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

Fuzzy Logic Based DSR Trust Estimation Routing Protocol for MANET Using Evolutionary Algorithms

In MANET attaining consistent routing is a main problem due to several reasons such as lack of static infrastructure, exposed transmission medium, energetic network topology and restricted battery power. These features also create the scheme of direction-finding protocols in MANETs become even more interesting. In this work, a Trust centered routing protocol is suggested, since trust plays a vital role in computing path in mobile ad hoc networks (MANETs). Estimating and computing trust encourages cooperation in mobile ad hoc networks (MANETs). Various present grade systems suddenly estimate the trust by considering any one of the parameters such as energy of node, number of hops and mobility. Estimating trust is an Energetic multi objective optimization problem (EMOPs) typically including many contradictory goals such as lifetime of node, lifetime of link and buffer occupancy proportion which change over time. To solve this multi objective problem, a hybrid Harmony Search Combined with Genetic algorithm and Cuckoo search is used along with reactive method Dynamic Source routing protocol to provide the mobile hosts to find out and sustain routes between the origin node (SN) to the target node (TN). In this work, the performance of the direction-finding practice is assessed using throughput, end to end delay, and load on the network and route detection period

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 Impregnable Lightweight Device Discovery (ILDD) Model for the Pervasive Computing Environment of Enterprise Applications

The worldwide use of handheld devices (personal digital assistants, cell phones, etc.) with wireless connectivity will reach 2.6 billion units this year and 4 billion by 2010. More specifically, these handheld devices have become an integral part of industrial applications. These devices form pervasive ad hoc wireless networks that aide in industry applications. However, pervasive computing is susceptible and vulnerable to malicious active and passive snoopers. This is due to the unavoidable interdevice dependency, as well as a common shared medium, very transitory connectivity, and the absence of a fixed trust infrastructure. In order to ensure security and privacy in the pervasive environment, we need a mechanism to maintain a list of valid devices that will help to prevent malicious devices from participating in any task. In this paper, we will show the feasibility of using a modified human- computer authentication protocol in order to prevent the malicious attacks of ad hoc networks in industrial applications. We will also present two separate models for both large and small networks, as well as several possible attack scenarios for each network

Policy-Based Immunization Framework for MANET

Mobility is one of the most important driving forces of hyper-interconnected world that we are living in. Mobile computing devices are becoming smaller, more ubiquitous and simultaneously providing more computing power. Various mobile devices in diff rent sizes with high computing power cause the emergence of new type of networks\u27 applications. Researchers in conferences, soldiers in battlefields, medics in rescue missions, and drivers in busy high- ways can perform more efficiently if they can be connected to each other and aware of the environment they are interacting with. In all mentioned scenarios, the major barrier to have an interconnected collaborative environment is the lack of infrastructure. Mobile Ad hoc Networks (MANETs) are very promising to be able to handle this challenge. In recent years, extensive research has been done on MANETs in order to deliver secure and reliable network services in an infrastructure-less environment. MANETs usually deal with dynamic network topologies and utilize wireless technologies, they are very susceptible to different security attacks targeting different network layers. Combining policy-based management concepts and trust evaluation techniques in more granular level than current trust management frameworks can lead to interesting results toward more secure and reliable MANETs

A trust supportive framework for pervasive computing systems

Recent years have witnessed the emergence and rapid growth of pervasive comput- ing technologies such as mobile ad hoc networks, radio frequency identification (RFID), Wi-Fi etc. Many researches are proposed to provide services while hiding the comput- ing systems into the background environment. Trust is of critical importance to protect service integrity & availability as well as user privacies. In our research, we design a trust- supportive framework for heterogeneous pervasive devices to collaborate with high security confidence while vanishing the details to the background. We design the overall system ar- chitecture and investigate its components and their relations, then we jump into details of the critical components such as authentication and/or identification and trust management. With our trust-supportive framework, the pervasive computing system can have low-cost, privacy-friendly and secure environment for its vast amount of services

Internet of things: where to be is to trust

[EN] Networks' creation is getting more and more required, anytime, anywhere. Devices that can participate on these networks can be quite different among them. Sensors, mobiles, home appliances, or other type of devices will have to collaborate to increase and improve the services provided to clients. In the same way, network configuration, security mechanisms establishment, and optimal performance control must be done by them. Some of these devices could have limited resources to work, sometimes even resources restriction not existing, they must work to optimize network traffic. In this article, we center our researching on spontaneous networks. We propose a secure spontaneous ad-hoc network, based on direct peer-to-peer interaction and communities' creation to grant a quick, easy, and secure access to users to surf the Web. Each device will have an identity in the network. Each community will also have an identity and will act as a unity on a world based on Internet connection. Security will be established in the moment they access to the network through the use of the trust chain generated by nodes. Trust is modified by each node on the basis of nodes behaviorLacuesta, R.; Palacios-Navarro, G.; Cetina Englada, C.; Peñalver Herrero, ML.; Lloret, J. (2012). Internet of things: where to be is to trust. EURASIP Journal on Wireless Communications and Networking. (203):1-16. doi:10.1186/1687-1499-2012-203S116203Lipnack J, Stamps J: Virtual Teams: Researching Across Space, Time, and Organizations with Technology. New York: John Wiley and Sons; 1997.Ahuja MK, Carley KN: Network structure in virtual organizations, organization science, Vol. 10, No. 6, Special Issue: Communication Processes for Virtual Organizations, November–December. 1999, 741-757.Mowshowitz A: Virtual organization. Commun ACM 1997, 40(9):30-37. 10.1145/260750.260759Preuß S: CH Cap, Overview of spontaneous networking-evolving concepts and technologies, in Rostocker Informatik-Berichte. 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Adaptive Cross-Layer Multipath Routing Protocol for Mobile Ad Hoc Networks

[EN] Mobile ad hoc networks (MANETs) are generally created for temporary scenarios. In such scenarios, where nodes are in mobility, efficient routing is a challenging task. In this paper, we propose an adaptive and cross-layer multipath routing protocol for such changing scenarios. Our routing mechanisms operate keeping in view the type of applications. For simple applications, the proposed protocol is inspired from traditional on-demand routing protocols by searching shortest routes from source to destination using default parameters. In case of multimedia applications, the proposed mechanism considers such routes which are capable of providing more data rates having less packet loss ratio. For those applications which need security, the proposed mechanism searches such routes which are more secure in nature as compared to others. Cross-layer methodology is used in proposed routing scheme so as to exchange different parameters across the protocol stack for better decision-making at network layer. Our approach is efficient and fault tolerant in a variety of scenarios that we simulated and tested.The authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for funding this research group no. 037-1435-RG.Iqbal, Z.; Khan, S.; Mehmood, A.; Lloret, J.; Alrajeh, NA. (2016). Adaptive Cross-Layer Multipath Routing Protocol for Mobile Ad Hoc Networks. Journal of Sensors. 2016:1-18. https://doi.org/10.1155/2016/5486437S1182016Abusalah, L., Khokhar, A., & Guizani, M. (2008). A survey of secure mobile Ad Hoc routing protocols. IEEE Communications Surveys & Tutorials, 10(4), 78-93. doi:10.1109/surv.2008.080407Murthy, S., & Garcia-Luna-Aceves, J. J. (1996). An efficient routing protocol for wireless networks. Mobile Networks and Applications, 1(2), 183-197. doi:10.1007/bf01193336Toh, C.-K. (1997). Wireless Personal Communications, 4(2), 103-139. doi:10.1023/a:1008812928561Pearlman, M. R., & Haas, Z. J. (1999). Determining the optimal configuration for the zone routing protocol. IEEE Journal on Selected Areas in Communications, 17(8), 1395-1414. doi:10.1109/49.779922ZHEN, Y., WU, M., WU, D., ZHANG, Q., & XU, C. (2010). Toward path reliability by using adaptive multi-path routing mechanism for multimedia service in mobile Ad-hoc network. The Journal of China Universities of Posts and Telecommunications, 17(1), 93-100. doi:10.1016/s1005-8885(09)60431-3Sivakumar, R., Sinha, P., & Bharghavan, V. (1999). CEDAR: a core-extraction distributed ad hoc routing algorithm. IEEE Journal on Selected Areas in Communications, 17(8), 1454-1465. doi:10.1109/49.779926Zapata, M. G. (2002). Secure ad hoc on-demand distance vector routing. ACM SIGMOBILE Mobile Computing and Communications Review, 6(3), 106-107. doi:10.1145/581291.581312Khan, S., & Loo, J. (2010). Cross Layer Secure and Resource-Aware On-Demand Routing Protocol for Hybrid Wireless Mesh Networks. Wireless Personal Communications, 62(1), 201-214. doi:10.1007/s11277-010-0048-ySharma, V., & Alam, B. (2012). Unicaste Routing Protocols in Mobile Ad Hoc Networks: A Survey. International Journal of Computer Applications, 51(14), 9-18. doi:10.5120/8108-1714Tarique, M., Tepe, K. E., Adibi, S., & Erfani, S. (2009). Survey of multipath routing protocols for mobile ad hoc networks. Journal of Network and Computer Applications, 32(6), 1125-1143. doi:10.1016/j.jnca.2009.07.002Shiwen Mao, Shunan Lin, Yao Wang, Panwar, S. S., & Yihan Li. (2005). Multipath video transport over ad hoc networks. IEEE Wireless Communications, 12(4), 42-49. doi:10.1109/mwc.2005.1497857Li, Z., Chen, Q., Zhu, G., Choi, Y., & Sekiya, H. (2015). A Low Latency, Energy Efficient MAC Protocol for Wireless Sensor Networks. International Journal of Distributed Sensor Networks, 11(8), 946587. doi:10.1155/2015/946587Zheng, Z., Liu, A., Cai, L. X., Chen, Z., & Shen, X. (2016). Energy and memory efficient clone detection in wireless sensor networks. IEEE Transactions on Mobile Computing, 15(5), 1130-1143. doi:10.1109/tmc.2015.2449847Dong, M., Ota, K., Liu, A., & Guo, M. (2016). Joint Optimization of Lifetime and Transport Delay under Reliability Constraint Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 27(1), 225-236. doi:10.1109/tpds.2015.2388482Hamrioui, S., Lorenz, P., Lloret, J., & Lalam, M. (2013). A Cross Layer Solution for Better Interactions Between Routing and Transport Protocols in MANET. Journal of Computing and Information Technology, 21(3), 137. doi:10.2498/cit.1002136Sanchez-Iborra, R., & Cano, M.-D. (2014). An approach to a cross layer-based QoE improvement for MANET routing protocols. Network Protocols and Algorithms, 6(3), 18. doi:10.5296/npa.v6i3.5827Cho, J.-H., Swami, A., & Chen, I.-R. (2011). A Survey on Trust Management for Mobile Ad Hoc Networks. IEEE Communications Surveys & Tutorials, 13(4), 562-583. doi:10.1109/surv.2011.092110.0008

Spontaneous ad hoc mobile cloud computing network

Cloud computing helps users and companies to share computing resources instead of having local servers or personal devices to handle the applications. Smart devices are becoming one of the main information processing devices. Their computing features are reaching levels that let them create a mobile cloud computing network. But sometimes they are not able to create it and collaborate actively in the cloud because it is difficult for them to build easily a spontaneous network and configure its parameters. For this reason, in this paper, we are going to present the design and deployment of a spontaneous ad hoc mobile cloud computing network. In order to perform it, we have developed a trusted algorithm that is able to manage the activity of the nodes when they join and leave the network. The paper shows the network procedures and classes that have been designed. Our simulation results using Castalia show that our proposal presents a good efficiency and network performance even by using high number of nodes.Lacuesta, R.; Lloret, J.; Sendra, S.; Peñalver Herrero, ML. (2014). Spontaneous ad hoc mobile cloud computing network. Scientific World Journal. 2014:1-19. doi:10.1155/2014/232419S1192014Rodrigues, J. J. P. C., Zhou, L., Mendes, L. D. P., Lin, K., & Lloret, J. (2012). Distributed media-aware flow scheduling in cloud computing environment. Computer Communications, 35(15), 1819-1827. doi:10.1016/j.comcom.2012.03.004Feeney, L. M., Ahlgren, B., & Westerlund, A. (2001). Spontaneous networking: an application oriented approach to ad hoc networking. IEEE Communications Magazine, 39(6), 176-181. doi:10.1109/35.925687Fernando, N., Loke, S. W., & Rahayu, W. (2013). Mobile cloud computing: A survey. Future Generation Computer Systems, 29(1), 84-106. doi:10.1016/j.future.2012.05.023Lacuesta, R., Lloret, J., Garcia, M., & Peñalver, L. (2013). A Secure Protocol for Spontaneous Wireless Ad Hoc Networks Creation. IEEE Transactions on Parallel and Distributed Systems, 24(4), 629-641. doi:10.1109/tpds.2012.168Lacuesta, R., Lloret, J., Garcia, M., & Peñalver, L. (2011). Two secure and energy-saving spontaneous ad-hoc protocol for wireless mesh client networks. Journal of Network and Computer Applications, 34(2), 492-505. doi:10.1016/j.jnca.2010.03.024Lacuesta, R., Lloret, J., Garcia, M., & Peñalver, L. (2010). A Spontaneous Ad Hoc Network to Share WWW Access. EURASIP Journal on Wireless Communications and Networking, 2010(1). doi:10.1155/2010/232083Lacuesta, R., Palacios-Navarro, G., Cetina, C., Peñalver, L., & Lloret, J. (2012). Internet of things: where to be is to trust. EURASIP Journal on Wireless Communications and Networking, 2012(1). doi:10.1186/1687-1499-2012-203Capkun, S., Buttyan, L., & Hubaux, J. (2003). Self-organized public-key management for mobile ad hoc networks. IEEE Transactions on Mobile Computing, 2(1), 52-64. doi:10.1109/tmc.2003.1195151Goodman, J., & Chandrakasan, A. (2000). An Energy Efficient Reconfigurable Public-Key Cryptography Processor Architecture. Lecture Notes in Computer Science, 175-190. doi:10.1007/3-540-44499-8_13Mayrhofer, R., Ortner, F., Ferscha, A., & Hechinger, M. (2003). Securing Passive Objects in Mobile Ad-Hoc Peer-to-Peer Networks. Electronic Notes in Theoretical Computer Science, 85(3), 105-121. doi:10.1016/s1571-0661(04)80687-xMendes, L. D. P., Rodrigues, J. J. P. C., Lloret, J., & Sendra, S. (2014). Cross-Layer Dynamic Admission Control for Cloud-Based Multimedia Sensor Networks. IEEE Systems Journal, 8(1), 235-246. doi:10.1109/jsyst.2013.2260653Dutta, R., & B, A. (2014). Protection of data in unsecured public cloud environment with open, vulnerable networks using threshold-based secret sharing. Network Protocols and Algorithms, 6(1), 58. doi:10.5296/npa.v6i1.486