securing the Beyond 5G (B5G) wireless networks by exploiting the physical properties of communication channels. Reconfigurable Intelligent Surfaces (RIS) are used to enhance PLS by dynamically controlling signal reflections to favor the legitimate users while degrading eavesdropper channels. This paper focuses on using RIS to improve the secrecy capacity in Line-of-Sight (LOS) scenarios.
Physical Layer Security (PLS) is a promising approach for securing the Beyond 5G (B5G) wireless networks by exploiting the physical properties of communication channels. Reconfigurable Intelligent Surfaces (RIS) are used to enhance PLS by dynamically controlling signal reflections to favor the legitimate users while degrading eavesdropper channels. This paper focuses on using RIS to improve the secrecy capacity in Line-of-Sight (LOS) scenarios.
Physical-layer security (PLS) is superior to classical cryptography techniques due to its notion of perfect secrecy and independence to an eavesdropper's computational power. One form of PLS arises when Alice and Bob (the legitimate users) exchange signals to extract a common key from the random common channels. The drawback of extracting keys from wireless channels is the ample dependence on the dynamicity and fluctuations of the radio channel. However, some radio channels are constant such as line-of-sight (LoS) and can be estimated by Eve (an illegitimate user), or can be quite static in behavior due to the presence low-mobility users thus restricting the amount of randomness. This in turn lowers the secret key rate (SKR) defined as the number of bits of key generated per channel use. In this work, we aim to address this challenge by using a reconfigurable intelligent surface (RIS) to produce random phases at certain carefully curated intervals such that it disrupts the channel in low-entropy environments. We propose an RIS assisted key generation method, study its performance, and compare with benchmarks to observe the benefit of using an RIS while considering various important metrics such as key mismatch rate and average secret key throughput. Simulations are made to validate our theoretical findings showing an improvement in performance when an RIS is deployed.
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.
Physical Layer Key Generation (PLKG) provides a promising approach for establishing secure cryptographic keys between legitimate parties. However, in static and quasi-static environments, the key generation rate is significantly limited due to the low entropy of the wireless channel. To overcome this, Reconfigurable Intelligent Surfaces (RIS) have been proposed to enhance the channel entropy by altering the phase of incident electromagnetic waves. This paper addresses this challenge by proposing a security architecture that integrates a Multi-Input Multi-Output (MIMO) base station with a Beyond-Diagonal Reconfigurable Intelligent Surface (BD-RIS) in multi-user scenarios, in the presence of an eavesdropper. Unlike conventional RIS, BD-RIS not only modifies the phase but also the magnitude of the impinging signals, introducing an additional degree of freedom that further enhances channel randomness. The secret key capacity of the proposed system is compared with that of conventional RIS in two scenarios: firstly, when a direct link exists alongside the BD-RIS-assisted link. Secondly, when the direct link is completely obstructed by an obstacle. Simulation results demonstrate that the proposed BD-RIS architecture outperforms conventional diagonal RIS (D-RIS) in all scenarios. Furthermore, the generated keys undergo randomness tests, successfully passing all National Institute of Standards and Technology (NIST) randomness subtests as well as the Autocorrelation (AC) test, confirming their suitability for secure communications. These findings establish BD-RIS as a promising technology for enhancing physical layer security in static environments for 5G/6G networks and IoT applications.
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.
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 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 anL-element legitimate RIS is deployed, confidential communication can be safeguarded against eavesdropping systems possessing even more than a5L-element malicious RIS.