Active Eavesdropper Research Articles

Electromagnetic side-channel attack risk assessment on a practical quantum-key-distribution receiver based on multi-class classification

While quantum key distribution (QKD) is a theoretically secure way of growing quantum-safe encryption keys, many practical implementations are challenged due to various open attack vectors, resulting in many variations of QKD protocols. Side channels are one such vector that allows a passive or active eavesdropper to obtain QKD information leaked through practical devices. This paper assesses the feasibility and implications of extracting the raw secret key from far-field radiated emissions from the single-photon avalanche diodes used in a BB84 QKD quad-detector receiver. Enhancement of the attack was also demonstrated through the use of deep-learning model to distinguish radiated emissions due to the four polarized encoding states. To evaluate the severity of such side-channel attack, multi-class classification based on raw-data and pre-processed data is implemented and assessed. Results show that classifiers based on both raw-data and pre-processed features can discern variations of the electromagnetic emissions caused by specific orientations of the detectors within the receiver with an accuracy higher than 90%. This research proposes machine learning models as a technique to assess EM information leakage risk of QKD and highlights the feasibility of side-channel attacks in the far-field region, further emphasizing the need to utilise mechanisms to avoid electromagnetic radiation information leaks and measurement-device-independent QKD protocols.

Toward Secrecy-Energy-Efficiency Optimization for UAV-Assisted Bidirectional Systems With Active Eavesdroppers

Toward Secrecy-Energy-Efficiency Optimization for UAV-Assisted Bidirectional Systems With Active Eavesdroppers

Secure and covert communication strategy of UAV based on hybrid RF/FSO system

The hybrid radio frequency (RF)/free-space optical (FSO) system can improve communication security by using complimentary characteristics and mitigating the risks of RF links being susceptible to co-channel interference (CCI) and malicious eavesdropping. We investigate the secure and covert communication performance of unmanned aerial vehicles (UAVs) equipped with a hybrid RF/FSO system. In terms of secure communication, UAVs employ the strategy of transmitting private data concurrently through RF and FSO links, considering two modes based on active eavesdropping by a malicious user. Closed-form expressions for the secrecy outage probability (SOP) and effective secrecy throughput (EST) are derived. With respect to covert communication, the communication strategy is to utilize the RF link to generate interfering signals, thus aiding the FSO signals in accomplishing covert communication. We formulate an optimization problem that maximizes the EST while considering transmit power and user-acceptable detection error probability. A two-stage gradient-based iterative solution algorithm is proposed. The numerical results demonstrate the effectiveness of the proposed secure and covert communication strategy based on the hybrid RF/FSO system, which is expected to enhance the communication security of UAVs in the RF-challenged environment.

Enhanced Active Eavesdroppers Detection System for Multihop WSNs in Tactical IoT Applications

Enhanced Active Eavesdroppers Detection System for Multihop WSNs in Tactical IoT Applications

EH Cognitive Network With NOMA: Perspective on Impact of Passive and Active Eavesdropping

EH Cognitive Network With NOMA: Perspective on Impact of Passive and Active Eavesdropping

IRS Backscatter-Based Secrecy Enhancement against Active Eavesdropping

This paper proposes to combat active eavesdropping using intelligent reflecting surface (IRS) backscatter techniques. To be specific, the source (Alice) sends the confidential information to the intended user (Bob), while the eavesdropper (Willie) transmits a jamming signal to interrupt the transmission for more data interception. To enhance the secrecy, an IRS is deployed and connected with Alice through fiber to transform the jamming signal into the confidential signal by employing backscatter techniques. Based on the considered model, an optimization problem is formulated to maximize the signal-to-interference-plus-noise ratio (SINR) at Bob under the constraints of the transmit power at Alice, the reflection vector at the IRS, and the allowable maximum the SINR at Willie. To address the optimization problem, an alternate optimization algorithm is developed. The simulation results verify the achievable secrecy gain of the proposed scheme. The proposed scheme is effective in combating active eavesdropping. Furthermore, the deployment of large-scale IRS significantly enhances the secrecy rate.

Fighting Against Active Eavesdropper: Distributed Pilot Spoofing Attack Detection and Secure Coordinated Transmission in Multi-cell Massive MIMO Systems

Fighting Against Active Eavesdropper: Distributed Pilot Spoofing Attack Detection and Secure Coordinated Transmission in Multi-cell Massive MIMO Systems

Active Eavesdropping Attack Scheduling for Cyber-Physical Systems With Operation Constraints

Active Eavesdropping Attack Scheduling for Cyber-Physical Systems With Operation Constraints

Secure RIS-Aided MISO-NOMA System Design in the Presence of Active Eavesdropping

As for the time-division communications system, the pilot spoofing attack technique is maliciously utilized by active eavesdroppers during the uplink training phase, for contaminating the legitimate channel estimation and thus altering the beamforming design towards the eavesdroppers. Nonorthogonal multiple access (NOMA) has been recognized as the key technology for the envisioned Internet of Things (IoT) networks. In order to prevent the aforementioned information leakage in NOMA-IoT systems, we develop a novel two-way training scheme to detect pilot spoofing attack and a robust secure beamforming design for providing secure transmission, by utilizing the emerging technique of reconfigurable intelligent surface (RIS), which is turned off during the uplink training phase and turned on during the downlink training phase, respectively. Considering that the perfect channel state information related to the eavesdropping channel is typically difficult to obtain, a secrecy outage probability constrained robust secure beamforming design is proposed to maximize the achievable sum secrecy rate of the legitimate users, by alternatively optimizing the active beamforming and RIS passive beamforming, while satisfying the requirements of the NOMA transmission. Elaborate simulation results reveal that the proposed detection method attains a super pilot spoofing attack detection performance and the proposed robust secure beamforming design is capable of efficiently enhancing the achievable sum secrecy rate, compared with various benchmark schemes.

Zero-Forcing Beamforming for RIS-Enhanced Secure Transmission

This article considers a reconfigurable intelligent surface (RIS) enhanced multi-antenna secure transmission system in the presence of both active eavesdroppers (AEves) and passive eavesdroppers (PEves). We propose a zero-forcing (ZF) beamforming strategy that can steer transmit beam to the null space of AEves' channel, while simultaneously enhancing the SNRs for a legitimate user equipment (UE) and PEves without perfect channel state information (CSI). The design goal is to maximize the SNR of UE subject to the transmit power constraint at the BS, SNR limitations on PEves, and reflection constraints at RIS. Due to the complexity of modeling, we first introduce a homogeneous Poisson point process (HPPP) to imitate the distribution of spatially random PEves, which derives a complicated non-convex problem. We then develop an efficient alternating algorithm where the transmit beamforming vector and the reflective beamforming vector are obtained by convex-concave procedure (CCP) and semi-definite relaxation (SDR) technique, respectively. Simulation results validate the performance advantages of the proposed optimized design.

UAV-assisted ISAC network physical layer security based on Stackelberg game

This paper deals with the physical layer security for multi-unmanned aerial vehicle (UAV) assisted transmission of integrated sensing and communication (ISAC) signals from a dual-function base station (BS) to the ground user. Here, an active eavesdropper (Eve) on the ground eavesdrops on the information transmitted by the UAV network to the user. We propose a Stackelberg game model for the game problem of information security transmission between UAV and Eve, with perfect or imperfect channel state information (CSI) and cost information. To deal with the Stackelberg game problem, the dual optimization theory and KKT conditions are used to solve it, then we prove the existence and uniqueness of Stackelberg equilibrium (SE). At the same time, considering that the influence of ISAC signal’s sensing of Eve’s location on the distance between Eve and the user, and thus on the utility function of both sides of the game, this paper uses the Cramer–Rao bound (CRB) to represent the accurate performance of location sensing. Then the relaxation method is used for the non-convex optimization problem, and convex optimization tools can be used subsequently. Finally we notice that both operations have their own optimal resolution strategy, it is difficult to reach agreement, therefore an overall algorithm is proposed to solve the whole problem iteratively. In the simulation results, the effect of power on game and location sensing, and the effect of the distance between Eve and the user on the utility function of both sides of the game are given. In addition, we give the relationship between the CRB threshold and the transmit power, and verify the convergence of the game and overall algorithm.

The Forgery Attack on the Post-Quantum AJPS-2 Cryptosystem and Modification of the AJPS-2 Cryptosystem by Changing the Class of Numbers Used as a Module

In recent years, post-quantum (quantum-resistant) cryptography has been actively researched, in particular, due to the National Institute of Standards and Technology's (NIST) Post-Quantum Cryptography Competition (PQC), which has been running since 2017. One of the participants in the first round of the competition is the Mersenne-756839 key encapsulation mechanism based on the AJPS-2 encryption scheme. The arithmetic modulo Mersenne number is used to construct the cryptoprimitives of the AJPS family. In this paper, we propose a forgery attack on the AJPS-2 cryptosystem using an active eavesdropper, and two modifications of the post-quantum AJPS-2 cryptosystem, namely, the modification of AJPS-2 using the arithmetic modulo generalized Mersenne number and Crandall number. Moreover, new algebraic problems are defined, on the complexity of which the security of the created modifications is based. The advantages of these modifications are the extension of the number class used as a module in the cryptosystem and the security against the forgery attack with the active eavesdropper, which was successful in the original AJPS-2.

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.

Cooperative jamming aided securing wireless communications without CSI of eavesdroppers

Physical layer security was designed as an effective solution to provide the security and confidentiality of information transmission in wireless networks, and secrecy transmission capacity (STC) played a key role in analyzing the impact of system parameters on physical layer security. Different from the previous works, which exploited cooperative jamming to improve the security with the assumption of perfect channel state information (CSI) of eavesdroppers (Eves), in this paper, without considering Eves’ CSI, we designed two secrecy improvement strategies aided by cooperative jamming with transmit power allocation scheme, i.e., connection guard zone (CGZ) and improved interferer protected zone (IIPZ). Specifically, we established an analytical framework of the STC by applying the tools of stochastic geometry and derived conditions that achieved a positive STC. In addition, we consider the impact of Random WayPoint (RWP) mobile receiver and active eavesdroppers on physical layer security. Simulations showed that IIPZ achieves the best reliability performance and CGZ makes the best secrecy performance than existing popular protections, and RWP mobile destination can achieve a higher level of reliability and STC than these achievable in static scenarios.

Spatial Sparsity-Based Pilot Attack Detection and Transmission Countermeasure for Cell-Free Massive MIMO System

In this article, we investigate the security performance of a cell-free (CF) massive multiple-input–multiple-output (MIMO) system that is composed of a large number of randomly distributed access points (APs) and multiple users. There may be an eavesdropper who launches an active pilot attack during uplink channel estimation stage to eavesdrop on information in data transmission stage, which threaten the security of the system. A spatial sparsity-based pilot attack detection (SS-based-PAD) method is proposed in this study to determine whether there is an active eavesdropper. Different data transmission schemes were developed according to the detection results. In the presence of an eavesdropper, rate maximization power allocation (SRM-PA) algorithm is proposed to maximize the security of the eavesdropped user. On the contrary, achievable rate equalization power allocation (ARE-PA) algorithm is proposed to provide fair services for all legitimate users. Moreover, an AP selection scheme and corresponding conjugate beamforming are used to enhance the security performance of the system and mitigate the impact of a pilot spoofing attack.

Hybrid precoding design for secure smart-grid enabled MIMO wireless communications in Industry 5.0

Secure and reliable wireless communication systems are essential for the successful integration of smart grid-enabled wireless communications and Industry 5.0 applications. This work proposes a hybrid precoding design for secure smart-grid multiple-input multiple-output (MIMO) wireless communications in Industry 5.0 to maximize the average secrecy capacity of the system while minimizing user outages crucial for maintaining the security and privacy of sensitive data in critical infrastructure. To achieve this, we develop a mathematical model that considers the impact of various system parameters, such as eavesdropping and interference caused by the active eavesdropper and noise, on the secrecy capacity. To find an efficient solution to the optimization problem, we propose an algorithm that decouples the original optimization problem into a series of subproblems and uses iterative techniques to find the optimal values, thereby improving computational efficiency. The hybrid precoding scheme is an effective technique for optimizing the design parameters of MIMO-based secure wireless communication systems. Our proposed approach provides a practical solution for achieving this optimization. Our numerical results demonstrate that our proposed scheme outperforms traditional benchmark schemes, maximizing the average secrecy capacity while minimizing user outages. Our work highlights the importance of secure wireless communication systems in Industry 5.0 and smart grid applications. The proposed approach provides an efficient method for designing secure wireless communication systems that can effectively address the unique challenges posed by these critical infrastructure systems.

Secure SWIPT-powered UAV communication against full-duplex active eavesdropper

Secure SWIPT-powered UAV communication against full-duplex active eavesdropper

QoS-aware secure transmission design for VLC with semi-grant-free NOMA scheme.

This work aims to enhance the physical layer security (PLS) of non-orthogonal multiple access (NOMA) aided indoor visible light communication (VLC) system with semi-grant-free (SGF) transmission scheme, in which a grant-free (GF) user shares the same resource block with a grant-based (GB) user whose quality of service (QoS) must be strictly guaranteed. Besides, the GF user is also provided with an acceptable QoS experience, which is closely aligned with the practical application. Both active and passive eavesdropping attacks are discussed in this work, where users' random distributions are taken into account. Specifically, to maximize the secrecy rate of the GB user in the presence of an active eavesdropper, the optimal power allocation policy is obtained in exact closed-form and the user fairness is then assessed by Jain's fairness index. Moreover, the secrecy outage performance of the GB user is analyzed in the presence of the passive eavesdropping attack. Both exact and asymptotic theoretical expressions for the secrecy outage probability (SOP) of the GB user are derived, respectively. Furthermore, the effective secrecy throughput (EST) is investigated on the basis of the derived SOP expression. Through simulations, it is found that the PLS of this VLC system can be significantly improved by the proposed optimal power allocation scheme. The radius of the protected zone, the outage target rate for the GF user, and the secrecy target rate for the GB user would have pronounced impacts on the PLS and user fairness performance of this SGF-NOMA assisted indoor VLC system. The maximum EST will increase with the increasing transmit power and it is hardly influenced by the target rate for the GF user. This work will benefit the design of indoor VLC system.

Cellular Network Enabled Energy-Harvesting Secure Communications for Full-Duplex D2D Links

This article investigates the secure transmissions for a wireless powered full-duplex (FD) device-to-device (D2D) overlay system. To coordinate the cellular downlink transmissions and the D2D transmissions, we propose a two-phase transmission protocol, where the first phase is dedicated to the transmissions of information and energy from the base station (BS) to its users and the devices, respectively, and the second phase is dedicated to information exchanging between the two devices over an FD link overheard by either active or passive eavesdroppers. In the case of active eavesdroppers, perfect channel state information (CSI) is assumed to be available, whereas for passive eavesdroppers, only statistic CSI is available. Both self-interference (SI) mitigation and BS-aided cooperative jamming are considered for the D2D secure transmissions. For system design, nonconvex power minimization problems under transmission rate constraints are formulated and convex approximated for efficiently obtaining numerical solutions. Simulation results show that the proposed scheme can well coordinate the cellular transmissions and the FD-D2D secure transmissions, while the cooperative jamming strategy can enhance the D2D transmission security, especially in the case of passive eavesdroppers.

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.