Covert communication has sparked widespread attention since it seeks to secure potentially undetected transmissions by employing a variety of confusion sources. Despite the highly directed nature of Terahertz (THz) beams, receiver vibration causes beam direction misalignment, lowering communication speeds, and reducing communication covertness. In this research, we present and analyze a resilient reconfigurable intelligent surface (RIS)-aided covert transmission scheme for THz transmissions, in which a multi-antenna node transmits to both a covert user and a public user in the presence of an unfriendly warden, under both perfect and imperfect channel state information assumptions. The proposed approach is based on superimposing the two legitimate users’ signals, confusing the warden node’s detection. Closed-form expressions for the optimal detection threshold at the warden, detection error probability (DEP), and minimum DEP (MDEP) are provided. Simulation findings corroborate the analytical results, and insightful discussions on the monotonicity of the main metrics and their impact on the system’s covertness are included. Then, using an alternating optimization (AO)-based framework, an optimal design of the power allocated to each user’s signal, their respective beamforming vectors, and the RIS phase shifts is carried out to maximize the system’s achievable communication rate subject to power constraints and an MDEP threshold at the warden. The convexity of all intermediate subproblems has been thoroughly examined, and the covertness advantage of the proposed approach has been proven.

Integrated sensing and communication (ISAC) has recently emerged as a viable technique for establishing sensing and communication using the same resources. Nonetheless, the operation of ISAC networks is often challenged by the absence of a direct link between the sensing node and the targets, and by the risk of disclosing confidential data to malicious targets when using the same signal for both tasks. In this paper, a robust reconfigurable intelligent surface (RIS)-aided scheme for securing a full-duplex (FD) ISAC network is proposed. The considered network consists of uplink and downlink users served in FD through a multi-antenna dual-functional radar communication base station (BS), which employs co-located multi-antenna communication-radar arrays to detect multiple malicious targets while preserving communication secrecy in their presence. Additionally, the BS utilizes an optimized artificial noise (AN) that serves to disrupt the malicious targets’ reception and increase the sensing illumination power. By optimally designing the RIS phase shifts, transmit beamforming matrix, AN covariance matrix, and uplink users’ transmit power and combining vectors using an alternating optimization-based algorithm, the network’s sensing performance is maximized under secrecy and total power constraints. Numerical results present the proposed scheme’s efficacy, particularly when a direct link between the BS and the various nodes/targets is absent.

In this paper, a robust pinching antenna-based scheme for ensuring secure wireless communication systems is proposed. In the presence of several malicious eavesdroppers targeting the legitimate signal of various genuine users, the designed approach exploits the spatial flexibility of a pinchingantennas system (PAS) composed of several waveguides and pinching antennas to provide secure communication to legitimate nodes. In particular, multiple pinching antennas can be positioned in each waveguide spanning a long distance, providing additional degrees of freedom and flexibility to adjust the channel response with respect to the various users and eavesdroppers. By virtue of semidefinite programming, an optimization problem aiming at optimizing the transmit beamforming to minimize the total transmit power, subject to secrecy constraints, is formulated and solved. The obtained results demonstrate the total transmit power reduction by increasing the number of antennas and waveguides subject to the same secrecy constraints. Furthermore, the proposed scheme outperforms the benchmark one, consisting of an array of co-located transmit antennas at the base station, when either a direct link from the latter to the users is blocked or when the eavesdroppers are located in the line of sight of the legitimate users.

In this paper, a robust and secure cooperative integrated sensing and communication (ISAC) scheme is proposed and analyzed. The considered scheme exploits multiple dual-functional radar communication (DFRC) base stations (BSs) in order to (i) better illuminate the sensed environment and increase the target detection performance, and (ii) ensure secure communication with respect to several malicious targets. The cluster of cooperating BSs beamform the confidential signals beams to the receiving legitimate users as well as an artificial noise (AN) signal to the set of malicious targets, whereby the AN signal is designed for sensing malicious targets and safeguarding confidential signals from being leaked to the latter nodes, acting as eavesdroppers. By optimizing the transmit beamforming and AN covariance matrices at each of the DFRC BSs, the network’s sensing performance is maximized subject to a minimal secrecy capacity and power constraints. The obtained results demonstrate the proposed cooperative ISAC scheme’s potential in enhancing the sensing performance compared to the baseline (i) single-BS DFRC-ISAC scheme and (ii) cooperative DFRC-ISAC employing a zero-forcing beamforming.

In this paper, a robust reconfigurable intelligent surface (RIS)-aided carrier frequency offset (CFO)-based physical layer authentication (PLA) scheme for wireless networks is proposed. The considered network consists of a legitimate transmitter, a spoofer, and a receiver, acting as an authenticator, who aims to identify the sender's legitimacy relying on the estimated CFO from received signals. Thus, the proposed scheme exploits an RIS to increase the received signal-to-noise ratio (SNR) and enhance the authentication performance. A deep reinforcement learning framework is developed to jointly optimize the RIS phase shifts and the preamble length to maximize the authentication performance under a minimal channel capacity constraint. Then, a supervised machine learning classifier is employed for node authentication, exploiting the optimized RIS reflection and preamble length. The results show that the authentication performance is enhanced with the increase in the RIS size and the difference between the transmitters' CFOs. Also, the proposed scheme outperforms the baseline RIS-aided CSI-based one in mobility scenarios.

In this paper, a robust enhanced Sybil attack detection scheme is proposed using both the Doppler shift and received signal strength (RSS) as physical layer parameters to identify Sybil nodes in a mobile network. The proposed scheme employs the absolute value of the difference between Doppler shift and RSS values for all pairs of nodes as test statistics, where threshold-based statistical hypothesis testing is performed to detect Sybil nodes. A performance evaluation of the scheme is provided in terms of its true positive rate (TPR) and false positive rate (FPR), and where an approximate expression for both metrics is provided for the particular two-user case. The proposed scheme yields a significant security enhancement compared to its single-attribute Doppler shift- and RSS-based schemes, where the proposed scheme's TPR manifests an increase surpassing 32% and 255%, with respect to the two aforementioned schemes, respectively. The performance evaluation shows the potential of incorporating multiple channel-based features for a robust Sybil attack detection scheme in mobile networks.

In this article, a robust reconfigurable intelligent surface (RIS)-aided physical layer authentication (PLA) scheme is proposed. The designed scheme leverages carrier frequency offset (CFO) as a hardware-based attribute for authentication and RIS’s reflective elements tunability to ensure an enhanced received signal-to-noise ratio at the authenticator in a wireless mesh network, resulting in improved authentication performance. Under the presence of a malicious eavesdropper in the network, and by leveraging semidefinite programming, the RIS phase-shifting optimization problem is solved, where a near-optimal RIS configuration maximizing the authentication performance (mitigating impersonation attacks) while fulfilling a minimal secrecy capacity (SC) value with respect to the eavesdropping attack is obtained. The obtained results show an enhanced authentication performance by the increase in the RIS size or the CFO difference between the pair of legitimate and illegitimate transmitters. Furthermore, it is shown that the proposed scheme achieves an authentication-confidentiality performance balance where the proposed scheme outperforms the benchmark one, maximizing the SC, in terms of authentication performance at the cost of a certain SC loss.

In this paper, a robust machine learning (ML)-based scheme for Sybil attack detection in mobile networks is proposed. The proposed scheme exploits three physical-layer features, namely the Doppler shift, received signal strength (RSS), and channel state information (CSI) for identifying Sybil nodes. By employing a Bayesian optimization method, an optimized Random Forest ML classifier is utilized for the classification phase by exploiting the estimated and processed physical-layer attributes, yielding an efficient node classification and Sybil attack detection in a mobile network. A thorough performance evaluation of the proposed scheme is performed in terms of its receiver operating characteristic (ROC) curve, demonstrating higher node classification accuracy gains. Furthermore, the proposed scheme outperforms its benchmark schemes, namely the single- and dual-attribute schemes and the three-features hypothesis-based one. Specifically, the proposed scheme improves the true positive rate (TPR) by 12.5% compared to its dual-feature RSS-Doppler shift-based counterpart, and enhances the Doppler shift-, RSS-, and CSI-based single-attribute ones by 216%, 137%, and 36%, respectively, in terms of the TPR.

The Internet of Things (IoT) is a popular technology that refers to a network of internet-connected physical devices that interact to perform tasks with minimal human intervention. However, as these networks expand, ensuring their security becomes challenging due to the communication broadcasting nature and extensive data exchanges. Traditional cryptographic security methods may not be optimal due to the constrained resources of loT devices. In this study, we propose a novel secure key distribution scheme from a physical layer perspective suitable for an loT environment. The proposed scheme takes advantage of the availability of Channel State Information (CSI) at both ends of the communication to enhance security. Specifically, CSI is utilized to precode the key symbols during the key distribution process. Additionally, the scheme employs the xor operation to add an extra layer of difficulty for potential eavesdroppers that attempt to retrieve the transmitted key symbols. The performance of the proposed scheme is evaluated in terms of Key Error Rate (KER) at legitimate nodes and eavesdroppers by using Monte Carlo simulations.

The pervasiveness of the Internet of Things (IoT) in our daily lives has been remarkably increasing over the past years. Due to their massive connectivity and limited resources, ensuring decent security levels for these networks has been challenging. In this article, a novel and efficient physical layer key exchange scheme for IoT devices is proposed. The proposed scheme leverages on the well-known index modulation (IM) technique for the key exchange process by exploiting IM-based selected carrier frequency indices at the legitimate transceiver pairs (i.e., Alice and Bob) to exchange key symbols. Additionally, a random power level selection along with channel precoding is performed for each symbol transmission to enhance the secrecy level against potential eavesdroppers. The performance of the proposed scheme is analyzed based on the upper-bound expression for the key error probability (KEP) metric. As compared to the benchmark scheme, results reveal a promising performance in the KEP, where a minimum of 10 dBW can be gained at the legitimate node, while the KEP at the eavesdropper is kept close to one regardless of its channel conditions. Moreover, extensive numerical results corroborate the accuracy of the derived mathematical framework and endorse the proposed scheme’s robustness under the existence of a smart and powerful adversarial node.

In this paper, we propose a Deep Reinforcement Learning (DRL) framework to optimize the secrecy performance of a Multi-User (MU)-Multiple-Input Single-Output (MISO) Underwater Optical Wireless Communication (UOWC) system. The network consists of several light-emitting diodes connected with various underwater users through optical beams. The legitimate transmission is threatened by several eavesdroppers attempting to overhear the confidential message sent to each user. Thus, digital precoding is employed to cancel the inter-user interference and maximize the per-user secrecy rate and, consequently, the secrecy sum rate (SSR). Leveraging the developed DRL algorithm, the MU-MISO precoding matrix is optimized for enhancing the system's SSR. Numerical results show the superiority of the proposed DRL framework compared to the baseline zero-forcing and random pre coding schemes, even with corrupted CSI at the transmitter due to seawater dynamics and estimation errors.

In this paper, the secrecy of a dual-hop unmanned aerial vehicle-based wireless communication system, in the presence of mobility and imperfect channel state information (CSI), is investigated. The system consists of a decode-and-forward relay connecting a source and destination node. The transmission is performed under the presence of two eavesdroppers aiming to intercept independently the source-relay and source-destination communication channels. It is assumed that the transmitters are equipped with one transmit antenna, while the receivers have multiple receive antennas. Based on the statistical properties of the per-hop signal-to-noise ratio (SNR), a closed-form formula for the network’s secrecy intercept probability (IP) is derived, in terms of the main system and channel parameters. The results correlate the impact of such parameters on the secrecy level of the system, where the latter can be enhanced by increasing the number of antennas at the legitimate receivers and the average SNRs of the legitimate links. Furthermore, it is shown that as the CSI imperfection level, nodes’ speed, delay, and carrier frequency increase, the system’s secrecy degrades. All the derived results are verified through Monte Carlo simulations.

In this work, we investigate the secrecy performance of reconfigurable intelligent surfaces (RIS)-aided network consisting of two legitimate nodes (i.e., transmitter and receiver) and several passive eavesdroppers. A RIS is installed between the legitimate transmitter and receiver to enhance the received signal quality and, consequently, increase the achievable secrecy rates. Furthermore, we consider a multi-antenna legitimate receiver combining the received signal copies, reaching via the RIS, using the maximal-ratio combining technique. In addition, we assume the presence of a friendly jammer that aims at degrading the eavesdroppers’ links quality. We propose two RIS phase shift configuration strategies, where the RIS is either aligned to the channel of the antenna with the best cascaded channel quality or to a randomly-selected one’s channel. An approximate expression for the system’s secrecy outage probability (SOP) is provided for the second strategy, while extensive numerical simulation results are provided for both proposed schemes, showing the superiority of the former strategy in terms of SOP performance for different values of the number of reflective elements, legitimate receiver antennas, and eavesdroppers.

Guaranteeing decent secrecy levels in future wireless network generations has gained crucial importance due to the unprecedented increase in wireless connectivity worldwide. In this paper, an enhanced hybrid channel/device-based physical layer authentication (PLA) scheme is proposed. The channel state information (CSI) and device-dependent carrier frequency offset (CFO) are employed to discriminate various malign and benign devices in a wireless network. In particular, CSI-based hypothesis testing (HT) is applied initially on the received authentication requests of several unknown transmitters, relying on legitimate CSI values from previous transmissions to classify such nodes. Then, a second stage takes place using the CFO HT on either the interval containing misclassified legitimate or illegitimate nodes to improve the initial stage’s classification results. Approximate expressions for the authentication and detection probabilities are retrieved, whose tightness is endorsed by extensive Monte Carlo simulations. Results show that the proposed scheme enhances the single-attribute PLA performance (CSI-and CFO-based). Also, the authentication probability improves by the increase in the average legitimate signal-to-noise ratio (SNR) and lower nodes’ speed. In addition, the detection probability rises at high legitimate and intruder links SNRs, while it degrades for low SNR (i.e., noisy attributes observations). Lastly, the more significant the difference between the actual malign and benign nodes’ CFOs, the better the detection probability.

In this article, the physical-layer security of a dual-hop unmanned aerial vehicle-based wireless network, subject to imperfect channel state information (CSI) and mobility effects, is analyzed. Specifically, a source node$(S)$communicates with a destination node$(D)$through a decode-and-forward relay$(R)$, in the presence of two wiretappers$(E_{1}$and$E_{2}$) independently trying to compromise the two hops. Furthermore, the transmit nodes$(S,R) $have a single transmit antenna, while the receivers$(R,D,E_{1},E_{2}) $are equipped with multiple receive antennas. Based on the per-hop signal-to-noise ratios (SNRs) and correlated secrecy capacities’ statistics, a closed-form expression for the secrecy intercept probability (IP) metric is derived, in terms of key system parameters. Additionally, asymptotic expressions are revealed for two scenarios, namely: 1) mobile nodes with imperfect CSI and 2) static nodes with perfect CSI. The results show that a zero secrecy diversity order is manifested for the first scenario, due to the presence of a ceiling value of the average SNR, while the IP drops linearly at high average SNR in the second one, where the achievable diversity order depends on the fading parameters and number of antennas of the legitimate links/nodes. Furthermore, for static nodes, the system can be castigated by a 15-dB secrecy loss at IP$=3\times 10^{-3}$, when the CSI imperfection power raises from 0 to 10−3. Finally, the higher the legitimate nodes’ speed, carrier frequency, delay, and/or relay’s decoding threshold SNR, the worse is the system’s secrecy. Monte Carlo simulations endorse the derived analytical results.

Ensuring physical layer security is a crucial task in conventional and emerging communication systems, which are typically characterized by stringent quality of service and security requirements. This also accounts for wireless technologies in the context of the Internet of Things paradigm, which are expected to exhibit considerably increased computational complexity. Based on this, the present contribution investigates the secrecy outage performance of a dual-hop decode-and-forward (DF) mixed radio-frequency/ underwater optical wireless communication (RF/UOWC) system. Such wireless network configurations are particularly useful in efficient and demanding scenarios, such as military communications. Therefore, our analysis considers one single-antenna source node (S) communicating with one legitimate destination node (D) via a DF relay node (R) equipped with multiple antennas for reception. Particularly, the relay receives the incoming signal from S via an RF link, applies selection-combining (SC) technique, fully decodes it, re-encodes it, and then forwards it to the destination via a UOWC link. The communication is performed under the eavesdropper's attempt to intercept the S - R hop (RF side). In this context, a closed-form expression for the secrecy outage probability is derived along with a thorough asymptotic analysis in the high SNR regime, based on which the achievable diversity order is provided. The offered results provide useful insights on the impact of some key system and channel parameters on the secrecy outage performance, such as the number of eavesdroppers, the number of relay antennas, fading severity parameters of RF links, and water turbulence severity of the UOWC link. The conducted analysis shows that the secrecy outage probability is dominated only by the R-D link in the high SNR regime, regardless of the S-R parameters, such as the number of relay antennas and the average SNR at the relay branches. The offered analytic results are corroborated with respective results from computer simulations. Since these parameters are closely related with the computational complexity at the involved terminals, the offered insights are useful for the design and computationally sustainable operation of such systems.

In this paper, a unified performance analysis of underwater wireless communication system is presented. The radio link between the source (S) and the destination (D) is subject to κ-μ shadowed fading channel. We present an analytical closed-form expression for the cumulative distribution function (CDF) and the probability density function (PDF) of the total end-to-end SNR in terms of the Kummer's Hypergeometric function. Based on these results, we present exact closed-form expressions of communication system performance criteria, such as outage probability (OP) and average bit/symbol error rate (ABER/ASER) with their respective asymptotic expansion, at both low and high SNR regimes, expressed in terms of basic elementary functions. All the derived analytical expressions are validated through computer-based simulation.

This work presents a study on the performance of a hybrid 5G RF/FSO communication system. Both transmitter and receiver communicate through two paths: the first link operates under Radio-Frequency (RF) technology, assumed to undergo a Weibull fading channel, while the second link operates under Free Space Optical (FSO) technology, subject to Málaga-M turbulence model with the presence of pointing error impairment. Both incoming signals are combined at the receiver side using Maximal Ratio Combining (MRC) technique. We retrieve, in particular, the Moment Generating Function (MGF) of the total Signal-toNoise Ratio (SNR). Based on that, we present the exact closedform expression of the Average Symbol Error Rate (ASER) of the considered RF/FSO system for different modulations schemes in terms of the bivariate Fox's H-Function.