Covert Communication in UAV-Assisted Air-Ground Networks

Unmanned aerial vehicle (UAV) assisted communication is a promising technique for future wireless networks due to its characteristics of low cost and flexible deployment. However, the high possibility of line-of-sight (LoS) air-ground channels may result in a great risk of being attacked by malicious users. Especially compared to the encryption and physical layer security that prevent eavesdropping, covert communication aims at hiding the existence of transmission, which is able to satisfy the more critical requirement of security. Thus, in this article, we focus on the covert communication issues of UAV-assisted wireless networks. First, the preliminaries of secure communications including encryption, physical layer security and covert communication are discussed. Then, current works and typical applications of UAV in covert communications are demonstrated. We then propose two schemes to enhance the covertness of UAV-assisted networks for some typical scenarios. Specifically, to improve the covert rate in UAV-assisted data dissemination, an iterative algorithm is proposed to jointly optimize the time slot, transmit power and trajectory. For the covertness of ground-air communication, a friendly jammer is employed to confuse the wardens, where the location of the jammer, the jamming power and the legitimate transmit power are jointly optimized. Numerical results are presented to validate the performance of these two proposed schemes. Finally, several challenges and promising directions are pointed out

Blockchain-Based Security Architecture for Unmanned Aerial Vehicles in B5G/6G Services and Beyond: A Comprehensive Approach

Unmanned Aerial Vehicles (UAVs), previously favored by enthusiasts, have evolved into indispensable tools for effectively managing disasters and responding to emergencies. For example, one of their most critical applications is to provide seamless wireless communication services in remote rural areas. Thus, it is substantial to identify and consider the different security challenges in the research and development associated with advanced UAV-based B5G/6G architectures. Following this requirement, the present study thoroughly examines the security considerations about UAVs in relation to the architectural framework of the 5G/6G system, the technologies that facilitate its operation, and the concerns surrounding privacy. It exhibits security integration at all the protocol stack layers and analyzes the existing mechanisms to secure UAV-based B5G/6G communications and its energy and power optimization factors. Last, this article also summarizes modern technological trends for establishing security and protecting UAV-based systems, along with the open challenges and strategies for future research work.Comment: 25 pages, 6 figures, 3 table

Graph Koopman Autoencoder for Predictive Covert Communication Against UAV Surveillance

Low Probability of Detection (LPD) communication aims to obscure the very presence of radio frequency (RF) signals, going beyond just hiding the content of the communication. However, the use of Unmanned Aerial Vehicles (UAVs) introduces a challenge, as UAVs can detect RF signals from the ground by hovering over specific areas of interest. With the growing utilization of UAVs in modern surveillance, there is a crucial need for a thorough understanding of their unknown nonlinear dynamic trajectories to effectively implement LPD communication. Unfortunately, this critical information is often not readily available, posing a significant hurdle in LPD communication. To address this issue, we consider a case-study for enabling terrestrial LPD communication in the presence of multiple UAVs that are engaged in surveillance. We introduce a novel framework that combines graph neural networks (GNN) with Koopman theory to predict the trajectories of multiple fixed-wing UAVs over an extended prediction horizon. Using the predicted UAV locations, we enable LPD communication in a terrestrial ad-hoc network by controlling nodes' transmit powers to keep the received power at UAVs' predicted locations minimized. Our extensive simulations validate the efficacy of the proposed framework in accurately predicting the trajectories of multiple UAVs, thereby effectively establishing LPD communication

Decentralized Covert Routing in Heterogeneous Networks Using Reinforcement Learning

This letter investigates covert routing communications in a heterogeneous network where a source transmits confidential data to a destination with the aid of relaying nodes where each transmitter judiciously chooses one modality among multiple communication modalities. We develop a novel reinforcement learning-based covert routing algorithm that finds a route from the source to the destination where each node identifies its next hop and modality only based on the local feedback information received from its neighboring nodes. We show based on numerical simulations that the proposed covert routing strategy has only negligible performance loss compared to the optimal centralized routing scheme

Resource allocation and trajectory optimization for UAV-enabled multi-user covert communications

In this correspondence, covert air-to-ground communication is investigated to hide the wireless transmission from unmanned aerial vehicle (UAV). The warden's total detection error probability with limited observations is first analyzed. Considering the location uncertainty of the warden, a robust resource allocation and UAV trajectory optimization problem with worst-case covertness constraint is then formulated to maximize the average covert rate. To solve this optimization problem, we propose a block coordinate descent method based iterative algorithm to optimize the time slot allocation, power allocation and trajectory alternately. Numerical results demonstrate the effectiveness of the proposed algorithm in covert communication for UAVs

Covert communication in relay and RIS networks

Covert communication aims to prevent the warden from detecting the presence of communications, i.e. with a negligible detection probability. When the distance between the transmitter and the legitimate receiver is large, large transmission power is needed, which in turn increases the detection probability. Relay is an effective technique to tackle this problem, and various relaying strategies have been proposed for long-distance covert communication in these years. In this article, we first offer a tutorial on the relaying strategies utilized in covert transmission. With the emergence of reflecting intelligent surface and its application in covert communications, we propose a hybrid relay-reflecting intelligent surface (HR-RIS)-assisted strategy to further enhance the performance of covert communications, which simultaneously improves the signal strength received at the legitimate receiver and degrades that at the warden relying on optimizing both the phase and the amplitude of the HR-RIS elements. The numerical results show that the proposed HR-RIS-assisted strategy significantly outperforms the conventional RIS-aided strategy in terms of covert rate

Sensing Aided Covert Communications: Turning Interference into Allies

In this paper, we investigate the realization of covert communication in a general radar-communication cooperation system, which includes integrated sensing and communications as a special example. We explore the possibility of utilizing the sensing ability of radar to track and jam the aerial adversary target attempting to detect the transmission. Based on the echoes from the target, the extended Kalman filtering technique is employed to predict its trajectory as well as the corresponding channels. Depending on the maneuvering altitude of adversary target, two channel models are considered, with the aim of maximizing the covert transmission rate by jointly designing the radar waveform and communication transmit beamforming vector based on the constructed channels. For the free-space propagation model, by decoupling the joint design, we propose an efficient algorithm to guarantee that the target cannot detect the transmission. For the Rician fading model, since the multi-path components cannot be estimated, a robust joint transmission scheme is proposed based on the property of the Kullback-Leibler divergence. The convergence behaviour, tracking MSE, false alarm and missed detection probabilities, and covert transmission rate are evaluated. Simulation results show that the proposed algorithms achieve accurate tracking. For both channel models, the proposed sensing-assisted covert transmission design is able to guarantee the covertness, and significantly outperforms the conventional schemes.Comment: 13 pages, 12 figures, submitted to IEEE journals for potential publicatio