Abstract
Unmanned Aerial Vehicles (UAVs) serve as highly versatile and efficient tools utilized across diverse industries for data collection purposes. However, they face vulnerabilities associated with wireless communication and data exchange, such as unauthorized access, data theft, and cyberattacks. These risks pose significant challenges to the establishment of reliable UAV network services. This study introduces a comprehensive blockchain-based architecture for UAV network services, designed to address these challenges. The proposed architecture tackles concerns related to identity authentication and privacy protection through the seamless integration of blockchain technology. Moreover, it incorporates advanced deep learning techniques to enhance UAV safety during operations and provide robust protection against cyber threats. A series of experimental tests were conducted, simulating various UAV network attack scenarios. The results of these experiments unequivocally demonstrate the feasibility and effectiveness of the blockchain-driven UAV network service architecture.
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References
Gupta, L., Jain, R., Vaszkun, G.: Survey of important issues in UAV communication networks. IEEE Commun. Surv. Tutorials 18(2), 1123–1152 (2015)
Hayat, S., Yanmaz, E., Muzaffar, R.: Survey on unmanned aerial vehicle networks for civil applications: a communications viewpoint. IEEE Commun. Surv. Tutorials 18(4), 2624–2661 (2016)
Zhang, Q., Jiang, M., Feng, Z., et al.: IoT enabled UAV: network architecture and routing algorithm. IEEE Internet Things J. 6(2), 3727–3742 (2019)
Srivastava, A., Prakash, J.: Internet of low-altitude UAVs (IoLoUA): a methodical modeling on integration of internet of “Things’’ with “UAV’’ possibilities and tests. Artif. Intell. Rev. 56(3), 2279–2324 (2023)
Datta, S.K., Dugelay, J.L., Bonnet, C.: IoT based UAV platform for emergency services. In: Proceedings of the International Conference on Information and Communication Technology Convergence, ICTC 2018, pp. 144–147 (2018)
Lihua, Z., Jianfeng, D., Yu, W., et al.: An online priority configuration algorithm for the UAV swarm in complex context. Procedia Comput. Sci. 150, 567–578 (2019)
Dai, M., Huang, N., Wu, Y., et al.: Unmanned-aerial-vehicle-assisted wireless networks: advancements, challenges, and solutions. IEEE Internet Things J. 10(5), 4117–4147 (2022)
Orsino, A., Ometov, A., Fodor, G., et al.: Effects of heterogeneous mobility on D2D-and drone-assisted mission-critical MTC in 5G. IEEE Commun. Mag. 55(2), 79–87 (2017)
Peng, S., Zhou, F., Li, J., et al.: Efficient, dynamic and identity-based remote data integrity checking for multiple replicas. J. Netw. Comput. Appl. 134, 72–88 (2019)
Strobel, V., Castelló, F.E., Dorigo, M.: Blockchain technology secures robot swarms: a comparison of consensus protocols and their resilience to byzantine robots. Front. Robot. AI 7, 54 (2020)
Wen, Q., Gao, Y., Chen, Z., et al.: A blockchain-based data sharing scheme in the supply chain by IIoT. In: Proceedings of the IEEE International Conference on Industrial Cyber Physical Systems, ICPS 2019, pp. 695–700 (2019)
Gao, Y., Chen, Y., Hu, X., et al.: Blockchain based IIoT data sharing framework for SDN-enabled pervasive edge computing. IEEE Trans. Industr. Inf. 17(7), 5041–5049 (2020)
Han, P., Sui, A., Wu, J.: Identity management and authentication of a UAV swarm based on a blockchain. Appl. Sci. 12(20), 10524 (2022)
Millard, A.G., Timmis, J., Winfield, A.F.T.: Towards exogenous fault detection in swarm robotic systems. In: Natraj, A., Cameron, S., Melhuish, C., Witkowski, M. (eds.) TAROS 2013. LNCS, vol. 8069, pp. 429–430. Springer, Heidelberg (2013)
Castelló Ferrer, E.: The blockchain: a new framework for robotic swarm systems. In: Arai, K., Bhatia, R., Kapoor, S. (eds.) FTC 2018. AISC, vol. 881, pp. 1037–1058. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-02683-7_77
Wang, J., Liu, Y., Niu, S., et al.: Lightweight blockchain assisted secure routing of swarm UAS networking. Comput. Commun. 165, 131–140 (2021)
Nguyen, T., Katila, R., Gia, T.N.: A novel internet-of-drones and blockchain-based system architecture for search and rescue. In: Proceedings of the International Conference on Mobile Ad Hoc and Smart Systems, MASS 2021, pp. 278–288 (2021)
Lee, S., Kim, M., Kim, M., et al.: Timely update probability analysis of blockchain ledger in UAV-assisted data collection networks. In: Proceedings of the International Conference on Communications, ICC 2022, pp. 4559–4564 (2022)
Ghribi, E., Khoei, T.T., Gorji, H.T., et al.: A secure blockchain-based communication approach for UAV networks. In: Proceedings of the International Conference on Electro Information Technology, EIT 2020, pp. 411–415 (2020)
Li, G., He, B., Wang, Z., et al.: Blockchain-enhanced spatiotemporal data aggregation for UAV-assisted wireless sensor networks. IEEE Trans. Industr. Inf. 18(7), 4520–4530 (2021)
Safavat, S., Rawat, D.B.: OptiML: an enhanced ML approach towards design of SDN based UAV networks. In: Proceedings of the International Conference on Communications, ICC 2022, pp. 1–6 (2022)
Mershad, K.: PROACT: parallel multi-miner proof of accumulated trust protocol for internet of drones. Veh. Commun. 36, 100495 (2022)
Chen, J., Feng, Z., Wen, J.Y., et al.: A container-based DoS attack-resilient control framework for real-time UAV systems. In: Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, DATE 2019, pp. 1222–1227 (2019)
Acknowledgment
The authors would like to thank the reviewers for their helpful comments and suggestions. This work was supported by the National Key Project of China (No. 2020YFB1005700).
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Li, Z., Chen, Q., Mo, W., Wang, X., Hu, L., Cao, Y. (2024). Converging Blockchain and Deep Learning in UAV Network Defense Strategy: Ensuring Data Security During Flight. In: Vaidya, J., Gabbouj, M., Li, J. (eds) Artificial Intelligence Security and Privacy. AIS&P 2023. Lecture Notes in Computer Science, vol 14509. Springer, Singapore. https://doi.org/10.1007/978-981-99-9785-5_12
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DOI: https://doi.org/10.1007/978-981-99-9785-5_12
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