Dataset for authentication and authorization using physical layer properties in indoor environment.

The proliferation landscape of the Internet of Things (IoT) has accentuated the critical role of Authentication and Authorization (AA) mechanisms in securing interconnected devices. There is a lack of relevant datasets that can aid in building appropriate machine learning enabled security solutions focusing on authentication and authorization using physical layer characteristics. In this context, our research presents a novel dataset derived from real-world scenarios, utilizing Zigbee Zolertia Z1 nodes to capture physical layer properties in indoor environments. The dataset encompasses crucial parameters such as Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), Device Internal Temperature, Device Battery Level, and more, providing a comprehensive foundation for advancing Machine learning enabled AA in IoT ecosystems.

Secrecy Performance Enhancement Using Self-Interference Cancellation in Wireless Mutual Broadcast Networks for Proximity-Based Services.

With the increasing demand for data exchange between nearby devices in proximity-based services, enhancing the security of wireless mutual broadcast (WMB) networks is crucial. However, WMB networks are inherently vulnerable to eavesdropping due to the open broadcast nature of their communication. This paper investigates the improvement of secrecy performance in random-access-based WMB (RA-WMB) networks by integrating physical layer security (PLS) techniques with hybrid duplex (HBD) operations under a stochastic geometry framework. The HBD method balances half-duplex (HD) receiving and full-duplex (FD) transceiving, utilizing self-interference cancellation (SIC) to enhance PLS performance. Key operational parameters, including transmission probability (TxPr), friendly jammer density, and conditions for FD operation, are designed to maximize secrecy performance. The analytical and numerical results demonstrate significant improvements in PLS performance, with SIC playing a critical role, particularly in scenarios with dense legitimate nodes, and with TxPr adjusted to balance HD receiving and FD transceiving based on SIC imperfections. The proposed design principles provide a comprehensive framework for enhancing the security of WMB networks, addressing the complex interplay of interference and SIC in various network configurations.

Wireless-Channel Key Distribution Based on Laser Synchronization.

We propose and experimentally demonstrate a wireless-channel key distribution scheme based on laser synchronization induced by a common wireless random signal. Two semiconductor lasers are synchronized under injection of the drive signal after electrical-optical conversion and emit irregular outputs that are used to generate shared keys. Our proof-of-concept experiment using a complex drive signal achieved a secure key generation rate of up to 150 Mbit/s with a bit error rate below 3.8 × 10-3. Numerical simulation results show that the proposed scheme has the potential to achieve a distribution distance of several hundred meters. It is believed that common-signal-induced laser synchronization paves the way for high-speed wireless physical-layer key distribution.

Enhancing Security in Visible Light Communication: A Tabu-Search-Based Method for Transmitter Selection.

In this paper, we explore the secrecy performance of a visible light communication (VLC) system consisting of distributed light-emitting diodes (LEDs) and multiple users (UEs) randomly positioned within an indoor environment while considering the presence of an eavesdropper. To enhance the confidentiality of the system, we formulate a problem of maximizing the sum secrecy rate for UEs by searching for an optimal LED for each UE. Due to the non-convex and non-continuous nature of this security maximization problem, we propose an LED selection algorithm based on tabu search to avoid getting trapped in local optima and expedite the search process by managing trial vectors from previous iterations. Moreover, we introduce three LED selection strategies with a low computational complexity. The simulation results demonstrate that the proposed algorithm achieves a secrecy performance very close to the global optimal value, with a gap of less than 1%. Additionally, the proposed strategies exhibit a performance gap of 28% compared to the global optimal.

Joint Active and Passive Beamforming in RIS-Assisted Secure ISAC Systems.

This paper investigates joint beamforming in a secure integrated sensing and communications (ISAC) system assisted by reconfigurable intelligent surfaces (RIS). The system communicates with legitimate downlink users, detecting a potential target, which is a potential eavesdropper attempting to intercept the downlink communication information from the base station (BS) to legitimate users. To enhance the physical-layer secrecy of the system, we design and introduce interference signals at the BS to disrupt eavesdroppers' attempts to intercept legitimate communication information. The BS simultaneously transmits communication and interference signals, both utilized for communication and sensing to guarantee the sensing and communication quality. By jointly optimizing the BS active beamformer and the RIS passive beamforming matrix, we aim to maximize the achievable secrecy rate and radiation power of the system. We develop an effective scheme to find the active beamforming matrix through fractional programming (FP) and semi-definite programming (SDP) techniques and obtain the RIS phase shift matrix via a local search technique. Simulation results validate the effectiveness of the proposed methods in enhancing communication and sensing performance. Additionally, the results demonstrate the effectiveness of introducing the interference signals and RIS in enhancing the physical-layer secrecy of the ISAC system.

Empowering the Vehicular Network with RIS Technology: A State-of-the-Art Review.

Reconfigurable intelligent surfaces (RIS) are expected to bring about a revolutionary transformation in vehicular networks, thus paving the way for a future characterized by connected and automated vehicles (CAV). An RIS is a planar structure comprising many passive elements that can dynamically manipulate electromagnetic waves to enhance wireless communication by reflecting, refracting, and focusing signals in a programmable manner. RIS exhibits substantial potential for improving vehicle-to-everything (V2X) communication through various means, including coverage enhancement, interference mitigation, improving signal strength, and providing additional layers of privacy and security. This article presents a comprehensive survey that explores the emerging opportunities arising from the integration of RIS into vehicular networks. To examine the convergence of RIS and V2X communications, the survey adopted a holistic approach, thus highlighting the potential benefits and challenges of this combination. In this study, we examined several applications of RIS-aided V2X communication. Subsequently, we delve into the fundamental emerging technologies that are expected to empower vehicular networks, encompassing mobile edge computing (MEC), non-orthogonal multiple access (NOMA), millimeter-wave communication (mmWave), Artificial Intelligence (AI), and visible light communication (VLC). Finally, to stimulate further research in this domain, we emphasize noteworthy research challenges and potential avenues for future exploration.

Generative Adversarial Network-Based Data Augmentation for Enhancing Wireless Physical Layer Authentication.

Wireless physical layer authentication has emerged as a promising approach to wireless security. The topic of wireless node classification and recognition has experienced significant advancements due to the rapid development of deep learning techniques. The potential of using deep learning to address wireless security issues should not be overlooked due to its considerable capabilities. Nevertheless, the utilization of this approach in the classification of wireless nodes is impeded by the lack of available datasets. In this study, we provide two models based on a data-driven approach. First, we used generative adversarial networks to design an automated model for data augmentation. Second, we applied a convolutional neural network to classify wireless nodes for a wireless physical layer authentication model. To verify the effectiveness of the proposed model, we assessed our results using an original dataset as a baseline and a generated synthetic dataset. The findings indicate an improvement of approximately 19% in classification accuracy rate.

Simultaneously Intelligent Sensing and Beamforming Based on an Adaptive Information Metasurface.

Due to its ability to adapt to a variety of electromagnetic (EM) environments, the sensing-enabled metasurface has garnered significant attention. However, large-scale EM-field sensing to obtain more information is still very challenging. Here, an adaptive information metasurface is proposed to enable intelligent sensing and wave manipulating simultaneously or more specifically, to realize intelligent target localization and beam tracking adaptively. The metasurface is composed of an array of meta-atoms, and each is loaded with two PIN diodes and a sensing-channel structure, for polarization-insensitive and programmable beamforming and sensing. By controlling the state of the PIN diode, the proposed meta-atom has 1-bit phase response in the designed frequency band, while the sensing loss keeps higher than -10 dB for both "ON" and "OFF" states. Hence there is nearly no interaction between the beamforming and sensing modes. Experiments are conducted to show multiple functions of the metasurface, including intelligent target sensing and self-adaptive beamforming, and the measured results are in good agreement with the numerical simulations and theoretical calculations.

Covert Scattering Control in Metamaterials with Non-Locally Encoded Hidden Symmetry.

Symmetries and tunability are of fundamental importance in wave scattering control, but symmetries are often obvious upon visual inspection, which constitutes a significant vulnerability of metamaterial wave devices to reverse-engineering risks. Here, it is theoretically and experimentally shown that a symmetry in the reduced basis of the "primary meta-atoms" that are directly connected to the outside world is sufficient; meanwhile, a suitable topology of non-local interactions between them, mediated by the internal "secondary" meta-atoms, can hide the symmetry from sight in the canonical basis. Covert symmetry-based scattering control in a cable-network metamaterial featuring a hidden parity ( P $\mathcal {P}$ ) symmetry in combination with hidden- P $\mathcal {P}$ -symmetry-preserving and hidden- P $\mathcal {P}$ -symmetry-breaking tuning mechanisms is experimentally demonstrated. Physical-layer security in wired communications is achieved using the domain-wise hidden P $\mathcal {P}$ -symmetry as a shared secret between the sender and the legitimate receiver. Within the approximation of negligible absorption, the first tuning of a complex scattering metamaterial without mirror symmetry to feature exceptional points (EPs) of PT $\mathcal {PT}$ -symmetric reflectionless states, as well as quasi-bound states in the continuum, is reported. These results are reproduced in metamaterials involving non-reciprocal interactions between meta-atoms, including the first observation of reflectionless EPs in a non-reciprocal system.

Large-Scale Multicast Group Secure Transmission Scheme Based on Multi-Carrier FDA.

Aiming at the problem that the traditional physical layer technology cannot realize secure transmission due to the large number of users and wide dispersion in the multicast system, a layered transmission method is proposed, and a scheme for the secure transmission of the multicast group physical layer is designed. Firstly, the hierarchical transmission system model is established. Then, the array weighted vector of each layer is optimized according to the design criterion of maximizing the artificial noise interference power. At the same time, in the case where the number of users in a single multicast group is greater than the number of transmitting antennas, a multicast grouping strategy is introduced, and the singular value decomposition and Lagrange multiplier algorithms are utilized to obtain the optimal solution. Simulation results show that the proposed method can realize the secure communication of users with different distances in the same direction and can distinguish the multicast users with the same direction angle and different distances under the premise of mutual non-interference, thus realizing the secure communication of large-scale multicast users.

Novel Noise Injection Scheme to Guarantee Zero Secrecy Outage under Imperfect CSI.

The paper proposes a novel artificial noise (AN) injection strategy in multiple-input single-output multiple-antenna-eavesdropper (MISOME) systems under imperfect channel estimation at the legitimate channel to achieve zero secrecy outage probability under any circumstance. The zero secrecy outage is proved to always be achievable regardless of the eavesdropper's number of antennas or location when the pair secrecy and codeword rates are chosen properly. The results show that when there is perfect channel state information, the zero-outage secrecy throughput increases with the transmit power, which is important for secrecy design. Additionally, an analysis of the secrecy throughput and secrecy energy efficiency gives further insight into the effectiveness of the proposed scheme.

Performance Analysis of Artificial Noise-Assisted Location-Based Beamforming in Rician Wiretap Channels.

This paper studies the performance of location-based beamforming with the presence of artificial noise (AN). Secure transmission can be achieved using the location information of the user. However, the shape of the beam depends on the number of antennas used. When the scale of the antenna array is not sufficiently large, it becomes difficult to differentiate the performance between the legitimate user and eavesdroppers nearby. In this paper, we leverage AN to minimize the area near the user with eavesdropping risk. The impact of AN is considered for both the legitimate user and the eavesdropper. Closed-form expressions are derived for the expectations of the signal to interference plus noise ratios (SINRs) and the bit error rates. Then, a secure beamforming scheme is proposed to ensure a minimum SINR requirement for the legitimate user and minimize the SINR of the eavesdropper. Numerical results show that, even with a small number of antennas, the proposed beamforming scheme can effectively degrade the performance of eavesdroppers near the legitimate user.

Performance Comparison of Relay-Based Covert Communications: DF, CF and AF.

In this paper, we investigate the performance of covert communications in different types of a relay system: decode-and-forward (DF), compress-and-forward (CF) and amplify-and-forward (AF). We consider a source node that attempts to send both public and covert messages to a destination node through a relay on which a covert message detector is embedded. By taking the minimum detection error probability (DEP) at the relay into account, we optimize the power distribution between the public and covert messages to achieve the maximum covert rate. We further make a delay-aware comparison among DF, CF and AF relay systems with the obtained closed-form covert rates and conduct an extensive examination on the asymptotic behaviors in different limits. Our analyses reveal that CF or AF tend to outperform DF for high source transmit power or low relay transmit power, while various system parameters such as the processing delay, minimum required quality of service for public messages and DEP threshold lead to different performance relationships among DF, CF and AF for high relay transmit power. Numerical results verify our investigation into the performance comparison in various channel models.

Information Leakage Rate of Optical Code Division Multiple Access Network Using Wiretap Code.

Secrecy capacity is usually employed as the performance metric of the physical layer security in fiber-optic wiretap channels. However, secrecy capacity can only qualitatively evaluate the physical layer security, and it cannot quantitatively evaluate the physical layer security of an imperfect security system. Furthermore, secrecy capacity cannot quantitatively evaluate the amount of information leakage to the eavesdropper. Based on the channel model of an optical CDMA network using wiretap code, the information leakage rate is analyzed to evaluate the physical layer security. The numerical results show that the information leakage rate can quantitatively evaluate the physical layer security of an optical CDMA wiretap channel, and it is related to transmission distance, eavesdropping position, confidential information rate and optical code.

Physical Layer Security: Channel Sounding Results for the Multi-Antenna Wiretap Channel.

Many physical-layer security works in the literature rely on purely theoretical work or simulated results to establish the value of physical-layer security in securing communications. We consider the secrecy capacity of a wireless Gaussian wiretap channel using channel sounding measurements to analyze the potential for secure communication in a real-world scenario. A multi-input, multi-output, multi-eavesdropper (MIMOME) system is deployed using orthogonal frequency division multiplexing (OFDM) over an 802.11n wireless network. Channel state information (CSI) measurements were taken in an indoor environment to analyze time-varying scenarios and spatial variations. It is shown that secrecy capacity is highly affected by environmental changes, such as foot traffic, network congestion, and propagation characteristics of the physical environment. We also present a numerical method for calculating MIMOME secrecy capacity in general and comment on the use of OFDM with regard to calculating secrecy capacity.

Security-Reliability Analysis of AF Full-Duplex Relay Networks Using Self-Energy Recycling and Deep Neural Networks.

This paper investigates the security-reliability of simultaneous wireless information and power transfer (SWIPT)-assisted amplify-and-forward (AF) full-duplex (FD) relay networks. In practice, an AF-FD relay harvests energy from the source (S) using the power-splitting (PS) protocol. We propose an analysis of the related reliability and security by deriving closed-form formulas for outage probability (OP) and intercept probability (IP). The next contribution of this research is an asymptotic analysis of OP and IP, which was generated to obtain more insight into important system parameters. We validate the analytical formulas and analyze the impact on the key system parameters using Monte Carlo simulations. Finally, we propose a deep learning network (DNN) with minimal computation complexity and great accuracy for OP and IP predictions. The effects of the system's primary parameters on OP and IP are examined and described, along with the numerical data.

Secrecy Performance Analysis of Cooperative Multihop Transmission for WSNs under Eavesdropping Attacks.

Multihop transmission is one of the important techniques to overcome the transmission coverage of each node in wireless sensor networks (WSNs). However, multihop transmission has a security issue due to the nature of a wireless medium. Additionally, the eavesdropper also attempts to interrupt the legitimate users' transmission. Thus, in this paper, we study the secrecy performance of a multihop transmission under various eavesdropping attacks for WSNs. To improve the secrecy performance, we propose two node selection schemes in each cluster, namely, minimum node selection (MNS) and optimal node selection (ONS) schemes. To exploit the impact of the network parameters on the secrecy performance, we derive the closed-form expression of the secrecy outage probability (SOP) under different eavesdropping attacks. From the numerical results, the ONS scheme shows the most robust secrecy performance compared with the other schemes. However, the ONS scheme requires a lot of channel information to select the node in each cluster and transmit information. On the other side, the MNS scheme can reduce the amount of channel information compared with the ONS scheme, while the MNS scheme still provides secure transmission. In addition, the impact of the network parameters on the secrecy performance is also insightfully discussed in this paper. Moreover, we evaluate the trade-off of the proposed schemes between secrecy performance and computational complexity.

Physical Layer Authenticated Image Encryption for IoT Network Based on Biometric Chaotic Signature for MPFrFT OFDM System.

In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the multi-parameter fractional Fourier transform-Orthogonal frequency division multiplexing (MP-FrFT-OFDM) is suggested for secure image transmission over the IoT network. In addition, a new robust multi-cascaded chaotic modular fractional sine map (MCC-MF sine map) is designed and analyzed. Also, a new dynamic chaotic biometric signature (DCBS) generator based on combining the biometric signature and the proposed MCC-MF sine map random chaotic sequence output is also designed. The final output of the proposed DCBS generator is used as a dynamic secret key for the MPFrFT OFDM system in which the encryption process is applied in the frequency domain. The proposed DCBS secret key generator generates a very large key space of 22200. The proposed DCBS secret keys generator can achieve the confidentiality and authentication properties. Statistical analysis, differential analysis and a key sensitivity test are performed to estimate the security strengths of the proposed DCBS-MP-FrFT-OFDM cryptosystem over the IoT network. The experimental results show that the proposed DCBS-MP-FrFT-OFDM cryptosystem is robust against common signal processing attacks and provides a high security level for image encryption application.

Analysis of the Mutual Information of Channel Phase Observations in Line-of-Sight Scenarios.

The mutual information of the observed channel phase between devices can serve as an entropy source for secret key generation in line-of-sight scenarios. However, so far only simulated and numeric results were available. This paper derives the probability distribution of the channel phase and corresponding expressions for the mutual information. Moreover, the orientation distribution is optimized in order to maximize the mutual information. All presented results are validated numerically. These outcomes serve as a basis for further analytic investigations on the secret key generation rate and subsequent physical layer security performance analysis in line-of-sight scenarios, such as those encountered in drone-aided communications.

Security- and Reliability-Guaranteed Transmission Control of Time-Sensitive Physical Layer Security Systems.

In this paper, we consider information transmission over a three-node physical layer security system. Based on the imperfect estimations of the main channel and the eavesdropping channel, we propose reducing the outage probability and interception probability by hindering transmissions in cases where the main channel is too strong or too weak, which is referred to as an SNR-gated transmission control scheme. Specifically, Alice gives up its chance to transmit a packet if the estimated power gain of the main channel is smaller than a certain threshold so that possible outages can be avoided; Alice also becomes silent if the estimated power gain is larger than another threshold so that possible interceptions at Eve can be avoided. We also consider the timeliness of the network in terms of the violation probability of the peak age of information (PAoI). We present the outage probability, interception probability, and PAoI violation probability explicitly; we also investigate the trade-off among these probabilities, considering their weight sum. Our numerical and Monte Carlo results show that by using the SNR-gated transmission control, both the outage probability and the interception probability are reduced.