UNION: A Trust Model Distinguishing Intentional and Unintentional Misbehavior in Inter-UAV Communication

[EN] Ensuring the desired level of security is an important issue in all communicating systems, and it becomes more challenging in wireless environments. Flying Ad Hoc Networks (FANETs) are an emerging type of mobile network that is built using energy-restricted devices. Hence, the communications interface used and that computation complexity are additional factors to consider when designing secure protocols for these networks. In the literature, various solutions have been proposed to ensure secure and reliable internode communications, and these FANET nodes are known as Unmanned Aerial Vehicles (UAVs). In general, these UAVs are often detected as malicious due to an unintentional misbehavior related to the physical features of the UAVs, the communication mediums, or the network interface. In this paper, we propose a new context-aware trust-based solution to distinguish between intentional and unintentional UAV misbehavior. The main goal is to minimize the generated error ratio while meeting the desired security levels. Our proposal simultaneously establishes the inter-UAV trust and estimates the current context in terms of UAV energy, mobility pattern, and enqueued packets, in order to ensure full context awareness in the overall honesty evaluation. In addition, based on computed trust and context metrics, we also propose a new inter-UAV packet delivery strategy. Simulations conducted using NS2.35 evidence the efficiency of our proposal, called UNION., at ensuring high detection ratios > 87% and high accuracy with reduced end-to-end delay, clearly outperforming previous proposals known as RPM, T-CLAIDS, and CATrust.This research is partially supported by the United Arab Emirates University (UAEU) under Grant no. 31T065.Barka, E.; Kerrache, CA.; Lagraa, N.; Lakas, A.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J. (2018). UNION: A Trust Model Distinguishing Intentional and Unintentional Misbehavior in Inter-UAV Communication. Journal of Advanced Transportation. 1-12. https://doi.org/10.1155/2018/7475357S112Ghazzai, H., Ben Ghorbel, M., Kadri, A., Hossain, M. J., & Menouar, H. (2017). Energy-Efficient Management of Unmanned Aerial Vehicles for Underlay Cognitive Radio Systems. IEEE Transactions on Green Communications and Networking, 1(4), 434-443. doi:10.1109/tgcn.2017.2750721Sharma, V., & Kumar, R. (2016). Cooperative frameworks and network models for flying ad hoc networks: a survey. Concurrency and Computation: Practice and Experience, 29(4), e3931. doi:10.1002/cpe.3931Sun, J., Wang, W., Kou, L., Lin, Y., Zhang, L., Da, Q., & Chen, L. (2017). A data authentication scheme for UAV ad hoc network communication. The Journal of Supercomputing, 76(6), 4041-4056. doi:10.1007/s11227-017-2179-3He, D., Chan, S., & Guizani, M. (2017). Drone-Assisted Public Safety Networks: The Security Aspect. IEEE Communications Magazine, 55(8), 218-223. doi:10.1109/mcom.2017.1600799cmSeong-Woo Kim, & Seung-Woo Seo. (2012). Cooperative Unmanned Autonomous Vehicle Control for Spatially Secure Group Communications. IEEE Journal on Selected Areas in Communications, 30(5), 870-882. doi:10.1109/jsac.2012.120604Singh, A., Maheshwari, M., Nikhil, & Kumar, N. (2011). Security and Trust Management in MANET. Communications in Computer and Information Science, 384-387. doi:10.1007/978-3-642-20573-6_67Kerrache, C. A., Calafate, C. T., Cano, J.-C., Lagraa, N., & Manzoni, P. (2016). Trust Management for Vehicular Networks: An Adversary-Oriented Overview. IEEE Access, 4, 9293-9307. doi:10.1109/access.2016.2645452Li, W., & Song, H. (2016). ART: An Attack-Resistant Trust Management Scheme for Securing Vehicular Ad Hoc Networks. IEEE Transactions on Intelligent Transportation Systems, 17(4), 960-969. doi:10.1109/tits.2015.2494017Raghunathan, V., Schurgers, C., Sung Park, & Srivastava, M. B. (2002). Energy-aware wireless microsensor networks. IEEE Signal Processing Magazine, 19(2), 40-50. doi:10.1109/79.985679Feeney, L. M. (2001). Mobile Networks and Applications, 6(3), 239-249. doi:10.1023/a:1011474616255De Rango, F., Guerriero, F., & Fazio, P. (2012). Link-Stability and Energy Aware Routing Protocol in Distributed Wireless Networks. IEEE Transactions on Parallel and Distributed Systems, 23(4), 713-726. doi:10.1109/tpds.2010.160Hyytia, E., Lassila, P., & Virtamo, J. (2006). Spatial node distribution of the random waypoint mobility model with applications. IEEE Transactions on Mobile Computing, 5(6), 680-694. doi:10.1109/tmc.2006.86Wang, Y., Chen, I.-R., Cho, J.-H., Swami, A., Lu, Y.-C., Lu, C.-T., & Tsai, J. J. P. (2018). CATrust: Context-Aware Trust Management for Service-Oriented Ad Hoc Networks. IEEE Transactions on Services Computing, 11(6), 908-921. doi:10.1109/tsc.2016.2587259Kumar, N., & Chilamkurti, N. (2014). Collaborative trust aware intelligent intrusion detection in VANETs. Computers & Electrical Engineering, 40(6), 1981-1996. doi:10.1016/j.compeleceng.2014.01.00

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