Abstract
The introduction of ferry UAVs (message ferry) in the UAV network is an effective means to solve the cooperative communication of multiple UAVs. The ferry UAVs act as message collectors and throwers in the network to improve data transmission efficiency, the critical roles that ferry plays have made them the target of sophisticated attacks, ferry should be protected, otherwise, routing efficiency and data delivery of the network will be affected. Since the movement mode of ferry nodes is different from the ordinary nodes, this paper attempts to distinguish ordinary node and ferry node through trajectory analysis, then we propose a Trajectory-based message Ferry Recognition Attack (TFRA) which is easy for an attacker to implement, using the idea of trajectory clustering to distinguish the trajectory of the ferry node, and obtain the location for further attacks. At the same time, we conducted a systematic study on the existing path planning scheme of ferry node, and summarized several typical types of message ferry path planning schemes, then evaluated the performance of TFRA in these schemes. The results show TFRA can attack ferry nodes with high accuracy and recognition rate.
Sponsored by the Natural Science Foundation of China (Grant No. 61902199); NUPTSF (Grant No. NY219142); State Key Laboratory for Novel Software Technology (Grant No. KFKT2019B13).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Crazyflie 2.1. https://www.bitcraze.io/products/crazyflie-2-1/
Radar data processing. https://grasswiki.osgeo.org/wiki/Radar_data_processing
Sklearn:feature selection and recursive feature elimination. https://scikit-learn.org, https://www.scikit-yb.org
Agrawal, P., Ghosh, R.K., Das, S.K.: Cooperative black and gray hole attacks in mobile ad hoc networks. In: Proceedings of the 2nd International Conference on Ubiquitous Information Management and Communication, pp. 310–314 (2008)
Alnuaimi, M., Shuaib, K., Alnuaimi, K., Abdel-Hafez, M.: Data gathering in delay tolerant wireless sensor networks using a ferry. Sensors 15(10), 25809–25830 (2015)
Alt, H., Godau, M.: Computing the fréchet distance between two polygonal curves. Int. J. Comput. Geomet. Appl. 5(01n02), 75–91 (1995)
Ammar, M., Chakrabarty, D., Sarma, A.D., Kalyanasundaram, S., Lipton, R.J.: Algorithms for message ferrying on mobile ad hoc networks. In: IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science. Schloss Dagstuhl-Leibniz-Zentrum für Informatik (2009)
Asadpour, M., Hummel, K.A., Giustiniano, D., Draskovic, S.: Route or carry: motion-driven packet forwarding in micro aerial vehicle networks. IEEE Trans. Mobile Comput. 16(3), 843–856 (2016)
Atev, S., Miller, G., Papanikolopoulos, N.P.: Clustering of vehicle trajectories. IEEE Trans. Intell. Transp. Syst. 11(3), 647–657 (2010)
Barton, D.K.: Modern radar system analysis. ah (1988)
Tariq, M.M.B., Ammar, M., Zegura, E.: Message ferry route design for sparse ad hoc networks with mobile nodes. In: Proceedings of the 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 37–48 (2006)
Deza, M.M., Deza, E.: Encyclopedia of distances. In: Encyclopedia of distances, pp. 1–583. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-00234-2
Guangjie Han, X., Miao, H.W., Guizani, M., Zhang, W.: CPSLP: a cloud-based scheme for protecting source location privacy in wireless sensor networks using multi-sinks. IEEE Trans. Veh. Technol. 68(3), 2739–2750 (2019)
Han, G., Zhou, L., Wang, H., Zhang, W., Chan, S.: A source location protection protocol based on dynamic routing in WSNS for the social internet of things. Futur. Gener. Comput. Syst. 82, 689–697 (2018)
Hu, C.-L., Lin, H.-Y., Hsu, Y.-F., Huang, S.-Z., Hui, L., Zhang, Z.: Message forwarding with ferries in delay-tolerant networks. In: 2019 28th Wireless and Optical Communications Conference (WOCC), pp. 1–5. IEEE (2019)
Jiang, J., Han, G., Wang, H., Guizani, M.: A survey on location privacy protection in wireless sensor networks. J. Netw. Comput. Appl. 125, 93–114 (2019)
Konstantopoulos, C., Pantziou, G., Vathis, N., Nakos, V., Gavalas, D.: Efficient mobile sink-based data gathering in wireless sensor networks with guaranteed delay. In: Proceedings of the 12th ACM International Symposium on Mobility Management and Wireless Access, pp. 47–54 (2014)
Manathara, J.G., Sujit, P.B., Beard, R.W.: Multiple UAV coalitions for a search and prosecute mission. J. Intell. Robot. Syst. 62(1), 125–158 (2011)
Maza, I., Caballero, F., Capitán, J., Dios, J.R.M., Ollero, A.: Experimental results in multi-UAV coordination for disaster management and civil security applications. J. Intell. Robot. Syst. 61(1–4), 563–585 (2011)
Merino, L., Caballero, F., Ramiro Martínez-De-Dios, J., Maza, I., Ollero, A.: An unmanned aircraft system for automatic forest fire monitoring and measurement. J. Intell. Robot. Syst. 65(1–4), 533–548 (2012)
Pu, C., Carpenter, L.: To route or to ferry: a hybrid packet forwarding algorithm in flying ad hoc networks. In: 2019 IEEE 18th International Symposium on Network Computing and Applications (NCA), pp. 1–8. IEEE (2019)
Salarian, H., Chin, K.-W., Naghdy, F.: An energy-efficient mobile-sink path selection strategy for wireless sensor networks. IEEE Trans. Veh. Technol. 63(5), 2407–2419 (2013)
Shah, R.C., Roy, S., Jain, S., Brunette, W.: mules: modeling and analysis of a three-tier architecture for sparse sensor networks (2003)
Wang, H., Han, G., Zhang, W., Guizani, M., Chan, S.: A probabilistic source location privacy protection scheme in wireless sensor networks. IEEE Trans. Veh. Technol. 68(6), 5917–5927 (2019)
Wang, H., Han, G., Zhou, L., Ansere, J.A., Zhang, W.: A source location privacy protection scheme based on ring-loop routing for the IoT. Comput. Netw. 148, 142–150 (2019)
Xing, G., Wang, T., Xie, Z., Jia, W.: Rendezvous planning in wireless sensor networks with mobile elements. IEEE Trans. Mob. Comput. 7(12), 1430–1443 (2008)
Peng, J., Gao, H., Liu, L., Wu, Y., Xu, X.: FNTAR: a future network topology-aware routing protocol in UAV networks. In: IEEE Wireless Communications and Networking Conference (WCNC) (2020)
Yoon, J., Lee, A.-H., Lee, H.: Rendezvous: opportunistic data delivery to mobile users by UAVs through target trajectory prediction. IEEE Trans. Veh. Technol. 69, 2230–2245 (2019)
Zhu, S., Wang, D., Low, C.B.: Ground target tracking using UAV with input constraints. J. Intell. Robot. Syst. 69(1–4), 417–429 (2013)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Wu, Y., Liu, Y., Liu, L., Wang, F., Fan, L., Zhou, Q. (2021). TFRA: Trajectory-Based Message Ferry Recognition Attack in UAV Network. In: Liu, Z., Wu, F., Das, S.K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2021. Lecture Notes in Computer Science(), vol 12938. Springer, Cham. https://doi.org/10.1007/978-3-030-86130-8_40
Download citation
DOI: https://doi.org/10.1007/978-3-030-86130-8_40
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-86129-2
Online ISBN: 978-3-030-86130-8
eBook Packages: Computer ScienceComputer Science (R0)