Active Eavesdropper Research Articles

Safeguarding UAV Networks against Active Eavesdropping: An Elevation Angle-Distance Trade-Off for Secrecy Enhancement

Because of their low expense and ease of rapid deployment, unmanned aerial vehicles (UAVs) are frequently applied in wireless networks. Although the wireless channel is able to broadcast, legitimate communications between UAVs and ground nodes are incredibly susceptible to severe security threats, such as malicious jamming and eavesdropping. Compared with the traditional line-of-sight channel (LC) model, the probabilistic LC (PrLC) model can better describe the practical channel conditions of UAV-to-ground transmission in city areas. Therefore, this paper considers the UAV-enabled networks under the PrLC model in complex city environments. Specifically, when the UAV transmits classified messages to legitimate ground nodes, multiple active eavesdroppers simultaneously eavesdrop on the transmitted confidential information to interfere with the signal and limit the legal transmission. We jointly optimize the communication connection, the three-dimensional (3D) UAV trajectory, and the transmit power of the UAV to increase the average secrecy rate for the worst condition. Because the problem is non-convex, the best solution is formidable to get, this paper designs an iterative algorithm and use the successive convex approximation (SCA) technique to solve it. Compared to other benchmarks, our proposed algorithm, as demonstrated by numerical results, can effectively balance the elevation angle-distance trade-off to improve secrecy rate performance.

Robust Multi-Beam Secure mmWave Wireless Communication for Hybrid Wiretapping Systems

In this paper, we consider the physical layer (PHY) security problem for hybrid wiretapping wireless systems in millimeter wave transmission, where active eavesdroppers (AEs) and passive eavesdroppers (PEs) coexist to intercept the confidential messages and emit jamming signals. To achieve secure and reliable transmission, we propose an artificial noise (AN)-aided robust multi-beam array transceiver scheme. Leveraging beamforming, we aim to minimize transmit power by jointly designing the information and AN beamforming, while satisfying valid reception for legitimate users (LUs), per-antenna power constraints for transmitter, as well as all interception power constraints for eavesdroppers (Eves). In particular, the interception power formulation is taken into account for protecting the information against hybrid Eves with imperfect AE channel state information (CSI) and no PE CSI. In light of the intractability of the problem, we reformulate the considered problem by replacing non-convex constraints with tractable forms. Afterwards, a two-stage algorithm is developed to obtain the optimal solution. Additionally, we design the received beamforming weights by means of minimum variance distortionless response, such that the jamming caused by AEs can be effectively suppressed. Simulation results demonstrate the superiority of our proposed scheme in terms of energy efficiency and security.

New LLRT-Based Methods for Active Eavesdropper Detection in Cell-Free Massive MIMO

In this paper, the problem of active eavesdropper detection is considered for a cell-free massive multiple-input multiple-output (m-MIMO) system which is attacked by an active eavesdropper within the uplink training phase, also called pilot spoofing attack. Two methods based on log-likelihoodratio tests (LLRT), one in a centralized and the other in a decentralized fashion, are proposed to detect the signal abnormality. The methods take advantage of a special protocol in which the legitimate users switch to an off-mode irregularly, without significantly affecting the spectral efficiency of the data transmission. The protocol is directly applicable to environments with low to moderate mobility, and can be extended to high mobility through a simple rearrangement of available pilot sequences among users if needed. More importantly, the proposed methods impose low fronthaul overhead which is imperative for a cellfree m-MIMO system with a large number of access points (APs). A closed-form expression for the joint probability density function (PDF) of the processed received signals conditioned on the alternative hypothesis, which is essential for the implementation of LLRT-based detection methods, is also derived. Through an asymptotic analysis, it is shown for the proposed methods that the detection and false-alarm probabilities approach to one and zero, respectively as the number of APs goes to infinity. Numerical results reveal that both methods significantly outperform a recent approach in terms of false-alarm rate with negligible degradation in the per user uplink spectral efficiency.

Secure Downlink Transmission Strategies against Active Eavesdropping in燦OMA Systems: A Zero-Sum Game Approach

Non-orthogonal multiple access technology (NOMA), as a potentially promising technology in the 5G/B5G era, suffers from ubiquitous security threats due to the broadcast nature of the wireless medium. In this paper, we focus on artificial-signal-assisted and relay-assisted secure downlink transmission schemes against external eavesdropping in the context of physical layer security, respectively. To characterize the non-cooperative confrontation around the secrecy rate between the legitimate communication party and the eavesdropper, their interactions are modeled as a two-person zero-sum game. The existence of the Nash equilibrium of the proposed game models is proved, and the pure strategy Nash equilibrium and mixed-strategy Nash equilibrium profiles in the two schemes are solved and analyzed, respectively. The numerical simulations are conducted to validate the analytical results, and show that the two schemes improve the secrecy rate and further enhance the physical layer security performance of NOMA systems.

Enhancing Physical-Layer Security for IoT With Nonorthogonal Multiple Access Assisted Semi-Grant-Free Transmission

Nonorthogonal multiple access (NOMA) assisted semi-grant-free transmission admits grant-free users to access the channels otherwise solely occupied by grant-based users, and has been recently attracting considerable attention in terms of accommodating massive connectivity and reducing access delay in Internet of Things (IoT). In this work, we investigate the security of semi-grant-free NOMA transmission in the presence of passive and active eavesdropping attacks. In particular, for the scenario-I with strong grant-based user and weak grant-free users, the scenario-I-based maximal user scheduling (IbMUS) and scenario-I-based optimal user scheduling (IbOUS) schemes are proposed to combat the passive and active eavesdropping, respectively. For the scenario-II with weak grant-based user and strong grant-free users, two parallel schemes, namely, the scenario-II-based maximal user scheduling (IIbMUS) and scenario-II-based optimal user scheduling (IIbOUS) schemes, are proposed to combat the passive and active eavesdropping, respectively. These proposed schemes enhance the security by scheduling a grant-free user with maximal main channel capacity/maximal secrecy capacity to access the NOMA channel on the premise of ensuring the grant-based user’s Quality of Service. Based on these proposed schemes, the exact secrecy outage probability (SOP) are analyzed to evaluate the system performance. The simulation results validates the theoretic analysis and the superiority of the proposed schemes. The IbOUS and IIbOUS schemes can achieve better performance than the IbMUS and IIbMUS schemes owing to the use of active eavesdropper’s channel state information (CSI). The SOP achieved by the proposed schemes can be further improved with the increasing number of grant-free users and decreasing target rate (or target secrecy rate).

Secure MIMO systems with nonlinear energy harvesting using optimal transmit antenna selection over [formula omitted] fading channels

This paper investigates the secrecy performance of multiple-input multiple-output systems with a nonlinear energy harvesting (EH) scheme used at the transmitter to improve energy efficiency and extend the lifetime of energy-constrained systems. Most of the current literature investigates cognitive radio networks with linear EH model. However, in order to realize more realistic scenarios due to hardware constraints, such as the saturation and sensitivity characteristics of the EH components, a nonlinear EH model is examined here and compared with a simpler linear EH scheme. In particular, a practical nonlinear energy harvester model with a source, a destination, an active eavesdropper, and a power beacon is considered under generalized α−μ fading conditions. Here, the eavesdropper can overhear the data transmission messages when the source communicates with the destination using wiretap channels. Furthermore, the source employs all its antennas to combine the radio frequency signals emitted by the power beacon via the maximal ratio combining (MRC) scheme. Moreover, the MRC scheme is used at the destination and eavesdropper to improve the signal’s quality (i.e., at the receiver side). Closed-form expressions for the lower bound and asymptotic security performance are investigated. Next, optimal antenna selection (OAS) scheme and traditional space–time transmission (STT) scheme are compared based on whether the channel state information (CSI) of the wiretap link is available. In addition to deriving the secrecy diversity order and secrecy array gain, asymptotic closed-form analytical expressions for security performance and closed-form analytical expressions for the probability of strictly positive secrecy capacity are also derived for various selection schemes. Finally, numerical results indicate that, compared to the linear EH scheme with just minimal trade-offs, the nonlinear EH scheme represents more realistic and dependable outcomes.

PERFORMANCE OF SECURE COMMUNICATION OVER LAMBDA-FISHER-SNEDECOR FADING CHANNELS

In this paper, we investigate the physical layer security (PLS) of the traditional Wyner’s wiretap channel model. Secrecy performance analysis is performed assuming a presence of an active eavesdropper trying to overhear the confidential data transmission from the source node to the predefined destination. In what follows, we derive the lower bound of the secrecy outage probability, the strictly positive secrecy capacity as well as the average secrecy capacity, over the composite a-Fisher-Snedecor (a-F) fading environment. According to the analytical results, numerical results are also shown. The impact of the path loss component, the average signal-to-noise ratios over the main/wiretap channel as well as the impact of the fading, the non-linearity of the propagation medium and the shadowing shaping parameter on the PLS metrics is examined. The overall analysis and the obtained results have a high level of generality and also a high level of applicability since the a-F distribution was recently proposed, as the best fit distribution for the channel characterization of the device-to-device wireless communication in the future Beyond 5G networks.

Deep Learning-Based Authentication Framework for Secure Terrestrial Communications in Next Generation Heterogeneous Networks

Smart Grid (SG) network is growing rapidly to improve the efficiency and reliability of the power supply. It will connect billions of devices to the internet in the near future. This increase in the number of internet-connected devices has led to an exponential increase in the market size of smart meters. These smart meters and devices will generate lakhs of gigabytes of data in upcoming years. To handle this massive amount of data flow, the Information and Communication Technology (ICT) of SG will experience huge advancements in terms of 5G and 6G wireless networks. These networks will provide higher data rates by utilizing the huge bandwidth spectrum of heterogeneous networks (HetNet). As the massive amount of data will be transmitted to various components of the smart grid using the internet, an open channel. Therefore, in addition to the need for high bandwidth and low latency, HetNet security has also become a prime concern. This paper presents an efficient approach to authenticate the smart devices in SG environment by using the channel state information (CSI) of the wireless links. Firstly, Low-Density Parity-Check (LDPC) codes are used to maintain the confidentiality and reliability of data transmission in the Advanced Metering Infrastructure (AMI) of SG. Then, a Convolution Neural Network (CNN)-based authentication framework is proposed to enhance the physical layer security (PLS) of terrestrial communications in next generation SG Hetnets. Further, the proposed framework is evaluated using received Channel State Information (CSI) values from smart meters placed at different locations, while also taking the scenario of active eavesdroppers into account. Experimental analysis reveals that the proposed CNN based authentication achieves 30.76 percent better authentication rate than existing DNN based authentication scheme. Further, the LDPC coded data transmission scheme reduces the bit error rate (BER) by 20 percent as compared to uncoded data transmission.

Performance enhancement in the cell-free massive MIMO SWIPT system with active eavesdropping

This paper investigates the secure transmission for simultaneous wireless information and power transfer (SWIPT) in the cell-free massive multiple-input multiple-output (MIMO) system. To develop green communication, legitimate users harvest energy by the hybrid time switching (TS) and power splitting (PS) strategy in the downlink phase, and the harvested energy can provide power to send uplink pilot sequences for the next time slot. By in-built batteries, the active eavesdropper can send the same pilots with the wiretapped user, which results in undesirable correlations between the channel estimates. Under these scenarios, we derive the closed-form expressions of average harvested energy and achievable rates, and propose an iterative power control (PC) scheme based on max–min fairness algorithm with energy and secrecy constraints (MMF-ESC). This scheme can ensure the uniform good services for all users preserving the distributed architecture advantage of cell-free networks, while meeting the requirements of energy harvested by legitimate users and network security against active eavesdroppers. Besides, continuous approximation, bisection and path tracking are jointly applied to cope with the high-complexity and non-convex optimization. Numerical results demonstrate that MMF-ESC PC scheme can effectively increase the achievable rate and the average harvested energy of each user, and decrease the eavesdropping rate below the threshold. Moreover, the results also reveal that PS strategy is superior in harvesting energy in terms of more stringent network requirements for average achievable rates or security.

Reconfigurable Intelligent Surface-Aided Cell-Free Massive MIMO with Low-Resolution ADCs: Secrecy Performance Analysis and Optimization

The secure communication in reconfigurable intelligent surface-aided cell-free massive MIMO system is investigated with low-resolution ADCs and with the existence of an active eavesdropper. Specifically, an aggregated channel estimation approach is applied to decrease the overhead required to estimate the channels. Using the available imperfect channel state information (CSI), the conjugate beamforming and random beamforming are applied at the APs and the RIS for downlink data transmission, respectively. The closed-form expression of the achievable secrecy rate is acquired to appraise the achievable secrecy performance using only the channel statistics. With the achievable analytical results, the impacts of the quantization bit of ADCs, channel estimation error, the number of RIS elements, and the number of the APs can be unveiled. Aiming to maximize the minimum achievable rate of all legitimate users subject to security constraints, the power control optimization scheme is first formulated. To tackle this nonconvex property of the proposed optimization problem, a path-following algorithm is then utilized to solve the initial problem with continuous approximations and iterative optimization. Numerical results are presented to verify the achieved results along with availability of the presented power allocation approach.

Caching and UAV Friendly Jamming for Secure Communications With Active Eavesdropping Attacks

In this paper, we discuss the security and reliability performance of a communication system, where the base station (BS) transmits signals to multiple users and an unmanned aerial vehicle (UAV) jammer sends friendly jamming signals to protect against a full-duplex active eavesdropper with the aid of caching. We derive the closed-form expressions of outage probability (OP) and intercept probability (IP) for the legitimate users and active eavesdropper, respectively. Aimed at minimizing the sum of the IP and the maximum OP among all users, we jointly optimize the BS transmit power, UAV jammer location and jamming power. An efficient algorithm based on alternating optimization (AO) and successive convex approximation (SCA) methods is designed to solve the optimization problem. Numerical results show that compared to other benchmark strategies, the proposed solution improves the reliability and security performance with the aid of caching and UAV friendly jamming.

Proactive eavesdropping rate maximization with UAV spoofing relay

Spoofing relay is an effective way for legitimate agencies to monitor suspicious communication links and prevent malicious behaviors. The unmanned aerial vehicles(UAVs)-assisted wireless information surveillance system can virtually improve proactive eavesdropping efficiency thanks to the high maneuverability of UAVs. This paper aims to maximize the eavesdropping rate of the surveillance system where the UAV is exploited to actively eavesdrop by spoofing relay technology. We formulate the problem to jointly optimize the amplification coefficient, splitting ratio, and UAV’s trajectory while considering successful monitoring. To make the nonconvex problem tractable, we decompose the problem into three sub-problems and propose a successive convex approximation based alternate iterative algorithm to quickly obtain the near-optimal solution. The final simulation results show that the UAV as an active eavesdropper can effectively increase the information eavesdropping rate than a passive eavesdropper.

Reinforcement Learning Based Network Coding for Drone-Aided Secure Wireless Communications

Active eavesdropper sends jamming signals to raise the transmit power of base stations and steal more information from cellular systems. Network coding resists the active eavesdroppers that cannot obtain all the data flows, but highly relies on the wiretap channel states that are rarely known in wireless networks. In this paper, we present a reinforcement learning (RL) based random linear network coding scheme for drone-aided cellular systems to address eavesdropping. In this scheme, the network coding policy, including the encoded packet number, the packet and power allocation, is chosen based on the measured jamming power, previous transmission performance and BS channel states. A virtual model generates simulated experiences to update Q-values besides real experiences for faster policy optimization. We also propose a deep RL version and design a hierarchical architecture to further accelerate the policy exploration and improve the anti-eavesdropping performance, in terms of the intercept probability, the latency, the outage probability and the energy consumption. We analyze the computational complexity, drone deployment, secure coverage area and the performance bound of the proposed schemes, which are verified via simulation results.

Security performance analysis for cell-free massive multiple-input multiple-output system with multi-antenna access points deployment in presence of active eavesdropping

This article investigates the influence of multiple-antenna deployment at access points on physical layer security under cell-free massive multiple-input multiple-output systems. To embody the concept of network multiple-input multiple-output, cell-free massive multiple-input multiple-output employs a great deal of geographically distributed access points, which jointly serve multiple users in the same frequency-time resource. Assuming a malicious active eavesdropper having knowledge of instantaneous channel state information, we derive the asymptotic closed-form expression of the achievable secrecy rate, which is used to evaluate network security performance. A distributed power allocation scheme is developed based on channel fading degrees of different users. All of access points distribute a larger proportion of local transmission power to the users with better channel conditions. We verified that the security performance of the multi-antenna access points outperforms that of the single one. Compared to equal power allocation, the proposed power control algorithm can further boost the network security performance.

An RFID Zero-Knowledge Authentication Protocol Based on Quadratic Residues

An RFID system is a contactless automatic identification technology and a solution to many business and personal applications. However, the privacy threats to RFID systems cause significant concerns in real RFID applications. Among the privacy issues in RFID systems, we are particularly interested in designing an RFID authentication protocol that achieves strong indistinguishability-based privacy (ind-privacy) and possesses the zero-knowledge property for active tags. In this article, a zero-knowledge authentication protocol (ZKAP) using quadratic residues is proposed. Then, an indistinguishability-based experiment using random oracles is modeled to prove that the proposed scheme achieves strong ind-privacy against active eavesdroppers. The zero-knowledge property is defined with respect to the tags’ private information against dishonest readers, and that property of our ZKAP is proven by constructing a polynomial time simulator that generates a transcript with the same distribution as that of ZKAP. Finally, the proposed protocol is implemented in a Raspberry Pi and a PC, and the performance is evaluated in terms of authentication time. The experimental results demonstrate that our ZKAP achieves its design goals.

Secrecy Coding Analysis of Short-Packet Full-Duplex Transmissions with Joint Iterative Channel Estimation and Decoding Processes.

This paper studies the secrecy coding analysis achieved by the self-jamming technique in the presence of an eavesdropper by considering a short-packet Full-Duplex (FD) transmission developed based on iterative blind or semi-blind channel estimation and advanced decoding algorithms. Indeed, the legitimate receiver and eavesdropper can simultaneously receive the intended signal from the transmitter and broadcast a self-jamming or jamming signal to the others. Unlike other conventional techniques without feedback, the blind or semi-blind algorithm applied at the legitimate receiver can simultaneously estimate, firstly, the Self-Interference (SI) channel to cancel the SI component and, secondly, estimate the propagation channel, then decode the intended messages by using 5G Quasi-Cyclic Low-Density Parity Check (QC-LDPC) codes. Taking into account the passive eavesdropper case, the blind channel estimation with a feedback scheme is applied, where the temporary estimation of the intended channel and the decoded message are fed back to improve both the channel estimation and the decoding processes. Only the blind algorithm needs to be implemented in the case of a passive eavesdropper because it achieves sufficient performances and does not require adding pilot symbols as the semi-blind algorithm. In the case of an active eavesdropper, based on its robustness in the low region of the Signal-to-Noise Ratio (SNR), the semi-blind algorithm is considered by trading four pilot symbols and only requiring the feedback for channel estimation processes in order to overcome the increase in noise in the legitimate receiver. The results show that the blind or semi-blind algorithms outperform the conventional algorithm in terms of Mean Square Error (MSE), Bit Error Rate (BER) and security gap (). In addition, it has been shown that the blind or semi-blind algorithms are less sensitive to high SI and self-jamming interference power levels imposed by secured FD transmission than the conventional algorithms without feedback.

Secrecy Performance of Underlay Cognitive Radio Networks With Primary Interference

This work explores the physical layer security of an underlay cognitive radio network (CRN) in the presence of a powerful interferer called a primary transmitter (PT) under peak interference power constraint. Under this scenario, the secondary transmitter (Alice) transmits secret information on a single antenna with the highest signal-to-interference plus noise ratio (SINR) to a legitimate receiver (Bob), and an eavesdropper (Eve) attempts to intercept that information. Depending upon the availability of channel state information (CSI) of the eavesdropper channel, we investigate the secrecy performance of the proposed network in the Rayleigh fading environment for both passive and active eavesdropping scenarios. We obtain analytical expressions for the secrecy outage probability, intercept probability, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -outage secrecy capacity in a passive eavesdropping scenario. A complete investigation of the average secrecy capacity (ASC) has been made, and novel expressions for the exact and asymptotic ASC have been obtained for active eavesdropping. Bolstering these results, we also define a high SINR power offset, which quantifies the significance of main system parameters on the ASC explicitly. Further, the effect of outdated CSI of Alice to primary receiver link on the various performance metrics with the concept of interference-outage is also studied.

Effect of best relay selection scheme on secrecy outage of underlay cognitive radio networks with energy harvesting: Design and simulation

In this paper, the secrecy outage performance is studied for optimal relay selection (ORS) schemes with energy harvesting system deployed at the secondary transmitter to improve both energy efficiency and spectral efficiency. This investigation is based on the use of a cooperative underlay cognitive radio network (CRN) consists of one primary transmitter, one primary receiver, one secondary source, N secondary relays, one secondary destination, and one active eavesdropper. Further, multiple antenna techniques are utilized at both the destination and the eavesdropper, where maximal ratio combining (MRC) diversity scheme is adopted to enhance the quality of the signal. Next, the security performance with ORS and energy harvesting (EH) schemes is derived over mixed Rayleigh and Nakagami-m fading channels. Here, the channel state information (CSI) is assumed available to both the secondary source and the relay, while the eavesdropper will try to overhear the transmitted information between the selected relay and the destination through a wiretap channel. Depending on these assumptions, a closed-form expression for the secrecy outage probability is derived with ORS scheme. The mathematical results indicate that the secrecy outage performance of the proposed system model improves when the number of antennas at the destination increases or by decreasing the number of antennas at the eavesdropper. Moreover, increasing the number of decode-and-forward (DF) relays improves the secrecy outage performance as well. Finally, the least value of secrecy outage probability can be achieved by increasing the average channel power gain between the source and relay (i.e., the key factor in cooperative communication). The accuracy of all derivations are validated through the Monte-Carlo simulations.

IRS-Aided Energy-Efficient Secure WBAN Transmission Based on Deep Reinforcement Learning

Wireless body area networks (WBANs) are vulnerable to active eavesdropping that simultaneously perform sniffing and jamming to raise the sensor transmit power, and thus steal more healthcare data. In this paper, we propose an intelligent reflecting surface (IRS)-aided reinforcement learning (RL) based secure WBAN transmission scheme that enables the coordinator to jointly optimize the sensor encryption key and transmit power, as well as the IRS phase shifts against active eavesdropping. A Dyna architecture is designed to improve the learning efficiency with the simulated transmission experiences and safe exploration is applied to avoid the risky policies that result in severe data leakage. A deep RL based WBAN transmission scheme is proposed to further improve the secure transmission with lower eavesdropping rate, intercept probability, sensor energy consumption and transmission latency for the coordinators that support deep learning. We analyze the computational complexity and investigate the equilibrium of the secure transmission game between the coordinator and the eavesdropper to provide the performance bounds, which is verified via the simulation results, showing the efficacy of our proposed schemes.

Artificial noise aided directional modulation via reconfigurable intelligent surface: Secrecy guarantee in range domain

Recently, the physical limitation of range-domain security guarantee for directional modulation with frequency diverse array was disclosed in Ding et al. (IEEE Access 8, 63302–63309 (2020)). Therefore, to recreate this significant secrecy realisation in both direction and range domain, the authors conceive an artificial noise aided directional modulation scheme via reconfigurable intelligent surface. Specifically, the angle of departure from the reconfigurable intelligent surface to co-direction receivers varies with distance, which provides the freedom to distinguish users in the range domain. With locations of the active eavesdroppers, an optimisation problem is further formulated to maximise the secrecy rate, which is then solved by applying genetic algorithm and alternating optimisation. On the other hand, when the eavesdroppers are silent, we employ maximum-ratio transmission precoding and artificial noise to guarantee information security. Finally, simulation results demonstrate that, due to the aid of reconfigurable intelligent surface, the developed directional modulation structure can robustly guarantee the information security in the range domain, whether the information of eavesdroppers is achieved.