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Platform for Efficient and Secure Data Collection and Exploitation in Intelligent Vehicular Networks

Platform for Efficient and Secure Data Collection and Exploitation in Intelligent Vehicular Networks

Trending PhD Thesis on Platform for Efficient and Secure Data Collection and Exploitation in Intelligent Vehicular Networks

Research Area:  Vehicular Ad Hoc Networks

Abstract:

    Nowadays, automotive area is witnessing a tremendous evolution due to the increasing growth in communication technologies, environmental sensing & perception aptitudes, and storage & processing capacities that we can find in recent vehicles. Indeed, a car is being a kind of intelligent mobile agent able to perceive its environment, sense and process data using on-board systems and interact with other vehicles or existing infrastructure.
   Several research investigations and projects have been conducted to overcome the aforementioned challenges. However, they still did not meet perfection and suffer from some weaknesses. For this reason, we focus our efforts during this thesis to develop a platform for a secure and efficient data collection and exploitation to provide vehicular network users with efficient applications to ease their travel with protected and available connectivity.
   Therefore, we first propose a solution to deploy an optimized number of data harvesters to collect data from an urban area. Then, we propose a new secure intersection based routing protocol to relay data to a destination in a secure manner based on a monitoring architecture able to detect and evict malicious vehicles. This protocol is after that enhanced with a new intrusion detection and prevention mechanism to decrease the vulnerability window and detect attackers before they persist their attacks using Kalman filter. In a second part of this thesis, we concentrate on the exploitation of collected data by developing an application able to calculate the most economic itinerary in a refined manner for drivers and fleet management companies.

Name of the Researcher:  Tarek Bouali

Name of the Supervisor(s):  Sidi-Mohammed Senouci

Year of Completion:  2016

University:  Bourgogne University

Thesis Link:   Home Page Url