Design a Cloud Security Model in VANET Communication: Design and Architecture

During the last few years, Intelligent Transportation System (ITS) has been progressed at a rapid rate, which aimed to improve the transportation activities in the terms of the safety and efficiency. According to many issues with the traditional Vehicular Ad-Hoc Networks (VANET), some efforts are made to merge the VANET with the cloud technology. This work proposes the VANET based on the cloud (V2Cloud), and designs a security model framework that is hosted on the cloud to manage the security services, and provide a secure VANET communication between the different entities eg vehicles, authorities and etc. This security model framework is called VANET Security as a Service (VSaaS). Our works will presented in a set of two papers. In this first one, it presents VSaaS design and architecture in order to show that the VSaaS fulfills the VANET's security requirements, and protects the VANET against the different types of attacks. The second paper will present the progress towards the implementation and the security analysis of the proposed architecture, along with the results of the performance of the security overhead for the secure Vehicle Information Messages (VIMs), which are sent by vehicles to the cloud as a coarse-grained information

A content dissemination framework for vehicular networking

Vehicular Networks are a peculiar class of wireless mobile networks in which vehicles are equipped with radio interfaces and are, therefore, able to communicate with fixed infrastructure (if available) or other vehicles. Content dissemination has a potential number of applications in vehicular networking, including advertising, traffic warnings, parking notifications and emergency announcements. This thesis addresses two possible dissemination strategies: i) Push-based that is aiming to proactively deliver information to a group of vehicles based on their interests and the level of matching content, and ii) Pull-based that is allowing vehicles to explicitly request custom information. Our dissemination framework is taking into consideration very specific information only available in vehicular networks: the geographical data produced by the navigation system. With its aid, a vehicle's mobility patterns become predictable. This information is exploited to efficiently deliver the content where it is needed. Furthermore, we use the navigation system to automatically filter information which might be relevant to the vehicles. Our framework has been designed and implemented in .NET C# and Microsoft MapPoint. It was tested using a small number of vehicles in the area of Cambridge, UK. Moreover, to prove the correctness of our protocols, we further evaluated it in a large-scale network simulation over a number of realistic vehicular trace-based scenarios. Finally, we built a test-case application aiming to prove that vehicles can gain from such a framework. In this application every vehicle collects and disseminates road traffic information. Vehicles that receive this information can individually evaluate the traffic conditions and take an alternative route, if needed. To evaluate this approach, we collaborated with UCLA's Network Research Lab (NRL), to build a simulator that combines network and dynamic mobility emulation simultaneously. When our dissemination framework is used, the drivers can considerably reduce their trip-times