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 an$L$-element legitimate RIS is deployed, confidential communication can be safeguarded against eavesdropping systems possessing even more than a$5L$-element malicious RIS.
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.
The escalating demand for secure wireless communication, driven by the proliferation of connected devices, has made information security a paramount concern. Traditional encryption methods struggle against eavesdropping and malicious jamming in open wireless channels, necessitating innovative solutions. This paper explores physical layer security, leveraging intrinsic wireless channel properties, enhanced by reconfigurable intelligent surface (RIS). We propose an RIS-assisted multiple-input single-output system to counteract eavesdroppers and jamming threats through an artificial noise (AN) cooperation scheme. AN is injected during legitimate beamforming to bolster transmission security. Jointly optimizing the base station’s precoding vector, AN vector, and RIS reflection coefficients under power, quality, and phase constraints, we formulate a non-convex secrecy rate (SR) maximization problem. Addressing its complexity, we model it as a Markov decision process and develop a deep deterministic policy gradient algorithm within a deep reinforcement learning framework. Simulation results demonstrate the proposed method’s superior performance, reduced complexity, and robustness against multiple eavesdroppers and high-power jamming, underscoring the critical roles of RIS and AN in securing wireless communications. It consistently outperforms traditional algorithms such as alternating optimization with semidefinite programming, offering up to 7% higher SR and achieving nearly 120% SR gains as RIS elements scale from N =4 to N =10.
Reconfigurable intelligent surface (RIS) has shown significant advantages in improving physical layer security (PLS) performance. Due to simultaneous intercepting and jamming, active eavesdropping attacks can induce more serious security threats to RIS-enabled wireless communications. To deal with this attack, in this work, we propose a double-cooperative RIS-aided PLS framework for protecting against full-duplex active eavesdropping. To be more specific, an optimization problem is formulated to maximize the secrecy capacity by optimizing the phase vectors of double RISs, with the consideration of inter-RIS beamforming gain. Next, to solve this non-convex problem, an efficient iterative algorithm is designed by applying semi-definite relaxation (SDR), successive convex approximation (SCA), and penalty-based solutions. The simulation results verify the superiority of our double-cooperative-RIS solution to prevail against full-duplex active eavesdropping.
In this paper, we pay our attention towards secure and robust communication in the presence of a Reconfigurable Intelligent Surface (RIS)-enhanced mobile eavesdropping attacker in Multiple-Input Multiple-Output (MIMO) wireless networks. Specifically, we first provide a unifying framework that generalizes specific intelligent wiretap model wherein the passive eavesdropper configured with any number of antennas is potentially mobile and can actively optimize its received signal strength with the help of RIS by intelligently manipulating wiretap channel characteristics. To effectively mitigate this intractable threat, we then propose a novel and lightweight secure communication scheme from the perspective of information theory. The main idea is that the data processing can in some cases be observed as communication channel, and a random bit-flipping scheme is then carefully involved for the legitimate transmitter to minimize the mutual information between the secret message and the passive eavesdropper’s received data. The Singular Value Decomposition (SVD)-based precoding strategy is also implemented to optimize power allocation, and thus ensure that the legitimate receiver is not subject to interference from this random bit-flipping. The corresponding results depict that our secure communication scheme is practically desired, which does not require any a prior knowledge of the eavesdropper’s full instantaneous Channel State Information (ICSI). Perfect acquisition of ICSI is clearly always not affordable, which is further exacerbated by the RIS involved and the potential mobility of the passive eavesdropper that leads to unavoidable fast fading channels. Furthermore, we consider the RIS optimization problem from the eavesdropper’s perspective, and provide RIS phase shift design solutions under different attacking scenarios. Finally, the optimal detection schemes respectively for the legitimate user and the eavesdropper are provided, and comprehensive simulations are presented to verify our theoretical analysis and show the effectiveness and robustness of our secure communication scheme across a wide range of attacking scenarios.
In this paper, we explore the physical layer security (PLS) of an active reconfigurable intelligent surface (RIS) assisted multi-input single-output (MISO) system in the presence of a passive eavesdropper (Eve), whose channel is unknown to the legitimate transmitter. In this practical scenario, we first propose an artificial noise (AN) based PLS approach, which can effectively deteriorate the eavesdropping by jointly designing the disturbance signal and the active RIS. However, the AN scheme requires a vast amount of energy to emit the noise signal, which can be potentially suppressed by Eve using more antennas. To tackle this issue, we then introduce another novel reconfigurable intelligent fading (RIF) approach, which utilizes the active RIS to rapidly manipulate the propagation environment, so that Eve suffers a fast fading channel, while the legitimate user (LU) still experiences a slow fading channel. Since Eve encounters difficulties in effectively estimating her fast fading channel, she cannot perform reliable legitimate information detection in a coherent manner, thereby significantly reducing the risk of information leakage and enabling secure communications. Simulation results demonstrate the effectiveness of both proposed approaches. Moreover, the RIF scheme achieves a substantial improvement in security performance compared to the AN scheme, particularly for the cases with limited transmit power.
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.
This paper investigates the integration of a reconfigurable intelligent surface (RIS) into a secure multiuser massive multiple-input multiple-output (MIMO) system in the presence of transceiver hardware impairments (HWI), imperfect channel state information (CSI), and spatially correlated channels. We first introduce a linear minimum-mean-square error estimation algorithm for the aggregate channel by considering the impact of transceiver HWI and RIS phase-shift errors. Then, we derive a lower bound for the achievable ergodic secrecy rate in the presence of a multi-antenna eavesdropper when artificial noise (AN) is employed at the base station (BS). In addition, the obtained expressions of the ergodic secrecy rate are further simplified in some noteworthy special cases to obtain valuable insights. To counteract the effects of HWI, we present a power allocation optimization strategy between the confidential signals and AN, which admits a fixed-point equation solution. Our analysis reveals that a non-zero ergodic secrecy rate is preserved if the total transmit power decreases no faster than 1/N, whereNis the number of RIS elements. Moreover, the ergodic secrecy rate grows logarithmically with the number of BS antennasMand approaches a certain limit in the asymptotic regimeN→ ∞. Simulation results are provided to verify the derived analytical results. They reveal the impact of key design parameters on the secrecy rate. It is shown that, with the proposed power allocation strategy, the secrecy rate loss due to HWI can be counteracted by increasing the number of low-cost RIS elements.