Physical layer security (PLS) has emerged as a promising technology to protect critical and sensitive information against unauthorized devices. To address the key challenge of acquiring channel state information (CSI) of passive eavesdroppers in PLS implementation, we propose a novel sensing-assisted PLS scheme with the aid of reflecting reconfigurable intelligent surface (STAR-RIS). It employs a self-refine sensing scheme utilizing the artificial noise (AN) signals to iteratively estimate the eavesdroppers’ positions for CSI calculation. We aim to maximize the secrecy capacity based on the sensing-estimated CSI while tracking the eavesdroppers in full-duplex (FD) mode with integrated sensing and communication (ISAC) signals comprising artificial noise (AN). This is achieved by jointly designing the beamforming vector of information signals, the beamforming vector of AN signals, and the coefficients of the STAR-RIS. To optimize these coupled variables, we introduce an alternating optimization (AO) scheme to solve the problem recursively. In particular, we tackle the non-convexity of the beamforming optimizations for information and AN signals with the successive convex approximation (SCA) scheme and adopt a semi-definite relaxation (SDR) scheme to design the reflection and refraction coefficients of the STAR-RIS. The numerical results validate that the proposed scheme ensures secure communications against multiple eavesdroppers without any prior eavesdropper channel information. In addition, the proposed scheme can significantly improve SC performance by up to 66. 7% compared to the benchmarks without the sensing-assisted function.
Physical layer security (PLS) has emerged as a promising technology to protect critical and sensitive information against unauthorized devices. To address the key challenge of acquiring channel state information (CSI) of passive eavesdroppers in PLS implementation, we propose a novel sensing-assisted PLS scheme with the aid of reflecting reconfigurable intelligent surface (STAR-RIS). It employs a self-refine sensing scheme utilizing the artificial noise (AN) signals to iteratively estimate the eavesdroppers’ positions for CSI calculation. We aim to maximize the secrecy capacity based on the sensing-estimated CSI while tracking the eavesdroppers in full-duplex (FD) mode with integrated sensing and communication (ISAC) signals comprising artificial noise (AN). This is achieved by jointly designing the beamforming vector of information signals, the beamforming vector of AN signals, and the coefficients of the STAR-RIS. To optimize these coupled variables, we introduce an alternating optimization (AO) scheme to solve the problem recursively. In particular, we tackle the non-convexity of the beamforming optimizations for information and AN signals with the successive convex approximation (SCA) scheme and adopt a semi-definite relaxation (SDR) scheme to design the reflection and refraction coefficients of the STAR-RIS. The numerical results validate that the proposed scheme ensures secure communications against multiple eavesdroppers without any prior eavesdropper channel information. In addition, the proposed scheme can significantly improve SC performance by up to 66. 7% compared to the benchmarks without the sensing-assisted function.
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.
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.
A robust full-space physical layer security (PLS) transmission scheme is proposed in this paper considering the full-space wiretapping challenge of wireless networks supported by simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). Different from the existing schemes, the proposed PLS scheme takes account of the uncertainty on the eavesdropper’s position within the 360◦ service area offered by the STAR-RIS. Specifically, the large system analytical method is utilized to derive the asymptotic expression of the average security rate achieved by the security user, considering that the base station (BS) only has the statistical information of the eavesdropper’s channel state information (CSI) and the uncertainty of its location. To evaluate the effectiveness of the proposed PLS scheme, we first formulate an optimization problem aimed at maximizing the weighted sum rate of the security user and the public user. This optimization is conducted under the power allocation constraint, and some practical limitations for STAR-RIS implementation, through jointly designing the active and passive beamforming variables. A novel iterative algorithm based on the minimum mean-square error (MMSE) and cross-entropy optimization (CEO) methods is proposed to effectively address the established non-convex optimization problem with discrete variables. Simulation results indicate that the proposed robust PLS scheme can effectively mitigate the information leakage across the entire coverage area of the STAR-RIS-assisted system, leading to superior performance gain when compared to benchmark schemes encompassing traditional RIS-aided scheme.
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.
A major limitation of physical layer security is the requirement for prior knowledge of the potential eavesdroppers' (Eves) channels, which makes its practical implementation challenging. Integrated sensing and communication systems can be exploited to address this issue by enabling both communication and sensing functionalities, sensing the physical environment to estimate Eves' directions and amplitudes, and further reconstructing their channel state information (CSI) to achieve sensing-assisted wiretap channel awareness, thus realizing secure communication. We analyze a more practical scenario where not only is reconstructed Eves' CSI inaccurate, but also the CSI of the legitimate user equipments (UEs) estimated by the base station is imperfect, and Eves are equipped with multiple antennas. To resolve this, we propose a robust optimization problem that jointly maximizes the sensing accuracy and the secrecy rate by co-designing the beamforming and the artificial noise matrix. For the highly challenging non-convex infinite objective function, the S-Procedure is introduced, which is then solved by an efficient algorithm based on alternating optimization and successive convex approximation. Numerical results validate the effectiveness of the proposed algorithm and demonstrate that the robust beamforming scheme can mitigate the impact of channel uncertainty (both UEs' and Eves') on the system performance.
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.