Biblio

Vehicular ad hoc networks (VANETs) have been growing rapidly because it can improve traffic safety and efficiency in transportation. In VANETs, messages are broadcast in wireless environment, which is vulnerable to be attacked in many ways. Accordingly, it is essential to authenticate the legitimation of vehicles to guarantee the performance of services. In this paper, we propose an anonymous conditional privacy-preserving authentication scheme based on message authentication code (MAC) for VANETs. With verifiable secret sharing (VSS), vehicles can obtain a group key for message generation and authentication after a mutual authentication phase. Security analysis and performance evaluation show that the proposed scheme satisfies basic security and privacy-preserving requirements and has a better performance compared with some existing schemes in terms of computational cost and communication overhead.

Cooperative Intelligent Transport Systems (C-ITS) are expected to play an important role in our lives. They will improve the traffic safety and bring about a revolution on the driving experience. However, these benefits are counterbalanced by possible attacks that threaten not only the vehicle's security, but also passengers' lives. One of the most common attacks is the Sybil attack, which is even more dangerous than others because it could be the starting point of many other attacks in C-ITS. This paper proposes a distributed approach allowing the detection of Sybil attacks by using the traffic flow theory. The key idea here is that each vehicle will monitor its neighbourhood in order to detect an eventual Sybil attack. This is achieved by a comparison between the real accurate speed of the vehicle and the one estimated using the V2V communications with vehicles in the vicinity. The estimated speed is derived by using the traffic flow fundamental diagram of the road's portion where the vehicles are moving. This detection algorithm is validated through some extensive simulations conducted using the well-known NS3 network simulator with SUMO traffic simulator.

In the near future, vehicular cloud will help to improve traffic safety and efficiency. Unfortunately, a computing of vehicular cloud and fog cloud faced a set of challenges in security, authentication, privacy, confidentiality and detection of misbehaving vehicles. In addition to, there is a need to recognize false messages from received messages in VANETs during moving on the road. In this work, the security issues and challenges for computing in the vehicular cloud over for computing is studied.

This study examines the effectiveness of virtual reality technology at creating an immersive user experience in which participants experience first hand the extreme negative consequences of smartphone use while driving. Research suggests that distracted driving caused by smartphones is related to smartphone addiction and causes fatalities. Twenty-two individuals participated in the virtual reality user experience (VRUE) in which they were asked to drive a virtual car using a Oculus Rift headset, LeapMotion hand tracking device, and a force feedback steering wheel and pedals. While driving in the simulation participants were asked to interact with a smartphone and after a period of time trying to manage both tasks a vehicle appears before them and they are involved in a head-on collision. Initial results indicated a strong sense of presence was felt by participants and a change or re-enforcement of the participant's perception of the dangers of smartphone use while driving was observed.