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

An Investigation into Trust and Reputation Frameworks for Autonomous Underwater Vehicles

As Autonomous Underwater Vehicles (AUVs) become more technically capable and economically feasible, they are being increasingly used in a great many areas of defence, commercial and environmental applications. These applications are tending towards using independent, autonomous, ad-hoc, collaborative behaviour of teams or fleets of these AUV platforms. This convergence of research experiences in the Underwater Acoustic Network (UAN) and Mobile Ad-hoc Network (MANET) fields, along with the increasing Level of Automation (LOA) of such platforms, creates unique challenges to secure the operation and communication of these networks. The question of security and reliability of operation in networked systems has usually been resolved by having a centralised coordinating agent to manage shared secrets and monitor for misbehaviour. However, in the sparse, noisy and constrained communications environment of UANs, the communications overheads and single-point-of-failure risk of this model is challenged (particularly when faced with capable attackers). As such, more lightweight, distributed, experience based systems of “Trust” have been proposed to dynamically model and evaluate the “trustworthiness” of nodes within a MANET across the network to prevent or isolate the impact of malicious, selfish, or faulty misbehaviour. Previously, these models have monitored actions purely within the communications domain. Moreover, the vast majority rely on only one type of observation (metric) to evaluate trust; successful packet forwarding. In these cases, motivated actors may use this limited scope of observation to either perform unfairly without repercussions in other domains/metrics, or to make another, fair, node appear to be operating unfairly. This thesis is primarily concerned with the use of terrestrial-MANET trust frameworks to the UAN space. Considering the massive theoretical and practical difference in the communications environment, these frameworks must be reassessed for suitability to the marine realm. We find that current single-metric Trust Management Frameworks (TMFs) do not perform well in a best-case scaling of the marine network, due to sparse and noisy observation metrics, and while basic multi-metric communications-only frameworks perform better than their single-metric forms, this performance is still not at a reliable level. We propose, demonstrate (through simulation) and integrate the use of physical observational metrics for trust assessment, in tandem with metrics from the communications realm, improving the safety, security, reliability and integrity of autonomous UANs. Three main novelties are demonstrated in this work: Trust evaluation using metrics from the physical domain (movement/distribution/etc.), demonstration of the failings of Communications-based Trust evaluation in sparse, noisy, delayful and non-linear UAN environments, and the deployment of trust assessment across multiple domains, e.g. the physical and communications domains. The latter contribution includes the generation and optimisation of cross-domain metric composition or“synthetic domains” as a performance improvement method

MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A

PROTECT: Proximity-based Trust-advisor using Encounters for Mobile Societies

Many interactions between network users rely on trust, which is becoming particularly important given the security breaches in the Internet today. These problems are further exacerbated by the dynamics in wireless mobile networks. In this paper we address the issue of trust advisory and establishment in mobile networks, with application to ad hoc networks, including DTNs. We utilize encounters in mobile societies in novel ways, noticing that mobility provides opportunities to build proximity, location and similarity based trust. Four new trust advisor filters are introduced - including encounter frequency, duration, behavior vectors and behavior matrices - and evaluated over an extensive set of real-world traces collected from a major university. Two sets of statistical analyses are performed; the first examines the underlying encounter relationships in mobile societies, and the second evaluates DTN routing in mobile peer-to-peer networks using trust and selfishness models. We find that for the analyzed trace, trust filters are stable in terms of growth with time (3 filters have close to 90% overlap of users over a period of 9 weeks) and the results produced by different filters are noticeably different. In our analysis for trust and selfishness model, our trust filters largely undo the effect of selfishness on the unreachability in a network. Thus improving the connectivity in a network with selfish nodes. We hope that our initial promising results open the door for further research on proximity-based trust

MobileTrust: Secure Knowledge Integration in VANETs

Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy