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.
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.
Physical layer security (PLS) technologies are expected to play an important role in the next-generation wireless networks, by providing secure communication to protect critical and sensitive information from illegitimate devices. In this paper, we propose a novel secure communication scheme where the legitimate receiver use full-duplex (FD) technology to transmit jamming signals with the assistance of simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) which can operate under the energy splitting (ES) model and the mode switching (MS) model, to interfere with the undesired reception by the eavesdropper. We aim to maximize the secrecy capacity by jointly optimizing the FD beamforming vectors, amplitudes and phase shift coefficients for the ES-RIS, and mode selection and phase shift coefficients for the MS-RIS. With above optimization, the proposed scheme can concentrate the jamming signals on the eavesdropper while simultaneously eliminating the self-interference (SI) in the desired receiver. To tackle the coupling effect of multiple variables, we propose an alternating optimization algorithm to solve the problem iteratively. Furthermore, we handle the non-convexity of the problem by the the successive convex approximation (SCA) scheme for the beamforming optimizations, amplitudes and phase shifts optimizations for the ES-RIS, as well as the phase shifts optimizations for the MS-RIS. In addition, we adopt a semi-definite relaxation (SDR) and Gaussian randomization process to overcome the difficulty introduced by the binary nature of mode optimization of the MS-RIS. Simulation results validate the performance of our proposed schemes as well as the efficacy of adapting both two types of STAR-RISs in enhancing secure communications when compared to the traditional self-interference cancellation technology.
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.
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.
The reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) network is applied to improve spectral efficiency and energy efficiency of wireless systems. Due to the incorporation of NOMA, RIS-aided NOMA system suffers from physical layer security (PLS) problem when an internal near user (NU) is the eavesdropper. In this case, it is difficult to always guarantee positive secrecy rate. Therefore, a scheme of artificial noise (AN) cooperative jamming and beamforming design is proposed against internal eavesdropper for RIS-aided NOMA in this paper. It is proved theoretically that the positive secrecy rate can be guaranteed if providing sufficient power. In addition, the power allocation of base station is further studied to minimize the total power consumption under the constraints of data rate and secrecy rate, and the closed-form solutions are achieved. Simulation results show that the performance of the proposed scheme is superior to the existing solutions.
Abstract This paper investigates a cooperative beamforming (BF) and jamming schemes in active reconfigurable intelligent surface (RIS)-assisted secure communication network, where an active RIS perform reflecting BF and a friendly jammer transmits jamming signal to enhance the security. Specifically, we consider a secrecy rate maximization problem under specific power constraints by assuming that perfect channel state information (CSI) of the eavesdroppers (Eves) can be obtained by the transmitter (Alice). Using the semidefinite relaxation (SDR) and CharnesCooper transformation, we address this problem by performing a one-dimensional search which involves solving a sequence of semidefinite programs (SDPs). For more practical scenario that perfect CSI of the Eves can not be obtained by Alice, a robust joint design of BF and jamming is proposed and the worst-case secrecy rate optimization is solved by using the S-procedure and its extension. Finally, simulation results demonstrate the performance gains of the proposed designs.