Emerging Technologies for Urban Traffic Management

Nowadays, the number of vehicles on the road and the need of transporting people grow fast. Road transportation has become the backbone of industrialized countries. Nevertheless, the road network system in cities is not sufficient to cope with the current demands due to the size of roads available. Building additional or extending existing roads do not solve the traffic congestion problem due to the high costs and the environmental and geographical limitations. As a consequence, the modern society is facing more traffic jams, higher fuel bills and high levels of CO2 emissions

Security aspects of communications in VANETs

The Fourth Industrial Revolution has begun and it promises breakthroughs in Artificial Intelligence, robotics, Machine Learning, Internet of Things, Digital Twin, and many other technologies that tackle advancements in the industries. The trend is headed towards automation and connectivity. In the automotive industry, advancements have been made towards integrating autonomous driving vehicles into Intelligent Transport Systems (ITS) with the use of Vehicular Ad-Hoc Networks (VANETs). The purpose of this type of network is to enable efficient communication between vehicles (V2V communication) or vehicles and infrastructure (V2I communication), to improve driving safety, to avoid traffic congestion, and to better coordinate transport networks. This direction towards limited (or lack of) human intervention implies vulnerability to cyber attacks. In this context, this paper provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) privacy, 2) authentication and 3) message integrity within VANETs. Discussions, challenges and open issues faced by the current and next generation of vehicular networks are also provided

Security in Vehicles With IoT by Prioritization Rules, Vehicle Certificates, and Trust Management

[EN] The Internet of Vehicles (IoV) provides new opportunities for the coordination of vehicles for enhancing safety and transportation performance. Vehicles can be coordinated for avoiding collisions by communicating their positions when near to each other, in which the information flow is indexed by their geographical positions or the ones in road maps. Vehicles can also be coordinated to ameliorate traffic jams by sharing their locations and destinations. Vehicles can apply optimization algorithms to reduce the overuse of certain streets without excessively enlarging the paths. In this way, traveling time can be reduced. However, IoV also brings security challenges, such as keeping safe from virtual hijacking. In particular, vehicles should detect and isolate the hijacked vehicles ignoring their communications. The current work presents a technique for enhancing security by applying certain prioritization rules, using digital certificates, and applying trust and reputation policies for detecting hijacked vehicles. We tested the proposed approach with a novel agent-based simulator about security in Internet of Things (IoT) for vehicle-to-vehicle communications. The experiments focused on the scenario of avoidance of collisions with hijacked vehicles misinforming other vehicles. The results showed that the current approach increased the average speed of vehicles with a 64.2% when these are giving way to other vehicles in a crossing by means of IoT.This work was supported by Harvard University (stay funded by T49_17R), University of Zaragoza (JIUZ-2017-TEC-03), Foundation Bancaria Ibercaja, Foundation CAI (IT1/18), University Foundation Antonio Gargallo (call 2017), and "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento" (TIN2017-84802-C2-1-P).García-Magariño, I.; Sendra, S.; Lacuesta, R.; Lloret, J. (2019). Security in Vehicles With IoT by Prioritization Rules, Vehicle Certificates, and Trust Management. IEEE Internet of Things. 6(4):5927-5934. https://doi.org/10.1109/JIOT.2018.2871255S592759346

A Secure Mechanism for Big Data Collection in Large Scale Internet of Vehicle

As an extension for Internet of Things (IoT), Internet of Vehicles (IoV) achieves unified management in smart transportation area. With the development of IoV, an increasing number of vehicles are connected to the network. Large scale IoV collects data from different places and various attributes, which conform with heterogeneous nature of big data in size, volume, and dimensionality. Big data collection between vehicle and application platform becomes more and more frequent through various communication technologies, which causes evolving security attack. However, the existing protocols in IoT cannot be directly applied in big data collection in large scale IoV. The dynamic network structure and growing amount of vehicle nodes increases the complexity and necessary of the secure mechanism. In this paper, a secure mechanism for big data collection in large scale IoV is proposed for improved security performance and efficiency. To begin with, vehicles need to register in the big data center to connect into the network. Afterwards, vehicles associate with big data center via mutual authentication and single sign-on algorithm. Two different secure protocols are proposed for business data and confidential data collection. The collected big data is stored securely using distributed storage. The discussion and performance evaluation result shows the security and efficiency of the proposed secure mechanism

Analysis of cyber risk and associated concentration of research (ACR)² in the security of vehicular edge clouds

Intelligent Transportation Systems (ITS) is a rapidly growing research space with many issues and challenges. One of the major concerns is to successfully integrate connected technologies, such as cloud infrastructure and edge cloud, into ITS. Security has been identified as one of the greatest challenges for the ITS, and security measures require consideration from design to implementation. This work focuses on providing an analysis of cyber risk and associated concentration of research (ACR2). The introduction of ACR2 approach can be used to consider research challenges in VEC and open up further investigation into those threats that are important but under-researched. That is, the approach can identify very high or high risk areas that have a low research concentration. In this way, this research can lay the foundations for the development of further work in securing the future of ITS

Design of CSKAS-VANET model for stable clustering and authentication scheme using RBMA and signcryption

A public key infrastructure-enabled system authentication model is developed to provide essential security functions for Vehicular ad hoc networks (VANETs). An intelligent transportation system is provided by VANET, an emerging technology. Dedicated short-range communication is used to disseminate messages wirelessly. Communications may be hacked, and messages can be stolen or fabricated. Hence, authenticated communication is crucial in the VANET environment. Some parameters such as trust, authentication, privacy, and security are at high risk. This article suggests a VANET with secure authentication and trust-based clustering mechanisms to provide stable and secure communication. Initially, the Restricted Boltzmann Machine learning algorithm (RBMA) is used to select the cluster head, which depends upon trust, vehicle lifetime, and buffer level. Then, cluster members are formed, followed by grouping. Diffie–Hellman Hyperelliptic Curve Cryptography and cryptographic hash functions are used by signcryption for secure communication in VANET. Therefore, the essential component of the key agreement strategy that will give superior authentication is this signcryption mechanism. Over the medium access protocol layer, all of these security characteristics are updated. The proposed method of clustering signcryption key agreement scheme (CSKAS) approach reduces time complexity and increases packet delivery ratio which is vital in providing stable, secure communication

Design Models for Trusted Communications in Vehicle-to-Everything (V2X) Networks

Intelligent transportation system is one of the main systems which has been developed to achieve safe traffic and efficient transportation. It enables the road entities to establish connections with other road entities and infrastructure units using Vehicle-to-Everything (V2X) communications. To improve the driving experience, various applications are implemented to allow for road entities to share the information among each other. Then, based on the received information, the road entity can make its own decision regarding road safety and guide the driver. However, when these packets are dropped for any reason, it could lead to inaccurate decisions due to lack of enough information. Therefore, the packets should be sent through a trusted communication. The trusted communication includes a trusted link and trusted road entity. Before sending packets, the road entity should assess the link quality and choose the trusted link to ensure the packet delivery. Also, evaluating the neighboring node behavior is essential to obtain trusted communications because some misbehavior nodes may drop the received packets. As a consequence, two main models are designed to achieve trusted V2X communications. First, a multi-metric Quality of Service (QoS)-balancing relay selection algorithm is proposed to elect the trusted link. Analytic Hierarchy Process (AHP) is applied to evaluate the link based on three metrics, which are channel capacity, link stability and end-to-end delay. Second, a recommendation-based trust model is designed for V2X communication to exclude misbehavior nodes. Based on a comparison between trust-based methods, weighted-sum is chosen in the proposed model. The proposed methods ensure trusted communications by reducing the Packet Dropping Rate (PDR) and increasing the end-to-end delivery packet ratio. In addition, the proposed trust model achieves a very low False Negative Rate (FNR) in comparison with an existing model

A Vehicle Message Scheduling Scheme For Vehicle Trust Management

The trustworthiness of vehicle messages is a major focus in intelligent transportation research. Existing studies focus on enhancing the accuracy of vehicle trustworthiness evaluation, overlooking that the transmission performance may affect the quality of vehicle messages, which are essential for implementing trustworthiness evaluation. This paper studies a novel vehicle message scheduling scheme to regulate vehicles’ transmissions so that incident messages for any part of the road can be reliably and accurately sent to a roadside unit. Through strategically scheduling vehicle transmissions to avoid interference between vehicles while guaranteeing sufficient numbers of vehicles transmitting their sensor data, vehicle messages can reliably yet timely arrive at Road Side Units (RSUs) without missing reporting an event on the road