Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V

Emerging privacy challenges and approaches in CAV systems

The growth of Internet-connected devices, Internet-enabled services and Internet of Things systems continues at a rapid pace, and their application to transport systems is heralded as game-changing. Numerous developing CAV (Connected and Autonomous Vehicle) functions, such as traffic planning, optimisation, management, safety-critical and cooperative autonomous driving applications, rely on data from various sources. The efficacy of these functions is highly dependent on the dimensionality, amount and accuracy of the data being shared. It holds, in general, that the greater the amount of data available, the greater the efficacy of the function. However, much of this data is privacy-sensitive, including personal, commercial and research data. Location data and its correlation with identity and temporal data can help infer other personal information, such as home/work locations, age, job, behavioural features, habits, social relationships. This work categorises the emerging privacy challenges and solutions for CAV systems and identifies the knowledge gap for future research, which will minimise and mitigate privacy concerns without hampering the efficacy of the functions

Secure and Privacy-Aware Cloud-Assisted Video Reporting Service in 5G Enabled Vehicular Networks

Vehicular networks are one of the main technologies that will be leveraged by the arrival of the future fifth generation (5G) mobile cellular networks. While scalability and latency are the major drawbacks of IEEE 802.11p and 4G LTE enabled vehicular communications, respectively, the 5G technology is a promising solution to empower the real-time services offered by vehicular networks. However, the security and privacy of such services in 5G enabled vehicular networks need to be addressed first. In this paper, we propose a novel system model for a 5G enabled vehicular network that facilitates a reliable, secure and privacy-aware real-time video reporting service. This service is designed for the participating vehicles to instantly report the videos of traffic accidents to guarantee a timely response from official and/or ambulance vehicles toward accidents. While it provides strong security and privacy guarantees for the participating vehicle’s identity and the video contents, the proposed service ensures traceability of misbehaving participants through a cooperation scheme among different authorities. We show the feasibility and the fulfilment of the proposed reporting service in 5G enabled vehicular networks in terms of security, privacy and efficiency

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version

Secure and Privacy-Aware Cloud-Assisted Video Reporting Service in 5G Enabled Vehicular Networks

Vehicular networks are one of the main technologies that will be leveraged by the arrival of the future fifth generation (5G) mobile cellular networks. While scalability and latency are the major drawbacks of IEEE 802.11p and 4G LTE enabled vehicular communications, respectively, the 5G technology is a promising solution to empower the real-time services offered by vehicular networks. However, the security and privacy of such services in 5G enabled vehicular networks need to be addressed first. In this paper, we propose a novel system model for a 5G enabled vehicular network that facilitates a reliable, secure and privacy-aware real-time video reporting service. This service is designed for the participating vehicles to instantly report the videos of traffic accidents to guarantee a timely response from official and/or ambulance vehicles toward accidents. While it provides strong security and privacy guarantees for the participating vehicle’s identity and the video contents, the proposed service ensures traceability of misbehaving participants through a cooperation scheme among different authorities. We show the feasibility and the fulfilment of the proposed reporting service in 5G enabled vehicular networks in terms of security, privacy and efficiency

The IPERMOB System for Effective Real-Time Road Travel Time Measurement and Prediction

Accurate, real-time measurement and estimation of road travel time is considered a central problem in the design of advanced Intelligent Transportation Systems. In particular, whether eective, real-time collection of travel time measurements in a urban area is possible is, to the best of our knowledge, still an open problem. In this paper, we introduce the IPERMOB system for efficient, real-time collection of travel time measurements in urban areas through vehicular networks. We demonstrate that travel time measurements can be accurately estimated onboard GPS-equipped vehicles, and delivered to a centralized server within a few seconds by sending a single message. Furthermore, in IPERMOB locations of travel time checkpoints can be dynamically changed through software reconfiguration, thus at a very limited cost as compared to the enormous costs of, say, installing and/or changing location of automatic vehicle identification equipment. We demonstrate the effectiveness of our approach through extensive travel time collection campaigns. In particular, our technique is shown to estimate travel time with an accuracy below 1%, with two-, three-orders of magnitude savings in both communication and storage resources with respect to existing techniques based on centralized collection of GPS traces. In the last part of the paper, we further show how real-time travel time measurements can be exploited to perform accurate, short range travel time predictions in situations where existing travel time prediction approaches are challenged (e.g., in presence of traffic congestion). The effects of vehicular network penetration rate on accuracy of travel time prediction are also discusse

On Board unit based authentication for V2V communication in VANET

The recent developments in wireless communication technologies along with the plummeting costs of hardware allow both V2V and V2I communications for information exchange. Such a network is called Vehicular ad Hoc Network (VANET) which is very important for various road safety and non-safety related applications. However, Due to the wireless nature of communication in VANETs, it is also prone to various security attacks which are originally present in wireless networks. Hence to realize the highest potential of VANET, the network should be free from attackers, there by all the information exchanged in the network must be reliable i.e. should be originated from authenticated source. However, authentication of vehicles using a PKI based architecture which is mostly based on V2I communication and solely depends on Road side Units, might fail in case of absence of proper infrastructure. Moreover PKI based solutions incur more communication overhead due to repeated connections with the Trusted Authority every time you want to authenticate a vehicle. Hence, this thesis work gives an OBU based authentication mechanism which allows the vehicle to authenticate each other for V2V communication when there is lack of proper infrastructure. Here each vehicle is capable of generating a pair of self-certified public/private key pair which can be verified by any other vehicle using a predefined secret key given by Trusted Authority. The grouping concept used in order to lower the communication overheads. The Vehicle in close proximity of each other form a group. A vehicle can obtain the group key by authenticating itself to the group leader. Our proposed scheme also preserves the privacy of the vehicle but can reveal the identity in liability issues. The security analysis of the proposed scheme shows that it can indeed operate with limited support of infrastructure and can become a fully self-organized system