Two-Way Aerial Secure Communications via Distributed Collaborative Beamforming under Eavesdropper Collusion (2404.07444v1)
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.
- Z. Dai, C. H. Liu, Y. Ye, R. Han, Y. Yuan, G. Wang, and J. Tang, “Aoi-minimal UAV crowdsensing by model-based graph convolutional reinforcement learning,” in Proc. IEEE INFOCOM, 2022, pp. 1029–1038.
- M. Zhang, Y. Xiong, S. X. Ng, and M. El-Hajjar, “Content-aware transmission in UAV-assisted multicast communication,” IEEE Trans. Wirel. Commun., 2023, early access, doi: 10.1109/twc.2023.3248266.
- N. L. Prasad and B. Ramkumar, “3-D deployment and trajectory planning for relay based UAV assisted cooperative communication for emergency scenarios using dijkstra’s algorithm,” IEEE Trans. Veh. Technol., vol. 72, no. 4, pp. 5049–5063, 2023.
- H. Hydher, D. N. K. Jayakody, K. T. Hemachandra, and T. Samarasinghe, “UAV deployment for data collection in energy constrained WSN system,” in Proc. IEEE INFOCOM - Workshops, 2022.
- A. I. Abubakar, M. S. Mollel, O. Onireti, M. Ozturk, I. Ahmad, S. M. Asad, Y. Sambo, A. Zoha, S. Hussain, and M. A. Imran, “Coverage and throughput analysis of an energy efficient UAV base station positioning scheme,” Computer Networks, vol. 6, no. 6, p. 109854, 2023.
- Z. Ma, B. Ai, R. He, G. Wang, Y. Niu, and Z. Zhong, “A wideband non-stationary air-to-air channel model for UAV communications,” IEEE Trans. Veh. Technol., vol. 69, no. 2, pp. 1214–1226, 2020.
- X. Shi, A. Wang, G. Sun, J. Li, and X. Zheng, “Air to air communications based on UAV-enabled virtual antenna arrays: A multi-objective optimization approach,” in Proc. IEEE WCNC, 2022, pp. 878–883.
- Y. Cao, S. Xu, J. Liu, and N. Kato, “IRS backscatter enhancing against jamming and eavesdropping attacks,” IEEE Internet Things J., vol. 10, no. 12, pp. 10 740–10 751, 2023.
- S. Feng, X. Lu, S. Sun, D. Niyato, and E. Hossain, “Securing large-scale D2D networks using covert communication and friendly jamming,” IEEE Trans. Wirel. Commun., 2023, early access, doi:10.1109/TWC.2023.3280464.
- S. J. Maeng, Y. Yapici, I. Güvenç, A. Bhuyan, and H. Dai, “Precoder design for physical-layer security and authentication in massive MIMO UAV communications,” IEEE Trans. Veh. Technol., vol. 71, no. 3, pp. 2949–2964, 2022.
- Y. Yapici, N. Rupasinghe, I. Güvenç, H. Dai, and A. Bhuyan, “Physical layer security for NOMA transmission in mmwave drone networks,” IEEE Trans. Veh. Technol., vol. 70, no. 4, pp. 3568–3582, 2021.
- Z. Yin, M. Jia, N. Cheng, W. Wang, F. Lyu, Q. Guo, and X. Shen, “UAV-assisted physical layer security in multi-beam satellite-enabled vehicle communications,” IEEE Trans. Intell. Transp. Syst., vol. 23, no. 3, pp. 2739–2751, 2022.
- G. Zhang, Q. Wu, M. Cui, and R. Zhang, “Securing UAV communications via joint trajectory and power control,” IEEE Trans. Wirel. Commun., vol. 18, no. 2, pp. 1376–1389, 2019.
- Z. Na, C. Ji, B. Lin, and N. Zhang, “Joint optimization of trajectory and resource allocation in secure UAV relaying communications for internet of things,” IEEE Internet Things J., vol. 9, no. 17, pp. 16 284–16 296, 2022.
- G. Sun, Y. Liu, Z. Chen, A. Wang, Y. Zhang, D. Tian, and V. C. M. Leung, “Energy efficient collaborative beamforming for reducing sidelobe in wireless sensor networks,” IEEE Trans. Mob. Comput., vol. 20, no. 3, pp. 965–982, 2021.
- S. Jayaprakasam, S. K. A. Rahim, and C. Y. Leow, “Distributed and collaborative beamforming in wireless sensor networks: Classifications, trends, and research directions,” IEEE Commun. Surv. Tutorials, vol. 19, no. 4, pp. 2092–2116, 2017.
- Y. Li, N. I. Miridakis, T. A. Tsiftsis, G. Yang, and M. Xia, “Air-to-air communications beyond 5G: A novel 3D CoMP transmission scheme,” IEEE Trans. Wirel. Commun., vol. 19, no. 11, pp. 7324–7338, 2020.
- K. Humadi, I. Trigui, W. Zhu, and W. Ajib, “Energy-efficient cluster sizing for user-centric air-to-air networks,” IEEE Commun. Lett., vol. 25, no. 4, pp. 1308–1312, 2021.
- A. Fakhreddine, C. Raffelsberger, M. Sende, and C. Bettstetter, “Experiments on drone-to-drone communication with Wi-Fi, LTE-A, and 5G,” in Proc. IEEE Globecom Workshops, 2022, pp. 904–909.
- S. Mohanti, C. Bocanegra, S. G. Sanchez, K. Alemdar, and K. R. Chowdhury, “SABRE: swarm-based aerial beamforming radios: Experimentation and emulation,” IEEE Trans. Wirel. Commun., vol. 21, no. 9, pp. 7460–7475, 2022.
- G. Sun, J. Li, Y. Liu, S. Liang, and H. Kang, “Time and energy minimization communications based on collaborative beamforming for UAV networks: A multi-objective optimization method,” IEEE J. Sel. Areas Commun., vol. 39, no. 11, pp. 3555–3572, 2021.
- J. Li, H. Kang, G. Sun, S. Liang, Y. Liu, and Y. Zhang, “Physical layer secure communications based on collaborative beamforming for UAV networks: A multi-objective optimization approach,” in Proc. IEEE INFOCOM, 2021, pp. 1–10.
- J. Feng, Y. Lu, B. Jung, D. Peroulis, and Y. C. Hu, “Energy-efficient data dissemination using beamforming in wireless sensor networks,” ACM Trans. Sens. Networks, vol. 9, no. 3, pp. 31:1–31:30, 2013.
- I. Ahmad, C. Sung, D. Kramarev, G. Lechner, H. Suzuki, and I. Grivell, “Outage probability and ergodic capacity of distributed transmit beamforming with imperfect CSI,” IEEE Trans. Veh. Technol., vol. 71, no. 3, pp. 3008–3019, 2022.
- M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Communications and control for wireless drone-based antenna array,” IEEE Trans. Commun., vol. 67, no. 1, pp. 820–834, 2019.
- G. Faraci, C. Grasso, and G. Schembra, “Reinforcement-learning for management of a 5G network slice extension with UAVs,” in Proc. IEEE INFOCOM, 2019, pp. 732–737.
- L. T. Dung and T. Kim, “Modeling and simulation of secure connectivity and hop count of multi-hop ad-hoc wireless networks with colluding and non-colluding eavesdroppers,” Ad Hoc Networks, vol. 122, p. 102620, 2021.
- J. Tang, G. Liu, and Q. Pan, “A review on representative swarm intelligence algorithms for solving optimization problems: Applications and trends,” IEEE CAA J. Autom. Sinica, vol. 8, no. 10, pp. 1627–1643, 2021.
- S. Mirjalili, P. Jangir, and S. Saremi, “Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems,” Appl. Intell., vol. 46, no. 1, pp. 79–95, 2017.
- B. Kazimipour, X. Li, and A. K. Qin, “A review of population initialization techniques for evolutionary algorithms,” in IEEE CEC, 2014, pp. 2585–2592.
- J. Li, G. Sun, H. Kang, A. Wang, S. Liang, Y. Liu, and Y. Zhang, “Multi-objective optimization approaches for physical layer secure communications based on collaborative beamforming in UAV networks,” IEEE/ACM Trans. Netw., 2023, early access, doi: 10.1109/TNET.2023.3234324.
- S. Z. Mirjalili, S. Mirjalili, S. Saremi, H. Faris, and I. Aljarah, “Grasshopper optimization algorithm for multi-objective optimization problems,” Appl. Intell., vol. 48, no. 4, pp. 805–820, 2018.
- S. Mirjalili, P. Jangir, S. Z. Mirjalili, S. Saremi, and I. N. Trivedi, “Optimization of problems with multiple objectives using the multi-verse optimization algorithm,” Knowl. Based Syst., vol. 134, pp. 50–71, 2017.
- S. Mirjalili, A. H. Gandomi, S. Z. Mirjalili, S. Saremi, H. Faris, and S. M. Mirjalili, “Salp swarm algorithm: A bio-inspired optimizer for engineering design problems,” Adv. Eng. Softw., vol. 114, pp. 163–191, 2017.
- S. Mirjalili, “Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems,” Neural Comput. Appl., vol. 27, no. 4, pp. 1053–1073, 2016.
- J. Li, G. Sun, L. Duan, and Q. Wu, “Multi-objective optimization for UAV swarm-assisted IoT with virtual antenna arrays,” IEEE Trans. Mob. Comput., 2023, early access, doi: 10.1109/TMC.2023.3298888.
- J. C. Ferreira, C. M. Fonseca, and A. Gaspar-Cunha, “Methodology to select solutions from the pareto-optimal set: a comparative study,” in Proc. ACM GECCO, 2007, pp. 789–796.
- H. Zhou, F. Hu, M. Juras, A. B. Mehta, and Y. Deng, “Real-time video streaming and control of cellular-connected UAV system: Prototype and performance evaluation,” IEEE Wirel. Commun. Lett., vol. 10, no. 8, pp. 1657–1661, 2021.
- S. Jeong, M. Murayama, and K. Yamamoto, “Efficient optimization design method using kriging model,” J. Aircr., vol. 42, no. 2, pp. 413–420, 2005.
- R. Bhanot and R. Hans, “A review and comparative analysis of various encryption algorithms,” Int. J. Secur. its Appl., vol. 9, no. 4, pp. 289–306, 2015.