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IEEE/CIC International Conference on Communications in China (ICCC)

DRL-Enhanced Security in RIS-Assisted Systems Simultaneous Against Eavesdropping and Jamming

Abraham Tesfai, Junyu Ma, Z. J. Zhang, Yapeng Li, Qiang Li, Xiaohu Ge

Published Aug 10, 2025• 0 citations
Publisher

Abstract

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.

DOI
10.1109/icccworkshops67136.2025.11148126

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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.
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.
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.
Ensuring signal confidentiality against eavesdroppers is particularly challenging, especially with imperfect channel state information (CSI). To address this, we propose a novel approach leveraging reconfigurable intelligent surfaces (RISs) to enhance security and optimize transmission performance. This paper focuses on secure communication in symbiotic radio (SR) systems by investigating cooperative jamming-assisted transmission with RISs, providing a robust solution to these challenges. RIS-I, acting as a secondary transmitter (STx), multicasts confidential signals from the primary transmitter (Alice) to a primary user (Bob), protecting against eavesdropping by Eve. Additionally, RIS-I transmits its own signals to a secondary user (SU) using backscattering radio technology. Meanwhile, RIS-II serves as a cooperative jammer, converting received confidential signals from Alice into jamming signals by strategically adjusting its reflection coefficients to disrupt Eve’s reception. These RISs can operate cooperatively; when RIS-II transmits as an STx, RIS-I functions as a cooperative jammer. We explore two scenarios: 1. With perfect CSI for the wiretap channel, we propose a joint SDR(Semi-definite relaxation)+MM(Minorization-maximization) optimization algorithm to simultaneously optimize Alice’s beamforming vector and the RISs’ reflection coefficients. 2. With imperfect CSI, we derive the secrecy outage probability formula and evaluate the scheme’s performance across different scenarios. Numerical results demonstrate that RIS-assisted cooperative jamming significantly enhances the secrecy rate and reduces the secrecy outage probability for Bob, outperforming traditional RIS-assisted SR systems.
This paper investigates a cooperative jamming (CJ)-aided secure wireless communication system. Conventional CJ schemes transmit Gaussian noise (GN) to improve security, which inherently degrades the legitimate receiver's performance. While the encoded jamming (EJ) scheme mitigates this interference, its advantage over the GN scheme is highly channel-dependent. To address this limitation, we introduce a reconfigurable intelligent surface (RIS)-assisted secure design based on the EJ scheme for secrecy-rate maximization. Starting from the multiple-input multiple-output (MIMO) secrecy-rate expressions for the EJ and GN schemes, we identify the jamming-channel conditions under which the EJ scheme may be limited. For the general MIMO setup, we develop a weighted minimum mean-square error (WMMSE)-based framework for joint precoder and RIS phase optimization. We further provide a large-RIS asymptotic benchmark showing that a jamming-aligned EJ construction achieves a positive gap over a signal-aligned GN benchmark in the considered multiple-input single-output (MISO) setting. Simulation results support the analysis and show that, under the evaluated settings, the RIS-assisted EJ scheme can alleviate the identified spatial bottlenecks and improve the secrecy rate relative to the considered baselines.
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.