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

Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs

Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data collected from CAVs across the whole city operational area. This paper develops a Fog Computing-based infrastructure for future Intelligent Transportation Systems (ITSs) enabling an agile and reliable off-load of CAV data. Since CAVs are expected to generate large quantities of data, it is not feasible to assume data off-loading to be completed while a CAV is in the proximity of a single Road-Side Unit (RSU). CAVs are expected to be in the range of an RSU only for a limited amount of time, necessitating data reconciliation across different RSUs, if traditional approaches to data off-load were to be used. To this end, this paper proposes an agile Fog Computing infrastructure, which interconnects all the RSUs so that the data reconciliation is solved efficiently as a by-product of deploying the Random Linear Network Coding (RLNC) technique. Our numerical results confirm the feasibility of our solution and show its effectiveness when operated in a large-scale urban testbed.Comment: To appear in IEEE VTC-Spring 201

Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times