Securing the communications link in reconfigurable intelligent surfaces (RISs) near-field (NF) wireless communications presents challenges, especially when uncrewed aerial vehicles (UAVs) provide the wireless communication links. NF communications have emerged as a pivotal area in next-generation wireless systems due to their focus on the spherical nature of waves and enhancing energy efficiency. They considered the best solution for consumer electronics, as the associated NF waves necessitate less energy for transmission in contrast to the planar waves employed in far-field communications. In the context of RIS, NF is critical since, in the far-field, a considerable portion of planar waves passes through the surface elements. Consequently, with UAV assistance, employing RIS in the NF effectively addresses the dynamic characteristics and reliability of communication links. However, the complexity of UAV and RIS models poses significant challenges for secure communication. This paper proposes two secret key generation (SKG) methods to address these challenges and secure RIS-connected users. The convergence of NF and RIS with physical layer-based SKG methods supported by UAV feed links has been analyzed in detail. An information reconciliation method to minimize key mismatch probability (KMP) has been further studied. The simulation results of the proposed methods demonstrate substantial improvements in securing NF-RIS communications within the UAV ecosystem.
Securing the communications link in reconfigurable intelligent surfaces (RISs) near-field (NF) wireless communications presents challenges, especially when uncrewed aerial vehicles (UAVs) provide the wireless communication links. NF communications have emerged as a pivotal area in next-generation wireless systems due to their focus on the spherical nature of waves and enhancing energy efficiency. They considered the best solution for consumer electronics, as the associated NF waves necessitate less energy for transmission in contrast to the planar waves employed in far-field communications. In the context of RIS, NF is critical since, in the far-field, a considerable portion of planar waves passes through the surface elements. Consequently, with UAV assistance, employing RIS in the NF effectively addresses the dynamic characteristics and reliability of communication links. However, the complexity of UAV and RIS models poses significant challenges for secure communication. This paper proposes two secret key generation (SKG) methods to address these challenges and secure RIS-connected users. The convergence of NF and RIS with physical layer-based SKG methods supported by UAV feed links has been analyzed in detail. An information reconciliation method to minimize key mismatch probability (KMP) has been further studied. The simulation results of the proposed methods demonstrate substantial improvements in securing NF-RIS communications within the UAV ecosystem.
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.
With the rapid advancement of unmanned aerial vehicle (UAV), ensuring the security of communication links among UAVs has become crucial. In this paper, we propose a novel physical layer key generation scheme based on channel codeword reconstruction. In UAV communications, the high mobility of aerial nodes leads to short channel coherence time, which together with noise causes inevitable channel estimation errors. These errors significantly degrades the performance of wireless channel-based key generation. Therefore, we propose a codeword construction algorithm that achieves a polarization characteristic, which effectively segregates reliable keys from unreliable ones. Compared to the existing quantization-based key generation scheme, our approach maximize the utilization of raw channel information and employ soft-decision decoding to generate key. Simulation results demonstrate that the proposed scheme reduces the key disagreement rate for legitimate users and increases the number of consistently generated keys. Furthermore, our method ensures a lower key consistency rate for eavesdropper, which guarantees system security.
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.
Due to its high mobility and flexible deployment, unmanned aerial vehicle (UAV) is drawing unprecedented interest in both military and civil applications to enable agile wireless communications and provide ubiquitous connectivity. Mainly operating in an open environment, UAV communications can benefit from dominant line-of-sight links; however, it on the other hand renders the UAVs more vulnerable to malicious eavesdropping or jamming attacks. Recently, physical layer security (PLS), which exploits the inherent randomness of the wireless channels for secure communications, has been introduced to UAV systems as an important complement to the conventional cryptography-based approaches. In this paper, a comprehensive survey on the current achievements of the UAV-aided wireless communications is conducted from the PLS perspective. We first introduce the basic concepts of UAV communications including the typical static/mobile deployment scenarios, the unique characteristics of air-to-ground channels, as well as various roles that a UAV may act when PLS is concerned. Then, we introduce the widely used secrecy performance metrics and start by reviewing the secrecy performance analysis and enhancing techniques for statically deployed UAV systems, and extend the discussion to a more general scenario where the UAVs' mobility is further exploited. For both cases, respectively, we summarize the commonly adopted methodologies in the corresponding analysis and design, then describe important works in the literature in detail. Finally, potential research directions and challenges are discussed to provide an outlook for future works in the area of UAV-PLS in 5G and beyond networks.
With the rapid development of 6G technologies, extremely large-scale reconfigurable intelligent surfaces (XL-RIS) have been introduced to enhance spatial diversity and improve signal coverage. Meanwhile, physical-layer key generation (PKG) has emerged as a promising, quantum-resistant solution for securing wireless communications. However, the deployment of XL-RIS significantly expands the near-field region, making traditional far-field planar wave models inadequate for PKG. To address this limitation, this paper proposes an XL-RIS-assisted PKG model based on near-field spherical wave propagation theory. We further derive a expression for the legitimate key generation rate (KGR) under passive eavesdropping attacks. To maximize the achievable KGR, we propose a novel alternating optimization(AO) algorithm ADA that combines Dinkelbach and the Alternating Direction Method of Multipliers (ADMM) to jointly optimize the base station (BS) beamforming vector and RIS reflection coefficients in an iterative manner. Simulation results indicate that the spatial resolution gain provided by the near-field channel helps enhance the independence between the legitimate and eavesdropping channels. The ADA demonstrates robust convergence. Notably, it maintains superior performance even when the eavesdropper and the legitimate user share the same azimuth angle.
In this letter, we analyze the secrecy performance of a reconfigurable intelligent surface (RIS)-aided communication system with spatially random unmanned aerial vehicles (UAVs) acting as eavesdroppers. We consider the scenarios where the base station (BS) is equipped with single and multiple antennas. The signal-to-noise ratios (SNRs) of the legitimate user and the eavesdroppers are derived analytically and approximated through a computationally effective method. The ergodic secrecy capacity is approximated and derived in closed-form expressions. Simulation results validate the accuracy of the analytical and approximate expressions and show the security-enhanced effect of the deployment of the RIS.