Legitimate Transmitter Research Articles

Performance Analysis of Artificial-Noise-Based Secure Transmission in Wiretap Channel

Artificial noise (AN)-aided techniques have been considered to be promising and practical candidates for enhancing physical layer security. However, there has been a lack of analysis regarding the AN effect on the eavesdropper (EV) from the perspective of the signal-to-interference plus noise ratio (SINR) regarding the existence of the EV’s channel state information (CSI) at the legitimate transmitter. In this paper, we analyze the performance of AN-aided secure transmission from the SINR perspective when a legitimate transmitter has and does not have the EV’s CSI. Based on the analyzed EV’s SINRs for the above two cases, the secrecy gap, which is the difference between the two secrecy capacities, is defined and analyzed. Based on the derived secrecy gap, we have analyzed the asymptotic performances of the secrecy capacity and gap when the number of antennas of the legitimate transmitter and the number of antennas of the EV have large values. Through asymptotic analysis, it is demonstrated that the AN-aided secure transmission under the practical environment (i.e., the case that the EV’s CSI is not available at the legitimate transmitter) can nearly achieve an ideal performance (i.e., the performance when the EV’s CSI is available at the legitimate transmitter) in a massive antenna system.

Quantum PSO-Based Optimization of Secured IRS-Assisted Wireless-Powered IoT Networks

In this paper, we explore intelligent reflecting surface (IRS)-assisted physical layer security (PLS) in a wireless-powered Internet of Things (IoT) network (WPIN) by combining an IRS, a friendly jammer, and energy harvesting (EH) to maximize sum secrecy throughput in the WPIN. Specifically, we propose a non-line-of-sight system where a hybrid access point (H-AP) has no direct link with the users, and a secure uplink transmission scheme utilizes the jammer to combat malicious eavesdroppers. The proposed scheme consists of two stages: wireless energy transfer (WET) on the downlink (DL) and wireless information transmission (WIT) on the uplink (UL). In the first phase, the H-AP sends energy to users and the jammer, and they then harvest energy with the help of the IRS. Consequently, during WIT, the user transmits information to the H-AP while the jammer emits signals to confuse the eavesdropper without interfering with the legitimate transmission. The phase-shift matrix of the IRS and the time allocation for DL and UL are jointly optimized to maximize the sum secrecy throughput of the network. To tackle the non-convex problem, an alternating optimization method is employed, and the problem is reformulated into two sub-problems. First, the IRS phase shift is solved using quantum particle swarm optimization (QPSO). Then, the time allocation for DL and UL are optimized using the bisection method. Simulation results demonstrate that the proposed method achieves significant performance improvements as compared to other baseline schemes. Specifically, for IRS elements N = 35, the proposed scheme achieves a throughput of 19.4 bps/Hz, which is 85% higher than the standard PSO approach and 143% higher than the fixed time, random phase (8 bps/Hz) approach. These results validate the proposed approach’s effectiveness in improving network security and overall performance.

Covert communications in STAR-RIS-aided rate-splitting multiple access systems

In this paper, an simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is deployed in the downlink rate-splitting multiple access (RSMA) covert system to enhance the covert communication performance. According to the RSMA transceiver mechanism, the messages for the covert user (Bob) and public user (Grace) are converted to the common and private streams at the legitimate transmitter (Alice) to realize downlink transmissions, while the STAR-RIS not only assists Alice in transmitting public messages to Grace but also protects the covert messages Alice sends to Bob by mixing up Warden (Willie). To characterize the covert performance of the considered STAR-RIS-aided RSMA (STAR-RIS-RSMA) system, We derive a closed expression for its detection error probability in the most favorable case for Willie, based on which a covert rate maximization problem is formulated. To maximize Bob’s covert rate while confusing Willie’s monitoring, the power allocation factor, common rate allocation factor, and STAR-RIS reflection/transmission beamforming are jointly optimized subject to Grace’s quality of service (QoS) requirements. The complex non-convex problem of maximizing covert rate, involving coupled system parameters, thus is split into three separate sub-issues: the allocation of transmit power, allocation of common rates, and STAR-RIS reflection/transmission beamforming, respectively. To obtain the rank-one constrained optimal solution for the sub-problem of optimizing the STAR-RIS reflection/transmission beamforming, a penalty-based successive convex approximation scheme is developed. Moreover, an alternative optimization (AO) algorithm is designed to determine the optimal solution for the sub-problem of optimizing the transmit power allocation, while the original problem is overall solved by a new AO algorithm. Simulation results corroborate the accuracy of the derived analytical results and demonstrate that the proposed STAR-RIS-RSMA scheme outperforms the benchmark scheme in achieving the covert rate.

A RNN-based approach to physical layer authentication in underwater acoustic networks with mobile devices

Underwater acoustic communications are becoming a popular solution for underwater data communications and telemetry, making the authentication of transmitted data a necessity. In this paper, we propose a physical-layer authentication strategy for underwater acoustic networks (UWANs) with mobile devices. Such a scenario is more challenging than classical authentication scenarios in static networks, because the mobility of the receiver and/or transmitter implies that channel conditions slowly change over time. Thus, we cannot rely on the statistics of channel features to be stationary. In our proposed strategy, we assume that the receiver can rely on a set of sensors. We first extract a set of channel features, to be used to track the channel evolution over time. We then develop a long short-term memory (LSTM)-based approach, where at each step the sensors predict future feature values based on a learned model and on previously observed feature values. Next, each sensor computes the prediction error and passes it on to the actual receiver, which makes a decision on the signal authenticity through a generalized likelihood ratio test (GLRT). We model different classes of attacks and test them using simulation data obtained via the Bellhop ray tracing software. Numerical results show that our authentication mechanism successfully distinguishes between legitimate and impersonating transmitters, even when considering challenging attacking scenarios where the attacker can successfully mimic the channels between the legitimate transmitter and the sensors.

Energy-efficient trajectory design for secure SWIPT systems assisted by UAV-IRS

Due to its controllable maneuverability, wide coverage, and low cost, unmanned aerial vehicle (UAV) has great potential in post-disaster rescue, cargo transport and emergency communication. Considering its limited onboard energy, energy-efficient UAV communication is a challenge. This research examines the security of simultaneous wireless information and power transfer (SWIPT) systems assisted by intelligent reflecting surfaces (IRS) and UAVs while considering the flight energy of rotary-wing UAVs. Specifically, an IRS is mounted on a UAV to enhance the quality of legitimate transmission, and artificial noise (AN) is introduced into the base station (BS) to reduce eavesdropping quality. The power splitting (PS) technology is adopted at ground devices (GDs) to simultaneously decode information and harvest energy. First, we jointly design the BS transmit beamforming, UAV-IRS phase shifts and trajectory/velocity as well as GDs PS ratio with the aim of maximizing the sum secrecy rate of all GDs. Then, an iterative algorithm is developed to address the formulated problem. In particular, additional variables are introduced to handle this complicated objective function, and the original problem is decoupled into multiple sub-problems, which can be solved alternately by invoking the successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques. Finally, numerical results demonstrate that the proposed scheme exhibits a substantial performance in the security rate of SWIPT systems assisted by UAV-IRS, and its performance is improved by at least 12% compared to benchmark schemes at the flight energy budget ethr=5KJ and the number of reflecting elements Nr=25.

National sovereignty and the spirit of the right to vote

The right to vote is one of the exclusively fundamental political rights through the application of which the citizen exercises sovereign power. And the right to vote, like any other phenomenon, is characterized by the organic unity between form and content - spirit.In this article, we intend to scientifically argue this connection, given that the exercise of the right to vote and its implementation is the only legal and legitimate transmission belt for the exercise of National Sovereignty through representation.

Aerial Bridge: A Secure Tunnel Against Eavesdropping in Terrestrial-Satellite Networks

Terrestrial-satellite networks (TSNs) can provide worldwide users with ubiquitous and seamless network services. Meanwhile, malicious eavesdropping is posing tremendous challenges on secure transmissions of TSNs due to their widescale wireless coverage. In this paper, we propose an aerial bridge scheme to establish secure tunnels for legitimate transmissions in TSNs. With the assistance of unmanned aerial vehicles (UAVs), massive transmission links in TSNs can be secured without impacts on legitimate communications. Owing to the stereo position of UAVs and the directivity of directional antennas, the constructed secure tunnel can significantly relieve confidential information leakage, resulting in the precaution of wiretapping. Moreover, we establish a theoretical model to evaluate the effectiveness of the aerial bridge scheme compared with the ground relay, non-protection, and UAV jammer schemes. Furthermore, we conduct extensive simulations to verify the accuracy of theoretical analysis and present useful insights into the practical deployment by revealing the relationship between the performance and other parameters, such as the antenna beamwidth, flight height and density of UAVs.

Learning-Based Multi-Domain Anti-Jamming Communication with Unknown Information

Due to the open nature of the wireless channel, wireless networks are vulnerable to jamming attacks. In this paper, we try to solve the anti-jamming problem caused by smart jammers, which can adaptively adjust the jamming channel and the jamming power. The interaction between the legitimate transmitter and the jammers is modeled as a non-zero-sum game. Considering that it is challenging for the transmitter and the jammers to acquire each other’s information, we propose two anti-jamming communication schemes based on the Deep Q-Network (DQN) algorithm and hierarchical learning (HL) algorithm to solve the non-zero-sum game. Specifically, the DQN-based scheme aims to solve the anti-jamming strategies in the frequency domain and the power domain directly, while the HL-based scheme tries to find the optimal mixed strategies for the Nash equilibrium. Simulation results are presented to validate the effectiveness of the proposed schemes. It is shown that the HL-based scheme has a better convergence performance and the DQN-based scheme has a higher converged utility of the transmitter. In the case of a single jammer, the DQN-based scheme achieves 80% of the transmitter’s utility of the no-jamming case, while the HL-based scheme achieves 63%.

Leaking Wireless ICs via Hardware Trojan-Infected Synchronization

We propose a Hardware Trojan (HT) attack in wireless Integrated Circuits (ICs) that aims at leaking sensitive information within a legitimate transmission. The HT is hidden inside the transmitter modulating the sensitive information into the preamble of each transmitted frame which is used for the synchronization of the transmitter with the receiver. The data leakage does not affect synchronization and is imperceptible by the inconspicuous nominal receiver as it does not incur any performance penalty in the communication. A knowledgeable rogue receiver, however, can recover the data using signal processing that is too expensive and impractical to be used during run-time in nominal receivers. The HT mechanism is designed at circuit-level and is embedded entirely into the digital section of the RF transceiver having a tiny footprint. The proposed HT attack is demonstrated with measurements on a hardware platform. We demonstrate the stealthiness of the attack, i.e., its ability to evade defenses based on testing and run-time monitoring, and the robustness of the attack, i.e., the ability of the rogue receiver to recover the leaked information even under unfavorable channel conditions.

Covert Transmission and Secrecy Analysis of RS-RIS-NOMA-Aided 6G Wireless Communication Systems

In this work, we investigate a novel covert communication system, where the legitimate transmitter attempts to communicate with a covert user in the presence of a warden and the public user covertly. Specifically, the legitimate transmitter employs non-orthogonal multiple access (NOMA) and rate-splitting (RS) to communicate with users aided by a reconfigurable intelligent surface (RIS). In this context, we investigate key performance indicators of covert communication, namely the detection error probability and the covert communication rate. Meanwhile, we consider the physical layer security (PLS) of the proposed system in the presence of an eavesdropper, and derive the approximate secrecy outage probability (SOP) expression. Also, an asymptotic analysis of the SOP is also carried out. Various numerical results are presented that demonstrate the usefulness of the proposed analysis, which are complemented by simulated ones, verifying the correctness of the theoretical framework. From these results, it becomes evident that the use of RS, NOMA, and RIS can improve the performance of covert communication. Finally, it is also depicted that under the condition of high signal-to-noise ratio, the SOP of the system tends to be a constant value.

Secure Hybrid Beamforming for IRS-Assisted Millimeter Wave Systems

This paper investigates the secure hybrid beamforming (HB) design in an intelligent reflecting surface (IRS) assisted millimeter-wave (mmWave) system, where an IRS is deployed to help the legitimate transmission from Alice to Bob under the eavesdropping of Eve. To protect the legitimate transmission, Alice employs HB to send both the information signal and the artificial noise, while the IRS employs passive beamforming (PB) to reconstruct the wireless environment. Aiming at the secrecy capacity (SC) maximization, the joint optimization of HB and PB is formulated as a non-convex problem with constant-modulus constraints. To efficiently solve such a challenging problem, the original problem is decomposed into a PB subproblem and an HB subproblem, then these subproblems are sequentially solved by the proposed algorithms. Particularly, for the PB subproblem, we propose a channel information aided PB algorithm, which is proved to converge at a stationary point. With the solution of PB subproblem, two algorithms are proposed for the HB subproblem: 1) near-optimal SC approaching HB algorithm that achieves a near-optimal solution; 2) low-complexity HB algorithm that achieves a slight lower SC with less computational complexity. Simulation results demonstrate the superior performance of proposed algorithms in comparison with the state-of-the-art works.

Learning-Based IRS-Assisted Secure Transmission for Mine IoTs.

Mine Internet of Things (MIoT) devices in intelligent mines often face substantial signal attenuation due to challenging operating conditions. The openness of wireless communication also makes it susceptible to smart attackers, such as active eavesdroppers. The attackers can disrupt equipment operations, compromise production safety, and exfiltrate sensitive environmental data. To address these challenges, we propose an intelligent reflecting surface (IRS)-assisted secure transmission system for an MIoT device which enhances the security and reliability of wireless communication in challenging mining environments. We develop a joint optimization problem for the IRS phase shifts and transmit power, with the goal of enhancing legitimate transmission while suppressing eavesdropping. To accommodate time-varying channel conditions, we propose a reinforcement learning (RL)-based IRS-assisted secure transmission scheme that enables MIoT device to optimize both the IRS reflecting coefficients and transmit power for optimal transmission policy in dynamic environments. We adopt the deep deterministic policy gradient (DDPG) algorithm to explore the optimal transmission policy in continuous space. This can reduce the discretization error caused by traditional RL methods. The simulation results indicate that our proposed scheme achieves superior system utility compared with both the IRS-free (IF) scheme and the IRS randomly configured (IRC) scheme. These results demonstrate the effectiveness and practical relevance of our contributions, proving that implementing IRS in MIoT wireless communication can enhance safety, security, and efficiency in the mining industry.

Intelligent deep learning‐aided future beam and proactive handoff prediction model in Unmanned Aerial Vehicle‐assisted anti‐jamming Terahertz communication system

SummaryWireless communications often suffer from legitimate transmissions regarding malicious jamming attacks launched through the smart jammer. The drone or unmanned aerial vehicle (UAV) communication networks derived with reconfigurable intelligent surfaces (RIS) increase the issues of beam selection and proactive handoff in terahertz (THz). Thus, a new heuristic strategy is designed for efficient and incorporated optimization of the beamforming vector and anti‐jamming transmit power allocation in undefined environments. Here, the transmit power allocation and beamforming matrix of UAV are optimized with the developed hybrid heuristic algorithm of the Hybrid Crow Black Widow Search Optimization (HCBWSO) algorithm for maximizing the system achievable rate. Here, the HCBWSO algorithm is implemented to integrate with the Crow search algorithm (CSO) and Black Widow Optimization (BWO). The second contribution is to adopt RIS into THz–UAV communications, a new Enhanced Deep Temporal Convolutional Network (EDTCN) for predicting the future beam and proactive handoff of UAVs based on their prior analysis of the UAV locations, where the HCBWSO algorithm is utilized for recommending EDTCN. Here, the training of the EDTCN needs to be done with the collection of UAV information from the DEEPMIMO dataset for predicting the future beams and, also, tracking the location of the UAV. EDTCN helps in increasing the possibility of expanding the UAV coverage and also increases the consistency of the THz communication system. Thus, the prediction of the future beam increases the coverage area of the UAV and also maximizes the system rate in the THz communication system.

Mode Adaptive Secure UAV Relay Transmissions

Unmanned aerial vehicles (UAV) can enhance wireless transmission security by improving the secrecy rate through relaying the legitimate transmission and injecting artificial noise to the eavesdroppers. However, due to the inherent mechanical energy consumption and the long-range signal propagation pathloss, the traditional cruising and hovering UAV relay modes are deficient in energy utilization and secrecy rate, respectively. Modeling of the secrecy energy efficiency with respect to UAV mode adaptation is limited in the literature and deserves further investigation. Therefore, in this paper, we propose a secrecy rate-energy efficient UAV relay mode adaptation scheme for secure wireless communications scenarios where the eavesdropping locations are known, i.e., the eavesdropper is a hijacked internal legitimate node. In this secure system, the UAV cooperatively assists the legitimate transmissions and injects artificial interference to the eavesdropper. We investigate optimum UAV placement and relay period planning for the hovering and the cruising relay modes, respectively. By modeling the UAV modes transfer and maximizing the secrecy energy efficiency, the optimum mode adaptation ratios are obtained under both the secrecy rate-prioritized and the energy-saving criteria. In addition, the proposed UAV relay mode adaptation mechanism is further studied for each UAV task division, to adapt to the dynamic channel variations and enhance the security. Our theoretical analysis shows that the mode adaptation ratio is determined by the secrecy rate-energy gain between the cruising and the hovering modes, and by the energy consumption threshold of the UAV relays. Our numerical results demonstrate that the proposed scheme achieves higher secrecy energy efficiency than the traditional schemes.

Secrecy Performance Analysis of Mixed-ADC/DAC Cell-Free Massive MIMO in the Presence of Multiple Eavesdroppers

This paper studies the secrecy performance of the cell-free massive multi-input multi-output (MIMO) system, where access points (APs) are equipped with a mixed analog-to-digital converter (ADC) and digital-to-analog converter (DAC) architecture. The distributed antenna structure is prone to multiple eavesdropping network threats. Specifically, legitimate transmissions can be affected by non-colluding and colluding eavesdroppers. Based on the above considerations, we determine the expressions of the sum achievable secrecy rate and secrecy energy efficiency (SEE) with applications of the additive quantization noise model and the conjugate performing precoding method. These provide the composite measures to analyze the effects of the mixed-ADC/DAC architecture on secrecy performance. We also propose a SEE-maximization power control (SEEMPC) scheme, which can be solved by the sequential convex approximation algorithm. In addition to verifying the effectiveness of the proposed SEEMPC algorithm, numerical simulations are carried out to evaluate the impact of some key design parameters, including the number of APs, quantization bit of coarse ADCs/DACs, ratio of ideal ADCs/DACs, and power control strategy.

Enhancing Physical Layer Security of Cooperative Nonorthogonal Multiple Access Networks via Artificial Noise

The massive connectivity requirement and security issues have become major factors restricting the further development of the Internet of Things. Nonorthogonal multiple access (NOMA) can be combined with physical layer security (PLS) to achieve massive connectivity and secure transmission. This article investigates the PLS performance for a downlink communication system over Nakagami-m fading channels, with full-duplex (FD) cooperative NOMA transmission aided by artificial noise (AN). While direct communication is built between the base station and two NOMA users, the strong user is employed as an FD relay as well as the jammer to enhance the PLS of the legitimate transmission in the presence of a passive eavesdropper (Eve). Closed-form analytical expressions in terms of the outage probability of the legitimate users and the intercept probability of Eve are derived to evaluate the security–reliability trade-off (SRT) of the proposed scheme. Monte Carlo simulations are provided to validate the veracity of the theoretic analyses and illustrate that the proposed scheme is superior in terms of SRT to the benchmark schemes in the low SNR region. Furthermore, the results reveal that the SRT performance of the two NOMA users can be enhanced through a proper AN-bearing ratio and power allocation optimization.

Secure beamforming designs for maximizing secrecy sum rate in MISO-NOMA networks

In this paper, the application of Non-Orthogonal Multiple Access (NOMA) is investigated in a multiple-input single-output network consisting of multiple legitimate users and a potential eavesdropper. To support secure transmissions from legitimate users, two NOMA Secrecy Sum Rate Transmit BeamForming (NOMA-SSR-TBF) schemes are proposed to maximise the SSR of a Base Station (BS) with sufficient and insufficient transmit power. For BS with sufficient transmit power, an artificial jamming beamforming design scheme is proposed to disrupt the potential eavesdropping without impacting the legitimate transmissions. In addition, for BS with insufficient transmit power, a modified successive interference cancellation decoding sequence is used to reduce the impact of artificial jamming on legitimate transmissions. More specifically, iterative algorithm for the successive convex approximation are provided to jointly optimise the vectors of transmit beamforming and artificial jamming. Experimental results demonstrate that the proposed NOMA-SSR-TBF schemes outperforms the existing works, such as the maximized artificial jamming power scheme, the maximized artificial jamming power scheme with artificial jamming beamforming design and maximized secrecy sum rate scheme without artificial jamming beamforming design.

Joint Secure Transmit Beamforming Designs for Integrated Sensing and Communication Systems

Integrated sensing and communication (ISAC), which allows individual radar and communication systems to share the same spectrum bands, is an emerging and promising technique for alleviating spectrum congestion problems. In this paper, we investigate how to exploit the inherent interference from strong radar signals to ensure the physical layer security (PLS) for the considered multi-user multi-input single-output (MU-MISO) communication and colocated multi-input multi-output (MIMO) radar coexistence system. In particular, with known eavesdroppers' channel state information (CSI), we propose to jointly design the transmit beamformers of communication and radar systems to minimize the maximum eavesdropping signal-to-interference-plus-noise ratio (SINR) on multiple legitimate users, while guaranteeing the communication quality-of-service (QoS) of legitimate transmissions, the requirement of radar detection performance, and the transmit power constraints of both radar and communication systems. When eavesdroppers' CSI is unavailable, we develop a joint artificial noise (AN)-aided transmit beamforming design scheme, which utilizes residual available power to generate AN for disrupting malicious receptions as well as satisfying the requirements of both legitimate transmissions and radar target detection. Extensive simulations verify the advantages of the proposed joint beamforming designs for ISAC systems on secure transmissions and the effectiveness of the developed algorithms.

Short Blocklength Wiretap Channel Codes via Deep Learning: Design and Performance Evaluation

We design short blocklength codes for the Gaussian wiretap channel under information-theoretic security guarantees. Our approach consists in decoupling the reliability and secrecy constraints in our code design. Specifically, we handle the reliability constraint via an autoencoder, and handle the secrecy constraint with hash functions. For blocklengths smaller than or equal to 128, we evaluate through simulations the probability of error at the legitimate receiver and the leakage at the eavesdropper for our code construction. This leakage is defined as the mutual information between the confidential message and the eavesdropper’s channel observations, and is empirically measured via a neural network-based mutual information estimator. Our simulation results provide examples of codes with positive secrecy rates that outperform the best known achievable secrecy rates obtained non-constructively for the Gaussian wiretap channel. Additionally, we show that our code design is suitable for the compound and arbitrarily varying Gaussian wiretap channels, for which the channel statistics are not perfectly known but only known to belong to a pre-specified uncertainty set. These models not only capture uncertainty related to channel statistics estimation, but also scenarios where the eavesdropper jams the legitimate transmission or influences its own channel statistics by changing its location.

Energy‐efficient covert communication with adaptive assist nodes group

AbstractIn this paper, a joint detection strategy of Willie based on two phases observation is proposed and an energy‐efficient covert communication scheme with an adaptive assist nodes group (AANG) based on uniform jamming power (UJP) strategy is proposed to against the joint‐phase detection of Willie, which achieves covert communication with lower energy cost and higher average covert rate (ACR). The probability of detection error (PDE) at Willie with joint‐phase detection and ACR are derived. Furthermore, the optimal power allocation of legitimate transmitters is resolved to maximize ACR. Numerical results demonstrate the benefit of the proposed scheme over the covert rate and consumed jamming power.