Litcius/Paper detail

Covert Communication for Cellular and X2U-Enabled UAV Networks with Active and Passive Wardens

Bin Yang, Tarik Taleb, Guilin Chen, Shikai Shen

2022IEEE Network27 citationsDOI

Abstract

Cellular and X2U-enabled UAV networks are a promising network paradigm to support constantly growing Internet of Things (IoT) applications in 5G and beyond wireless networks, wherein X2U includes the UAV-to-UAV (U2U) and ground IoT device-to-UAV (G2U) communications. However, such networks pose a significant challenge to secure wireless communications due to the open and broadcasting features of wireless channels. Covert communication is an attractive technique to hinder adversaries (i.e., wardens) from detecting the existence of data transmission for guaranteeing secure IoT communications. This article investigates the covert communication issue for a promising network scenario consisting of a BS, UAV swarm, multiple ground IoT devices and wardens. Especially, each UAV/ground IoT device can select cellular or X2U communication mode according to a flexible mode selection scheme which can cover the cellular network and ad hoc network as special cases by setting a bias factor. We design two types of wardens: active wardens who not only detect the legitimate transmission but also jet noise to interfere with legitimate signals, and passive wardens who only detect the legitimate transmission. Cooperative jamming technique is further employed to resist the attacks of wardens. Then, numerical results are provided to explore the effects of the flexible mode selection and the number of wardens on the covert performances like covert capacity and detection error probability. We finally present a vision for future research in the cellular and X2U-enabled UAV networks.

Topics & Concepts

Computer scienceCovertComputer networkTransmission (telecommunications)Computer securityCellular networkWirelessTelecommunicationsWireless networkLinguisticsPhilosophyWireless Communication Security TechniquesUAV Applications and OptimizationFace recognition and analysis