Passive Eavesdropper Research Articles

Intelligent-Reflecting-Surface-Assisted Single-Input Single-Output Secure Transmission: A Joint Multiplicative Perturbation and Constructive Reflection Perspective.

Due to the inherent broadcasting nature and openness of wireless transmission channels, wireless communication systems are vulnerable to the eavesdropping of malicious attackers and usually encounter undesirable situations of information leakage. The problem may be more serious when a passive eavesdropping device is directly connected to the transmitter of a single-input single-output (SISO) system. To deal with this urgent situation, a novel IRS-assisted physical-layer secure transmission scheme based on joint transmitter perturbation and IRS reflection (JPR) is proposed, such that the secrecy of wireless SISO systems can be comprehensively guaranteed regardless of whether the reflection-based jamming from the IRS to the eavesdropper is blocked or not. Moreover, to develop a trade-off between the achievable performance and implementation complexity, we propose both element-wise and group-wise reflected perturbation alignment (ERPA/GRPA)-based IRS reflection strategies, respectively. In order to evaluate the achievable performance, we analyze the ergodic secrecy rate (ESR) and secrecy outage probability (SOP) of the SISO secure systems with the ERPA/GRPA-based JPRs, respectively. Finally, by characterizing the simulated and numerical ESR and SOP performance results, our proposed scheme is compared with the benchmark scheme of random phase-based reflection, which strongly demonstrates the effectiveness of our proposed scheme.

Smart Collaborative Intrusion Detection System for Securing Vehicular Networks Using Ensemble Machine Learning Model

The advent of the Fourth Industrial Revolution has positioned the Internet of Things as a pivotal force in intelligent vehicles. With the source of vehicle-to-everything (V2X), Internet of Things (IoT) networks, and inter-vehicle communication, intelligent connected vehicles are at the forefront of this transformation, leading to complex vehicular networks that are crucial yet susceptible to cyber threats. The complexity and openness of these networks expose them to a plethora of cyber-attacks, from passive eavesdropping to active disruptions like Denial of Service and Sybil attacks. These not only compromise the safety and efficiency of vehicular networks but also pose a significant risk to the stability and resilience of the Internet of Vehicles. Addressing these vulnerabilities, this paper proposes a Dynamic Forest-Structured Ensemble Network (DFSENet) specifically tailored for the Internet of Vehicles (IoV). By leveraging data-balancing techniques and dimensionality reduction, the DFSENet model is designed to detect a wide range of cyber threats effectively. The proposed model demonstrates high efficacy, with an accuracy of 99.2% on the CICIDS dataset and 98% on the car-hacking dataset. The precision, recall, and f-measure metrics stand at 95.6%, 98.8%, and 96.9%, respectively, establishing the DFSENet model as a robust solution for securing the IoV against cyber-attacks.

Enhancing security offloading performance in NOMA heterogeneous MEC networks using access point selection and meta-heuristic algorithm

The research delves into the intricate domain of security offloading within the context of non-orthogonal multiple access (NOMA) heterogeneous mobile edge computing (het-MEC) networks operating over Rayleigh fading channels. The investigation centers on a system model comprising a single antenna-equipped edge user, denoted as U, which strategically offloads computational tasks to two distinct heterogeneous wireless access points (APs): the far AP (AP1) and the near one (AP2), employing NOMA techniques. Notably, the research accounts for a passive eavesdropper (E) intending to intercept the U−AP2 transmission. A four-phase protocol is proposed to ensure the security offloading process, namely SAPS, which leverages wireless access point selection (APS) and physical layer security (PLS) techniques. The focus extends to derive a closed-form expression for a novel critical system performance metric: the secrecy successful computation probability (SSCP). Furthermore, an algorithm based on Ant Colony Optimization (ACO) within the continuous domain is introduced, which aims to enhance the SSCP by intelligently determining system parameters. The impact of critical factors such as transmit power, power allocation coefficient, bandwidth, CPU frequency, and task division ratio under the SAPS scheme is explored and compared to the conventional approach using pure NOMA. Remarkably, the algorithm in the proposed scheme demonstrates up to a 3% performance improvement. The validity and accuracy of the study findings are verified through Monte-Carlo simulations. The work contributes significantly to advancing secure offloading strategies in NOMA-based MEC networks, offering valuable insights for practical deployment and optimization.

Physical layer security in SWIPT-based cooperative vehicular relaying networks

The future of autonomous transportation systems depends on energy sustainability and secure information exchange from low-power vehicular sensors, hence the increased interest in vehicular sensor charging using simultaneous wireless information and power transfer (SWIPT). This study investigates the physical layer security of a SWIPT-based radio frequency energy harvesting cooperative vehicular relaying network subjected to cascade Nakagami-m and double Nakagami-m (DN) fading channels. In the considered system model, a stationary source communicates with a mobile destination through a power-splitting-based decode-and-forward relay in the presence of a mobile passive eavesdropper. Based on the Gamma-distributed first term of the Laguerre series, new statistical probability density function (PDF) and cumulative distribution function (CDF) expressions for the DN are derived to accurately model the complex cascaded fading scenario. The secrecy performance metrics analyzed are the secrecy outage probability (SOP), the probability of non-zero secrecy capacity (PNZSC), and the intercept probability (IP). In addition, the asymptotic SOP (ASOP) is investigated in the high signal-to-noise ratio (SNR) to enhance the comprehension of the secrecy performance. Based on the derived ASOP, the secrecy diversity order (SDO) of the proposed system is determined and examined. Particularly, we present analytical closed-form expressions for the secrecy performance metrics and provide a detailed understanding of the impact of the system parameters under the cascade fading scenario. Then, a power splitting (PS) optimization problem is formulated to minimize the SOP. The results demonstrate a reduction in the SOP with the proposed PS scheme compared to the equal PS scheme. The obtained analytical findings are validated using Monte Carlo simulations.

On secrecy performance of RIS-assisted CRNs leveraging discrete phase control

In this paper, we investigate the physical layer security (PLS) of a cognitive radio network (CRN) assisted by a reconfigurable intelligent surface (RIS) based on discrete phase control. Specifically, the phase shifts of the RIS are designed to maximize the received signal-to-noise ratio (SNR) at the secondary receiver. In the presence of passive eavesdropping, we address the secrecy outage performances for the considered system under two different scenarios whether the direct link exists or not. To characterize the performance, novel exact expressions of secrecy outage probability (SOP) are derived leveraging the Gaussian–Chebyshev quadrature. We also conduct the asymptotic analysis to study the influence of the main parameters such as the number of reflect elements of RIS and the number of quantization bits on the secrecy performance of our proposed system. Finally, our analytical results are verified through performing Monte Carlo simulations. Simulation results show that significant security enhancement can be achieved in CRN by employing the RIS.

Secure Power Control for Downlink Cell-Free Massive MIMO With Passive Eavesdroppers

Secure Power Control for Downlink Cell-Free Massive MIMO With Passive Eavesdroppers

Trajectory Optimization and Power Allocation Scheme for a UAV Relay-aided Network in the Presence of an Eavesdropper

The information theoretical security for a cellular network in the presence of an eavesdropper is investigated in this research. The network is single-input-single-output (SISO) in nature. A small unmanned aerial vehicle (UAV) is aiding the network as a relay that follows the decode-and-forward (DF) protocol. The relay decodes the transmitted signal and retransmits it to the destination while repositioning itself if required. The allotted power of the UAV may not be enough for long-distance and long-duration travel. This article deals with the power needed for the data transmission so that the UAV can operate as a relay with less transmit power. However, the confidential data transmission between a base station and a mobile device is being intercepted by a passive eavesdropper. The security issue affects the transmit power and the outage situation. The theory of physical layer security is employed to ensure a secure wireless transmission. The secrecy parameters, namely, the secrecy capacity and the secrecy outage probability are investigated via mathematical derivations and computer programming. Additionally, optimizing the trajectory and allocation of the transmit power budget of the UAV will increase the network’s reliability. Our results show that the UAV relay can handle a secure transmission with its limited resources if a budget power allocation can be achieved along with an optimized trajectory.

Intelligent Reflecting Surface Assisted Secure Computation of Wireless Powered MEC System

The integration of mobile edge computing (MEC) and wireless power transfer (WPT) can effectively improve the computing ability and energy sustainability of energy-constrained wireless devices in the Internet of Things (IoT) networks. Intelligent reflecting surface (IRS) has recently emerged as an effective technique to improve the performance of wireless systems by intelligently reconfiguring wireless environments. This paper studies the exploitation of IRS to improve the secure computation performance of WPT-MEC systems with a passive eavesdropper. A wireless access point (AP) first charge multiple users with the emitted energy signals, and then the users perform local computing and partial offloading to complete their computation tasks with the harvested energy in the presence of an eavesdropper, where the local computing can be executed during the whole process of WPT and offloading. Meanwhile, deploying IRS can improve the energy capture and secure offloading performance of the users. We maximize the secure computation task bits of users by jointly optimizing the AP energy transmit beamforming, the IRS phase shifts, the transmit power, users' offloading time, and the local computation frequency of users, which are tangled with each other. An iterative optimal algorithm is developed to solve this non-convex problem by combining Taylor expansion method, semidefinite relaxation (SDR) algorithm, the Lagrange duality theory and Karush-Kuhn-Tucker (KKT) conditions. The numerical results show that the proposed scheme can effectively increase the secure computation task bits compared with other benchmark schemes, especially for the maximum transmit power of AP, the improvement is above 45 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

Secrecy Analysis of ABCom-Based Intelligent Transportation Systems With Jamming

Employing ambient backscatter communication (AmBC) technology in Intelligent Transportation Systems (ITS) has emerged as an appealing solution to boost the awareness of crosswalks. However, the AmBC-based ITS is expected to face serious security threats due to the presence of malicious eavesdroppers. In this paper, we investigate the secure multi-antenna transmission in an AmBC-based ITS coexisting with a passive eavesdropper with jamming. Specifically, a cooperative jammer is placed in the system to deliberately disrupt the eavesdropper without affecting the legitimate receiver. In order to characterize the performance of the proposed scheme, new approximate closed-form expressions of secrecy outage probability (SOP) are derived by adopting the Gauss-Chebyshev quadrature. Additionally, the asymptotic behavior of SOP at the high signal-to-noise ratio (SNR) regime is also studied to provide more insights into the system design. We also derive the asymptotic SOP, when the number of transmit antennas tends to infinity. Monte Carlo simulations are provided to demonstrate the validity of our analytical results and to show that 1) the secrecy performance can be significantly improved by allocating part of the transmit power to perform cooperative jamming and 2) the optimal power allocation factor is related to the total transmit power.

Modeling and Analysis of Physical Layer Security of OTFS Systems Under Transmit Antenna Selection and Passive Eavesdropping

Modeling and Analysis of Physical Layer Security of OTFS Systems Under Transmit Antenna Selection and Passive Eavesdropping

Securing cooperative vehicular networks amid obstructing vehicles and mixed fading channels

Smart cities (SCs) were founded on the basis of the Internet of Vehicles paradigm, aiming to enhance the quality of life. Despite not having a unique composition, the intelligent transportation services (ITS) is a key component in most of the SCs. The ITS integrates the new communication systems along with the traditional transportation systems, forming a universal network of static and vehicular entities communicating over wireless broadcast channels. In addition to its vulnerability to co-channel interference (CCI), eavesdropping, and fading, the vehicle-to-vehicle communication channels could be subjected to shadowed fading. That is due to the probabilistic obstruction by big vehicles. Hence, degrading the signal-to-noise ratio at the receiving vehicle severely. This work evaluates the secrecy performance of a practical cooperative vehicular relaying network in terms of its secrecy outage probability (SOP). Due to the probabilistic existence of a vehicular obstacle, three different communication scenarios are considered and a novel closed-form analytical expression for the SOP is obtained over mixed Nakagami-m fading and Nakagami-N-Gamma shadowed fading channels. The system comprises legitimate source and destination operating in full-duplex mode, thus imposing CCI on both the relay and the passive eavesdropper. The result demonstrate the impacts of the secrecy data rate threshold, the strength of shadowing, the density of the obstructing vehicles, and several parameters on the SOP. High levels of shadowing strength and density of obstructing vehicles significantly degrades the secrecy performance by increasing the SOP. Accordingly, adopting the mixed fading channel model is of great importance for practical network modeling.

Eavesdropping with intelligent reflective surfaces: Near-optimal configuration cycling

Intelligent reflecting surfaces (IRSs) have several prominent advantages, including improving the level of wireless communication security and privacy. In this work, we focus on the latter aspect and introduce a strategy to counteract the presence of passive eavesdroppers overhearing transmissions from a base station towards legitimate users that are facilitated by the presence of IRSs. Specifically, we envision a transmission scheme that cycles across a number of IRS-to-user assignments, and we select them in a near-optimal fashion, thus guaranteeing both a high data rate and a good secrecy rate. Unlike most of the existing works addressing passive eavesdropping, the strategy we envision has low complexity and is suitable for scenarios where nodes are equipped with a limited number of antennas. Through our performance evaluation, we highlight the trade-off between the legitimate users’ data rate and secrecy rate, and how the system parameters affect such a trade-off.

Full‐duplex jamming for physical layer security improvement in NOMA‐enabled overlay cognitive radio networks

AbstractIn this paper, we analyze the physical layer security (PLS) performance of nonorthogonal multiple access (NOMA)‐enabled overlay cognitive radio networks (NOMA‐OCRNs) in the presence of an external passive eavesdropper. Here PLS is expressed in terms of the secrecy outage probabilities (SOPs) experienced by the primary user (PU) and secondary user (SU). We obtain approximate expressions for the SOPs of both PU as well as SU assuming a jamming‐free environment, where both primary and secondary destination nodes are half‐duplex devices. To improve the SOP performance, we propose a jamming‐assisted framework, where full‐duplex destination nodes are employed, which are capable of transmitting jamming signals to confound the eavesdropper. Approximate expressions for the SOPs of PU and SU are derived for the jamming‐assisted framework as well. It is demonstrated that the proposed jamming‐assisted framework significantly reduces the SOPs compared to the jamming‐free scenario. We also determine optimal power allocation coefficients (OPACs) for PU and SU at the secondary transmitter that maximizes the total secrecy throughput of the jamming‐assisted NOMA‐OCRN with FD destinations. It is shown that the suggested OPAC significantly enhances the total secrecy throughput, compared to the default selection of the PAC.

Energy-Efficient Coordinated Beamforming in Multi-Pair MISO Networks With CDI and Eavesdroppers

This paper investigates the energy-efficient coordinated beamforming design for multi-pair multiple-input single-output (MISO) networks with passive eavesdroppers. To be practical, it is assumed that only channel distribution information (CDI) of the network is known by the transmitters/sources, and the dynamic energy consumption model (DECM) is employed. In order to achieve a green network design, an energy efficiency (EE) maximization problem is formulated subjecting to the individual available power constraints, the rate outage probability constraints, and the information leakage probability constraints. To solve the formulated non-convex problem, semidefinite relaxation (SDR) and first-order lower bound are applied to transform the problem, and then an efficient algorithm is proposed based on successive convex approximation (SCA) and Dinkelbach's approaches. The proposed algorithm is theoretically proved to converge to a stationary point of the considered problem. Further, a distributed version of the proposed algorithm is designed, with which each transmitter is able to optimize its own beamforming vector with local CDI. Moreover, the computational complexities and the signaling overheads of the two developed algorithms are analyzed and compared. Simulation results show that both algorithms achieve good EE performance, and the EE performance achieved by the distributed algorithm is very similar to that achieved by the centralized one. Additionally, it is shown that similar to the conventional scenarios without eavesdroppers, the achieved system EE also has a saturation point w.r.t. the available power of the transmitters, and by employing our proposed algorithms, the network security is significantly enhanced.

RIS-Assisted Secure UAV Communication Scheme Against Active Jamming and Passive Eavesdropping

RIS-Assisted Secure UAV Communication Scheme Against Active Jamming and Passive Eavesdropping

Physical Layer Security in IRS-Assisted Cache-Enabled Satellite Communication Networks

This paper presents a comprehensive analysis of the physical layer security performance of a cache-enabled satellite communication network that incorporates intelligent reflecting surfaces (IRS) in the presence of a passive eavesdropper. In the proposed system, content caches are deployed at both the ground station and the satellite, which can improve system performance by reducing latency and transmission overhead. Moreover, the use of IRS provides an additional layer of security by enabling the manipulation of the reflected signals to impede eavesdropping. Practical channel models are used to derive connection probability and secrecy probability for both the ground station-IRS-user and the satellite-IRS-user links. The obtained results are then used to evaluate the system’s secure transmission probability, which is maximized subject to the caching probabilities and transmission rate constraints. The paper presents numerical results to demonstrate the accuracy of the analysis and the effectiveness of deploying IRS and caching to support secure content delivery. The findings provide valuable insights into the potential benefits of utilizing IRS and caching technologies in satellite communication networks for improved physical layer security.

Estimating Traffic Rates in CSMA/CA Networks: A Feasibility Analysis for a Class of Eavesdroppers

Estimation of transmission rates by a malicious user can serve as a stepping stone to further attacks on the network. In this paper, we aim to investigate the general problem of estimating traffic transmission rates in a CSMA/CA network using a class of passive eavesdropping methods. We consider the case where a single eavesdropper passively monitors all active network nodes but cannot observe all packet transmissions due to spatial-reuse collisions. To enable tractable analysis, we first propose an approximate statistical model that can help the eavesdropper estimate transmission rates with partial measurements under spatial reuse. We next consider a class of eavesdroppers that become increasingly more capable, and develop a framework to demonstrate that two classes of eavesdropper capabilities are sufficient to achieve a consistent transmission rate estimator. We provide numerical tests of our proposed estimators under practical network cases using the NS-3 simulator that validate the theoretical results.

Secrecy Energy Efficiency Maximization for Secure Unmanned-Aerial-Vehicle-Assisted Simultaneous Wireless Information and Power Transfer Systems

Unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) systems have recently gained significant attraction in internet-of-things (IoT) applications that have limited or no infrastructure. Specifically, the free mobility of UAVs in three-dimensional (3D) space allows us good-quality channel links, thereby enhancing the communication environment and improving performance in terms of achievable rates, latency, and energy efficiency. Meanwhile, IoT devices can extend their battery life by harvesting the energy following the SWIPT protocol, which leads to an increase in the overall system lifespan. In this paper, we propose a secure UAV-assisted SWIPT system designed to optimize the secrecy energy efficiency (SEE) of a ground network, wherein a base station (BS) transmits confidential messages to an energy-constrained device in the presence of a passive eavesdropper. Here, we employ a UAV acting as a helper node to improve the SEE of the system and to aid in the energy harvesting (EH) of the battery-limited ground device following the SWIPT protocol. To this end, we formulate the SEE maximization problem by jointly optimizing the transmit powers of the BS and UAV, the power-splitting ratio for EH operations, and the UAV’s flight path. The solution is obtained via a proposed algorithm that leverages successive convex approximation (SCA) and Dinkelbach’s method. Through simulations, we corroborate the feasibility and effectiveness of the proposed algorithm compared to conventional partial optimization approaches.

Physical Layer Security for Frequency Diverse Array-Based Dual-Hop Spatial Modulation

In this paper, we design the physical layer security of a dual-hop spatial modulation system provided the relay node transmits its own private information. Meanwhile, the quadrature virtual channel spatial modulation (QVCSM) is proposed to enhance the physical layer security in the second hop. To achieve system security in both angle and range dimensions, the frequency diverse array (FDA) is used in the relay node with a decode-and-forward (DF) protocol. Moreover, the baseband directional modulation (DM) and artificial noise (AN) are jointly utilized to suppress the received signal at the passive eavesdropper. Additionally, the Ergodic secrecy rate of the proposed system is analyzed, whereas the closed-form expressions for tight upper bounds on the bit error rates (BERs) of the source and relay are derived for both the destination and eavesdropper. The simulation results show that the proposed FDA relay design outperforms the traditional phase array (PA) relay system in terms of the system secrecy rate. In contrast to the quadrature spatial modulation (QSM) method, the proposed designs achieve an improved suppression performance of the eavesdropper.

UAV Trajectory and Multi-User Beamforming Optimization for Clustered Users Against Passive Eavesdropping Attacks With Unknown CSI

This paper tackles the fundamental passive eavesdropping problem in modern wireless communications in which the location and the channel state information (CSI) of the attackers are unknown. In this regard, we propose deploying an unmanned aerial vehicle (UAV) that serves as a mobile aerial relay (AR) to help ground base station (GBS) support a subset of vulnerable users. More precisely, our solution (1) clusters the single-antenna users in two groups to be either served by the GBS directly or via the AR, (2) employs optimal multi-user beamforming to the directly served users, and (3) optimizes the AR's 3D position, its multi-user beamforming matrix and transmit powers by combining closed-form solutions with machine learning techniques. Specifically, we design a plain beamforming and power optimization combined with a deep reinforcement learning (DRL) algorithm for an AR to optimize its trajectory for the security maximization of the served users. Numerical results show that the multi-user multiple input, single output (MU-MISO) system split between a GBS and an AR with optimized transmission parameters without knowledge of the eavesdropping channels achieves high secrecy capacities that scale well with increasing the number of users.