Unmanned Aerial Vehicle Jamming Research Articles

Generative adversarial network based resource optimization for UAV jamming assisted cognitive covert communication

This paper discusses a resource optimization problem for unmanned aerial vehicle (UAV) jamming assisted cognitive covert communication. Specially, the secondary users adopt underlay strategy for spectrum access and the UAV transmits the noise signal to confuse the underlay detection of eavesdropper. According to the dynamic game characteristics in the covert communication process, a new generative adversarial network-based covert communication resource optimization algorithm (GAN-RO) is proposed for the joint optimization of UAV’s trajectory and power in cognitive covert communication assisted by UAV’s interference. The generator simulates the legitimate user to generate the resource allocation scheme, while the discriminator imitates the eavesdropper to detect covert communication. The dynamic game process between the generator and discriminator can obtain covert communication schemes by achieving Nash equilibrium. Simulation results indicate that the proposed GAN-RO algorithm can obtain a near-optimal resource optimization scheme with a rapid converge speed for non-ideal UAV jamming assisted cognitive covert communication system.

Joint Trajectory Design and Resource Allocation for Secure Air–Ground Integrated IoT Networks

We investigate in this paper joint trajectory design and resource allocation for secure air-ground integrated Internet of Things (IoT) networks with unmanned aerial vehicle (UAV) jamming and device to device (D2D) enhancement. By jointly optimizing ground user scheduling, UAV flight trajectory and transmit power, we are able to maximize the minimum system secrecy rate of UAV and D2D communications. The formulated optimization problems of the two typical network scenarios, i.e., with and without UAV jamming, are challenging to be solved due to the corresponding non-smooth and non-concave objective functions. Therefore, we propose alternating iterative algorithms to solve the problems by employing the successive convex approximation and block coordinate descent methods. Extensive results indicate that the proposed joint optimization schemes can effectively improve the secrecy communication performance under different spatial distributions of ground users.

Analysis of Jamming Effects in IRS Assisted UAV Dual-Hop FSO Communication Systems

In this paper, we investigate the effects of jamming caused by a malicious unmanned aerial vehicle (UAV) on the performance of a free-space optical (FSO) communication system using a legitimate UAV as a relay and utilizing an intelligent reflecting surface (IRS) to improve the coverage. We statistically characterize the combined effects of the three impairments on the performance of the considered system: atmospheric turbulence (AT), pointing error (PE), and angle of arrival (AoA) fluctuation of both the UAVs. Incorporating the aforementioned effects, closed-form expressions of the overall average bit error rate (ABER) and outage probability (OP) for the considered system are derived. We also present a comprehensive study of the proposed system by considering different locations of the malicious UAV jammer and IRS and draw some interesting conclusions. Useful insights into the system performance are obtained through the asymptotic analysis. Furthermore, the analytically derived expressions are verified through Monte-Carlo simulations.

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.

Enhancing Reliability and Security of UAV-Enabled NOMA Communications With Power Allocation and Aerial Jamming

In view of the scarce spectrum resources and inconvenient deployment in wireless communications, this work focuses on an unmanned aerial vehicle (UAV) enabled non-orthogonal multiple access (NOMA) system where a UAV deployed as a base station serves two users by NOMA. A joint power allocation and aerial jamming (PAAJ) scheme is proposed to achieve reliable and secure communications for the system in the presence of a malicious eavesdropper. To be specific, dynamic power allocation is adopted to ensure the reliability of the system and another friendly UAV jammer is introduced to improve the security of the system. The closed-form expressions of connection outage probability (COP), secrecy outage probability (SOP), and effective secrecy throughput (EST) are derived to evaluate the performance of the security-required user in the practical condition of probabilistic line-of-sight (LoS) and non-line-of-sight (NLoS) air-to-ground (A2G) channels. Moreover, the asymptotic EST is analyzed to obtain further insights. Numerical results show the validity of theoretical derivations and the superiority of the proposed PAAJ scheme over benchmark schemes. The EST of the UAV-enabled NOMA communication system outperforms the conventional terrestrial NOMA system at the low transmitting power from the UAV base station. There exists an optimal height of the UAV base station to maximize the EST, which provides a useful framework for designing UAV-enabled communication systems with heterogeneous service requirements.

MD-GAN-Based UAV Trajectory and Power Optimization for Cognitive Covert Communications

This article investigates the covert performance of an unmanned aerial vehicle (UAV) jammer-assisted cognitive radio (CR) network. In particular, the covert transmission of secondary users can be effectively protected by UAV jamming against the eavesdropping. For practical consideration, the UAV is assumed to only know certain partial channel distribution information (CDI), whereas not to know the detection threshold of an eavesdropper. For this sake, we propose a model-driven generative adversarial network (MD-GAN)-assisted optimization framework, consisting of a generator and a discriminator, where the unknown channel information and the detection threshold are learned weights. Then, a GAN-based joint trajectory and power optimization (GAN-JTP) algorithm is developed to train the MD-GAN optimization framework for covert communication, which results in the joint solution of the UAV’s trajectory and transmits power to maximize the covert rate and the probability of detection errors. Our simulation results show that the proposed GAN-JTP with a rapid convergence speed can attain near-optimal solutions of the UAV’s trajectory and transmit power for the covert communication.

Variation in the Polarization Loss Factor in an Unmanned Aerial Vehicle Jamming Link Due to the Attitude Change

A method to analyze the variation of the jamming power received by an unmanned aerial vehicle (UAV) receiver according to the change in the attitude of the small UAV is presented. The main interest of the study is in the variation of the polarization loss factor (PLF) in the UAV jamming link due to attitude change, which may be caused by the wind or intended movement. The attitude change is modeled by a combination of three successive rotations using roll, pitch, and yaw, which are defined as UAV rotations. The proposed method is applied to a jamming link, where a small UAV with an omnidirectional antenna is jammed by a jammer antenna on the ground. The method is applied to a plane ground and over a simulated terrain. The variation of the PLF according to the change of UAV attitude may be higher than the generally expected PLF at locations where the height difference between the UAV and the jammer is large, and near the locations where the jammer is located close to the vertical plane containing the rotation axis when the attitude change is represented by one rotation.

Enhanced Intrusion Detection System for an EH IoT Architecture Using a Cooperative UAV Relay and Friendly UAV Jammer

In this paper, the detection capabilities and system performance of an energy harvesting (EH) Internet of Things (IoT) architecture in the presence of an unmanned aerial vehicle (UAV) eavesdropper (UE) are investigated. The communication protocol is divided into two phases. In the first phase, a UAV relay (UR) cooperates with a friendly UAV jammer (UJ) to detect the UE, and the UR and UJ harvest energy from a power beacon (PB). In the second phase, a ground base station (GBS) sends a confidential signal to the UR using non-orthogonal multiple access (NOMA); the UR then uses its harvested energy to forward this confidential signal to IoT destinations (IDs) using the decode-and-forward (DF) technique. Simultaneously, the UJ uses its harvested energy to emit an artificial signal to combat the detected UE. A closed-form expression for the probability of detecting the UE (the detection probability, DP) is derived to analyze the detection performance. Furthermore, the intercept probability (IP) and throughput of the considered IoT architecture are determined. Accordingly, we identify the optimal altitudes for the UR and UJ to enhance the system and secrecy performance. Monte Carlo simulations are employed to verify our approach.

Robust 3D trajectory and power design in probabilistic LoS channel for UAV-enabled cooperative jamming

This paper proposes a mobile unmanned aerial vehicle (UAV)-enabled jamming scheme under the probabilistic line-of-sight (LoS) channel model to improve the secrecy of ground wiretap channels in urban areas, where a friendly UAV is deployed to cooperatively transmit jamming signals to confuse the suspicious ground eavesdroppers. Our goal is to maximize the average (expected) secrecy rate by jointly optimizing the user scheduling, the source's transmit power, the UAV's jamming power and its three-dimensional (3D) trajectory for a given flight time. Since the expected secrecy rate is highly complicated with respect to the 3D UAV trajectory, we derive a more tractable lower bound for it. Nevertheless, the resulting optimization problem is still non-convex and difficult to solve optimally due to the imperfect location information of the eavesdroppers. To tackle such an intractable problem, we first derive a worst-case (expected) secrecy rate, and then we propose an efficient iterative algorithm to obtain a suboptimal solution to it by applying the block coordinate descent (BCD) and successive convex approximation (SCA) techniques. Simulation results show that the proposed algorithm under the probabilistic LoS channel model significantly outperforms various benchmark algorithms.

Securing Communications With Friendly Unmanned Aerial Vehicle Jammers

In this paper, we analyze the impact of a friendly unmanned aerial vehicle (UAV) jammer on UAV communications in the presence of multiple eavesdroppers. We first present channel components determined by the line-of-sight (LoS) probability between the friendly UAV jammer and the ground device, and introduce different channel fadings for LoS and non-line-of-sight (NLoS) links. We then derive the secrecy transmission probability satisfying both constraints of legitimate and wiretap channels. We also analyze the secrecy transmission probability in the presence of randomly distributed multiple friendly UAV jammers. Finally, we show the existence of the optimal UAV jammer location, and the impact of the density of eavesdroppers, the transmission power of the UAV jammer, and the density of UAV jammers on the optimal location.

Enhancing physical layer security via a UAV friendly jammer for NOMA‐based IoT systems with imperfect CSI

AbstractIn this article, we investigate physical layer security in downlink Internet of Things networks under imperfect channel state information (CSI), in which a controller (Alice) intends to serve two user devices (D1 and D2) simultaneously by using nonorthogonal multiple access (NOMA). Cooperative jamming (CJ) is introduced as a powerful solution for guaranteeing secure transmission. To be specific, we integrate an unmanned aerial vehicle (UAV) jammer that generates artificial noise to confuse multiple noncolluding eavesdroppers (Eves). Considering only D1 requires secure transmission, we develop an adaptive power allocation scheme to maximize the secrecy rate at D1 while meeting the desired quality of service (QoS) threshold at D2. Furthermore, a strategy can be utilized to obtain the optimal location of the UAV jammer is derived for further performance enhancement. Besides, we also examine the impact of the channel uncertainties on system performance. Numerical results are provided to confirm the superiority and applicability of the proposed CJ scheme over benchmark schemes in terms of secrecy performance and effective energy efficiency.

Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization.

Wireless networks are vulnerable to jamming attacks. Jamming in wireless communication becomes a major research problem due to ease in Unmanned Aerial Vehicle (UAV) launching and blocking of communication channels. Jamming is a subset of Denial of Service Attack (DoS) and an intentional interference where the malicious node disrupts the wireless communication by increasing the noise at the receiver node through transmission interference signal towards the target channel. In this work, the considered jammer is a UAV hovering around the target area to block the communication channel between two transceivers. We proposed a three-dimensional (3-D) UAV jamming localization scheme to track and detect the jammer position at each time step by employing a single boundary node observer. For this purpose, we developed two distributed Extended Kalman Filter (EKF) based schemes: (1) the Distributed EKF (DEKF) scheme using the information of the received power from the jammer at a single nearby boundary node only and (2) Distance Ratio aided Distributed EKF (DEKF-DR) based scheme utilizing an edge node in addition to a single boundary node. Extensive simulations are conducted in order to evaluate the performance of the proposed distributed algorithms for a 3-D trajectory and compared with that of the conventional Centralized EKF (EKF-Centr) based method (which is also modified for the 3-D scenario). The results show the clear supremacy of the proposed distributed algorithms with much lesser complexity in contrast to the conventional EKF-Centr technique.

Improving PHY-Security of UAV-Enabled Transmission With Wireless Energy Harvesting: Robust Trajectory Design and Communications Resource Allocation

In this paper, we consider an unmanned aerial vehicle (UAV) assisted communications system, including two cooperative UAVs, a wireless-powered ground destination node leveraging simultaneous wireless information and power transfer (SWIPT) technique, and a terrestrial passive eavesdropper. One UAV delivers confidential information to destination and the other sends jamming signals to against eavesdropping and assist destination with energy harvesting. Assuming UAVs have partial information about eavesdropper's location, we propose two transmission schemes: friendly UAV jamming (FUJ) and Gaussian jamming transmission (GJT) for the cases when jamming signals are known and unknown a priori at destination, respectively. Then, we formulate an average secrecy rate maximization problem to jointly optimize the transmission power and trajectory of UAVs, and the power splitting ratio of destination. Being non-convex and hence difficult to solve the formulated problem, we propose a computationally efficient iterative algorithm based on block coordinate descent and successive convex approximation to obtain a suboptimal solution. Finally, numerical results are provided to substantiate the effectiveness of our proposed multiple-UAV schemes, compared to other existing benchmarks. Specifically, we find that the FUJ demonstrates significant secrecy performance improvement in terms of the optimal instantaneous and average secrecy rate compared to the GJT and the conventional single-UAV counterpart.

Anti-Intelligent UAV Jamming Strategy via Deep Q-Networks

The downlink communications are vulnerable to intelligent unmanned aerial vehicle (UAV) jamming attack. In this paper, we propose a novel anti-intelligent UAV jamming strategy, in which the ground users can learn the optimal trajectory to elude such jamming. The problem is formulated as a stackelberg dynamic game, where the UAV jammer acts as a leader and the ground users act as followers. First, as the UAV jammer is only aware of the incomplete channel state information (CSI) of the ground users, for the first attempt, we model such leader sub-game as a partially observable Markov decision process (POMDP). Then, we obtain the optimal jamming trajectory via the developed deep recurrent Q-networks (DRQN) in the three-dimension space. Next, for the followers sub-game, we use the Markov decision process (MDP) to model it. Then we obtain the optimal communication trajectory via the developed deep Q-networks (DQN) in the two-dimension space. We prove the existence of the stackelberg equilibrium and derive the closed-form expression for the stackelberg equilibrium in a special case. Moreover, some insightful remarks are obtained and the time complexity of the proposed defense strategy is analyzed. The simulations show that the proposed defense strategy outperforms the benchmark strategies.

Aerial Cooperative Jamming for Cellular-Enabled UAV Secure Communication Network: Joint Trajectory and Power Control Design.

To improve the secrecy performance of cellular-enabled unmanned aerial vehicle (UAV) communication networks, this paper proposes an aerial cooperative jamming scheme and studies its optimal design to achieve the maximum average secrecy rate. Specifically, a base station (BS) transmits confidential messages to a UAV and meanwhile another UAV performs the role of an aerial jammer by cooperatively sending jamming signals to oppose multiple suspicious eavesdroppers on the ground. As the UAVs have the advantage of the controllable mobility, the objective is to maximize the worst-case average secrecy rate by the joint optimization of the two UAVs’ trajectories and the BS’s/UAV jammer’s transmit/jamming power over a given mission period. The objective function of the formulated problem is highly non-linear regarding the optimization variables and the problem has non-convex constraints, which is, in general, difficult to achieve a globally optimal solution. Thus, we divide the original problem into four subproblems and then solve them by applying the successive convex approximation (SCA) and block coordinate descent (BCD) methods. Numerical results demonstrate that the significantly better secrecy performance can be obtained by using the proposed algorithm in comparison with benchmark schemes.

UAV-Enabled Secure Communications: Joint Trajectory and Transmit Power Optimization

This paper studies the physical layer security of an unmanned aerial vehicle (UAV) network, where a UAV base station (UAV-B) transmits confidential information to multiple information receivers (IRs) with the aid of a UAV jammer (UAV-J) in the presence of multiple eavesdroppers. We formulate an optimization problem to jointly design the trajectories and transmit power of UAV-B and UAV-J in order to maximize the minimum average secrecy rate over all IRs. The optimization problem is non-convex and the optimization variables are coupled, which leads to the optimization problem being mathematically intractable. As such, we decompose the optimization problem into two subproblems and then solve it by employing an alternating iterative algorithm and the successive convex approximation technique. Our results show that the average secrecy rate performance of the proposed scheme provides about 20% and 150% performance gains over the joint trajectory and transmit power optimization without UAV-J scheme and the transmit power optimization with fixed trajectory scheme at flight period $T=150$ s, respectively.

Secure UAV Communication With Cooperative Jamming and Trajectory Control

This letter presents a new cooperative jamming approach to secure the unmanned aerial vehicle (UAV) communication by leveraging jamming from other nearby UAVs to defend against the eavesdropping. In particular, we consider a two-UAV scenario when one UAV transmitter delivers the confidential information to a ground node (GN), and the other UAV jammer cooperatively sends the artificial noise to confuse the ground eavesdropper for protecting the confidentiality of the data transmission. By exploiting the fully controllable mobility, the two UAVs can adaptively adjust their locations over time (a.k.a. trajectories) to facilitate the secure communication and cooperative jamming. We assume that the two UAVs perfectly know the GN's location and partially know the eavesdropper's location a priori. Under this setup, we maximize the average secrecy rate from the UAV transmitter to the GN over one particular time period, by optimizing the UAVs' trajectories, jointly with their communicating/jamming power allocations. Although the formulated problem is non-convex, we propose an efficient solution by applying the techniques of alternating optimization and successive convex approximation.

Improving Physical Layer Security via a UAV Friendly Jammer for Unknown Eavesdropper Location

In this correspondence paper, we consider an unmanned aerial vehicle (UAV) equipped with an air-to-ground friendly jammer assisting secure communications between a legitimate transmitter-receiver pair for unknown eavesdropper location. To enhance the reliability and security of this system, we examine the impact of the UAV jamming power and its three-dimensional (3-D) spatial deployment on the outage probability (OP) of the legitimate receiver and the intercept probability (IP) of the eavesdropper. Based on the IP, we develop a new security measure, which we refer to as the intercept probability security region (IPSR). The IPSR defines the region within a target area where the IP is less than a given threshold. We design a low-complexity iterative algorithm to maximize the IPSR subject to an OP constraint by jointly optimizing the 3-D deployment and jamming power of the UAV jammer. Numerical results show that our proposed iterative algorithm performs close to an exhaustive search with significantly reduced complexity.