Wireless Channel-based Secret Key Generation (WC-SKG) offers a promising alternative for wireless communication security, yet suffers from an extremely low key generation rate (KGR) in quasi-static environments (e.g., indoor Internet of Things), where key refresh cycles can extend for hours, creating a security vulnerability. Reconfigurable Intelligent Surfaces (RIS) can boost KGR by introducing artificial randomness, yet existing schemes only randomize the RIS phase shifts without using environmental priors, failing to maximize the KGR and meet the communication signal-to-noise ratio (SNR) requirement, causing service outages. To overcome these limitations, we propose the RIS-assisted Integrated Communication and WC-SKG (RICK) scheme. First, we treat the RIS-adjusted channel as a designable random variable and derive its optimal probability density function (PDF) using a novel geometric-algebraic framework to maximize the KGR under the communication SNR constraint. Second, we design a constrained-clustering-based quantization region division scheme tailored to this optimal non-uniform PDF, guaranteeing uniformly distributed secret keys. Simulation results show RICK achieves a KGR approximately 3.5-5 times higher than the state-of-the-art scheme while saving at least 20 dB of transmit power for the same KGR, confirming its effectiveness in quasi-static scenarios.

In this paper, we propose a dynamic agile reconfigurable intelligent surface antenna (DARISA) array integrated into multi-input multi-output (MIMO) transceivers. Each DARISA comprises a number of metasurface elements activated simultaneously via a parallel feed network. The proposed system enables rapid and intelligent phase response adjustments for each metasurface element within a single symbol duration, facilitating a dynamic agile adjustment of phase response (DAAPR) strategy. By analyzing the theoretical degrees of freedom (DoF) of the DARISA MIMO system under the DAAPR framework, we derive an explicit relationship between DoF and critical system parameters, including agility frequentness (i.e., the number of phase adjustments of metasurface elements during one symbol period), cluster angular spread of wireless channels, DARISA array size, and the number of transmit/receive DARISAs. The DoF result reveals a significant conclusion: when the number of receive DARISAs is smaller than that of transmit DARISAs, the DAAPR strategy of the DARISA MIMO enhances the overall system DoF. Furthermore, relying on DoF alone to measure channel capacity is insufficient, so we analyze the effective DoF (EDoF) that reflects the impacts of the DoF and channel matrix singular value distribution on capacity. We show channel capacity monotonically increases with EDoF, and optimize the agile phase responses of metasurface elements by using fractional programming (FP) and semidefinite relaxation (SDR) algorithms to maximize the EDoF. Simulations validate the theoretical DoF gains and reveal that increasing agility frequentness, metasurface element density, and phase quantization accuracy can enhance the EDoF. Additionally, densely deployed elements can compensate for the loss in communication performance caused by lower phase quantization accuracy.

We propose an innovative physical layer authentication method, leveraging deep learning to robustly safeguard millimeter wave communications against pilot contamination and clone attacks. Unlike traditional upper-layer authentication mechanisms, our method capitalizes on the spatial-temporal characteristics of millimeter wave channels to extract unique fingerprints, thus establishing a lightweight channel-based authentication technique. Existing methods largely overlook pilot contamination attacks, which may severely degrade the performance of physical layer authentication. Furthermore, traditional threshold-based methods struggle to differentiate between multiple nodes, while supervised learning-based methods are practically constrained due to the unavailability of attackers’ instantaneous channel state information. Moreover, traditional real-valued deep neural networks are inefficient in utilizing the phase information of complex-valued channels, rendering them inadequate for designing practical physical layer authentication schemes. To address these challenges, we propose an autoencoder, empowered by an alternating direction method of multipliers, which can detect and mitigate pilot contamination attacks by exploiting the inherent sparsity of channels. Subsequently, we design a weighted loss function to optimize the proposed classifiable autoencoder to strike an effective balance between detecting clone attacks and authenticating multiple nodes. Finally, to further enhance feature extraction from complex-valued channels, we customize a complex-valued classifiable autoencoder incorporating an innovative complex-valued long short-term memory module. Our simulation results unveil that the proposed method significantly outperforms existing approaches in maintaining high authentication accuracy even under pilot contamination, achieving a desirable trade-off between false alarm and detection rates. Additionally, our proposed complex-valued neural networks further enhance the accuracy of clone attack detection and multiple legitimate nodes authentication.

Leveraging its exceptionally wide bandwidth, Terahertz (THz) communication offers ultra-high-speed data transmission and remarkably precise sensing, establishing itself as a cornerstone technology for integrated sensing and communication (ISAC) systems. This paper investigates a multi-base-station (multi-BS) cooperative extremely-large-scale multiple-input multiple-output (XL-MIMO) orthogonal frequency division multiplexing (OFDM) near-field THz-ISAC system designed to guarantee secure downlink communication for multiple users, while simultaneously enhancing multi-target localization accuracy. The core challenge lies in optimizing the secrecy rate subject to the Cramer-Rao Bound (CRB) constraint to strike an´ effective balance between communication security and sensing precision. To this end, we propose an unsupervised learning-based complex-valued deep neural network (CVNN) that jointly optimizes hybrid beamforming and radar sensing signals in a data-driven manner. Simulation results unveil that the proposed approach outperforms the conventional alternating optimization-based hybrid beamforming benchmark in terms of secrecy rate and computation time. These results validate the practicality of data-driven joint optimization in THz-ISAC systems by demonstrating its effectiveness in achieving an efficient tradeoff between communication security and sensing accuracy, while also providing actionable design guidelines for scalable, low-latency system in extremely-large-scale deployment.

ABSTRACT The real‐time reconfigurable characteristics of meta‐surface antennas can be used to separate multi‐stream signals under the condition of single radio frequency (RF). However, with the increase of the symbol rate and the number of antenna arrays in the future, it will face the problem that the state switch rate of the electromagnetic unit is not enough to reach the upper limit of array effective degrees of freedom (DOF) of the meta‐surface antenna. To solve this problem, a theory of asynchronous control meta‐surface antenna is proposed in this paper. By designing the starting time of different element state switching, different electromagnetic element states are staggered to improve the array effective DOF of the meta‐surface antenna. Then, an electromagnetic unit state design algorithm of asynchronous control meta‐surface antenna based on the minimum condition number of equivalent channel matrix is proposed. We improve the sparrow search algorithm to solve the condition number minimization problem in order to obtain the better multi‐stream signal separation performance. The simulation results show that compared with the synchronous control meta‐surface antenna, theory proposed in this paper can improve the effective DOF of array under the condition of limited switch rate, and can effectively reduce the receiving bit error rate and improve spectral efficiency when separating multi‐stream signals.

Abstract This paper investigates methods to enhance antenna's channel information extraction capabilities in wireless communications, particularly in challenging multi‐path environments. Focusing on the issues of channel information loss due to multi‐path superposition at the receiver and multi‐path fading during wireless channel propagation, this paper utilizes metasurface antennas to rapidly reconfigure antenna patterns and construct high‐dimensional projection spaces, thus improving information sensing resolution. Based on this, a channel‐matched receiving pattern design method is proposed to mitigate the communication performance loss caused by multi‐path fading. Furthermore, this paper analyses the comprehensive impact of various metasurface parameters on the performance of the proposed scheme, providing theoretical guidance for engineering implementation. Simulation results demonstrate that the proposed scheme can achieve the performance of multi‐path channel estimation and reception close to those of multi‐antenna arrays using a single radio frequency link.

Reconfigurable intelligent surface (RIS), which can manipulate the wireless environment, has recently been integrated into physical-layer key generation (PKG) systems to establish randomness symmetric keys in static environments. However, few studies have jointly considered the optimization and randomization of the RIS elements to simultaneously achieve a high key generation rate (KGR) and communication performance. This study proposes a RIS-assisted communication and security-integrated protocol for dual-function integration of communication enhancement and PKG in static environments. The protocol partitions RIS elements for beamforming and random beams for parallel execution, utilizing a sparsity adaptive matching pursuit-based channel estimation algorithm to obtain individual channel state information. Subsequently, an optimization problem is formulated for KGR maximization while satisfying quality of service (QoS) requirements. The non-convex optimization problem is addressed through monotonicity analysis and triangle inequality. We validate the efficacy of the proposed protocol by developing a 4.9 GHz RIS-assisted PKG prototype system, comprising modular hardware and flexible software. The field trials demonstrate a 30.81 bit/s KGR for static environments with an average received power increase of 10.6 dB, achieving effective simultaneous integration of communication and security.

Due to the limited coverage of reflecting-only reconfigurable intelligent surfaces (RIS), the existing RIS-assisted physical-layer key generation (PKG) scheme limits its overall performance in the full space. This paper proposes a novel simultaneously transmitting and reflecting (STAR)-RIS-assisted PKG protocol for multiple-input multiple-output (MIMO) systems, where the closed-form sum secret key rate is derived in the presence of full-space eavesdroppers. Two optimization problems are formulated to maximize the sum secret key rate by designing the transmit beamforming (TBF) and transmitting and reflecting coefficients (TRCs) for energy splitting (ES) with coupled phase-shift and mode switching (MS) mode. For ES mode with coupled phase-shift, a penalty-based alternating optimization (AO) algorithm is proposed to address its non-convexity. For MS mode, the semidefinite relaxation-successive convex approximation-based AO algorithm is utilized to achieve continuous solutions and then quantize to binary value for the MS mode. Simulation results demonstrate that the coupled phase-shift STAR-RIS incurs a slight KGR loss in comparison to the independent phase-shift STAR-RIS. Additionally, the ES mode outperforms the MS mode in terms of KGR performance. Finally, STAR-RIS can achieve a higher sum secret key rate than traditional reflecting-only RIS.

This paper investigates the simultaneously transmitting and reflecting reconfigurable surface (STAR-RIS) assisted physical layer key generation (PKG) for multiuser networks. We propose a novel STAR-RIS-assisted PKG protocol and formulate a sum secret key rate maximization problem by jointly optimizing the active and passive beamforming. To address the non-convex problem, a block coordinate descent (BCD) algorithm is developed, using both semidefinite relaxation (SDR) and successive convex approximation (SCA) methods to optimize active and passive precoding alternately. Simulation results demonstrate the key generation performance of the proposed algorithm outperforms schemes that STAR-RISs using the random configuration and conventional reflecting/transmitting-only RISs.

An array’s degree of freedom (DoF) determines the number of jamming incidents that can be managed and the antijamming performance. Conventional arrays can improve the DoF only by increasing the number of antennas. On the other hand, when the received signal is digitized, high-power jamming will reduce the number of bits used to represent the desired signal, further increasing the difficulty of back-end antijamming based on digital signal processing. In this paper, we propose a joint radio frequency (RF) front-end and digital back-end antijamming scheme based on a metasurface antenna array. The metasurface antennas can rapidly switch patterns when receiving signals, so that a single channel can be equivalent to multiple channels and increase the DoF. We use independent component analysis to estimate the channel and then optimize the array parameters under the minimum signal-to-jamming ratio constraint of each antenna. The proposed scheme works well under high-power jamming conditions by suppressing jamming at the RF front end and using a low-precision analog-to-digital converter. Simulation results show that the proposed scheme reduces the bit error rate of the received signals by one order of magnitude compared with the conventional array.

Abstract The propagation of electromagnetic waves will produce multi‐path fading of wireless channel, which degrades communication performance substantially. If multi‐path can be separated, better signal transmission and reception strategies can be designed to weaken or eliminate fading and improve signal transmission performance. However, it is challenging for communication nodes with limited number of antennas. A general multi‐path separation and measurement framework based on single dynamic metasurface antenna is established which rapidly changes patterns within a single pilot symbol period so that equivalent multi‐dimensional received signals can be obtained. Based on the framework, a multi‐path channel estimation scheme is proposed. Specifically, the parameter estimation problem is formulated and present the algorithm based on atomic norm minimisation to estimate parameters including angle of arrival and complex gain of each propagation path. Simulation results illustrate that single dynamic metasurface antenna can approach the capability of a conventional multi‐antenna array, and even using single dynamic metasurface antenna with 1‐bit coding can estimate angle of arrivals and complex gains of multi‐path components accurately.

The sixth-generation mobile communication (6G) networks will face more complex endogenous security problems, and it is urgent to propose new universal security theories and establish new practice norms to deal with the “unknown unknown” security threats in cyberspace. This paper first expounds the new paradigm of cyberspace endogenous security and introduces the vision of 6G cyberspace security. Then, it analyzes the security problems faced by the 6G core network, wireless access network, and emerging associated technologies in detail, as well as the corresponding security technology development status and the integrated development of endogenous security and traditional security. Furthermore, this paper describes the relevant security theories and technical concepts under the guidance of the new paradigm of endogenous security.

Due to the channel estimation error, most of the physical layer secret key generation schemes need information reconciliation to correct error key bits, resulting in reduced efficiency. To solve the problem, this work proposes a novel secure communication scheme based on a equivalent interference channel. Different keys generated from imperfect channel state information are directly applied to signal scrambling and descrambling, which is equivalent to the process of a signal passing through an interference channel. Legitimate communication parties can reduce interference with the help of similar keys and channel coding without sending additional signals, while the eavesdropper channel is deteriorated due to the spatial decorrelation. For this kind of schemes, we first establish a discrete memoryless broadcast channel model to derive the expressions of bit error rate (BER), channel capacity, and security capacity for performance analysis. Simulation results verify the derivations that the proposed scheme achieves secure communication with a correlated eavesdropping channel and has a higher upper bound of transmission rate. Furthermore, we design a new metric to evaluate the efficiency and the result shows that the proposed scheme has superior performance on error reconciliation efficiency, despite its slight increase in BER.

Existing studies on the secret key generation based on physical layer wireless fading channel are largely open under active attacks. In this paper, we discuss how the man-in-the- middle (MITM) attacker, who acts as a transparent relay, attacks the training phase in wireless communication to improve the information leaked rate. We prove that the MITM attacker can intercept all of the channel information when all of the paths pass through the attacker. We present the closed-form solution of information leakage rate and achieve the optimal attack effect when the transmitter can directly communicate with receiver besides the paths by way of attacker. The results show that the MITM attack can cause new challenges for physical-layer security since it leads to higher information leakage rate. Numerical results are presented to further demonstrate the potent threat of MITM attack.