Two-Way Aerial Secure Communications via Distributed Collaborative Beamforming under Eavesdropper Collusion
Jiahui Li, Geng Sun, Qingqing Wu, Shuang Liang, Pengfei Wang, Dusit Niyato
Abstract
Unmanned aerial vehicles (UAVs)-enabled aerial communication provides a flexible, reliable, and cost-effective solution for a range of wireless applications. However, due to the high line-of-sight (LoS) probability, aerial communications between UAVs are vulnerable to eavesdropping attacks, particularly when multiple eavesdroppers collude. In this work, we aim to introduce distributed collaborative beamforming (DCB) into UAV swarms and handle the eavesdropper collusion by controlling the corresponding signal distributions. Specifically, we consider a two-way DCB-enabled aerial communication between two UAV swarms and construct these swarms as two UAV virtual antenna arrays. Then, we minimize the two-way known secrecy capacity and the maximum sidelobe level to avoid information leakage from the known and unknown eavesdroppers, respectively. Simultaneously, we also minimize the energy consumption of UAVs for constructing virtual antenna arrays. Due to the conflicting relationships between secure performance and energy efficiency, we consider these objectives as a multi-objective optimization problem. Following this, we propose an enhanced multi-objective swarm intelligence algorithm via the characterized properties of the problem. Simulation results show that our proposed algorithm can obtain a set of informative solutions and outperform other state-of-the-art baseline algorithms. Experimental tests demonstrate that our method can be deployed in limited computing power platforms of UAVs and is beneficial for saving computational resources.
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Builds on2
- AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement LearningZipeng Dai, Chi Harold Liu, Yuxiao Ye, Rui Han et al.INFOCOM 2022 · 72 citations
- Physical Layer Secure Communications Based on Collaborative Beamforming for UAV Networks: A Multi-objective Optimization ApproachJiahui Li, Hui Kang, Geng Sun, Shuang Liang et al.INFOCOM 2021 · 48 citations
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