Software Defined Network-Based Multi-Access Edge Framework for Vehicular Networks

The authors are grateful to the Deanship of Scientific Research at King Saud University for funding this work through Vice Deanship of Scientific Research Chairs: Chair of Pervasive and Mobile Computing.Peer reviewe

An Efficient Localization and Avoidance Method of Jammers in Vehicular Ad Hoc Networks

Jamming is a terrifying attack that could harm 802.11p-based vehicular communications by occupying the communication channels by overwhelming the network with jamming packets, especially for self-driving cars, as it is essential to send/receive messages without any interruptions to control the vehicles remotely. In wireless vehicular ad hoc networks (VANET), the attacker’s mission is more accessible due to the network’s open nature, way of communication, and lack of security measures. Most of the existing studies have focused on jamming detection approaches. However, few of them have addressed the jammer localization challenge. Moreover, even in these limited studies, the solutions’ assumptions, the proposed countermeasures, and their complexity were also missing. Therefore, this paper introduces a new approach to detecting, localizing, and avoiding jamming attacks in VANETs with high efficiency in terms of accuracy, implementation and complexity. The proposed approach uses the signal strength of the jammer for estimating only the distance between jammer and receiver, while then a less complex algorithm is proposed for localizing the jammer and then redirecting the vehicles away from the roads the attacker is using. This approach was simulated using real-life maps and specialized network environments. Additionally, the performance of the new approach was evaluated using different metrics. These evaluation metrics include (1) the estimated position of the jammer, (2) the handling of the jammer by announcing its location to normal vehicles (3) the avoidance of the jammed routes by increasing their weight, which forces the cars to reroute and evade the jamming area. The high localization accuracy, measured by the Euclidean distance, and the successful communication of the attacker’s position and its avoidance have highly increased the packet delivery ratio (PDR) and the signal-to-interference-plus-noise ratio (SINR). This was noticed significantly before and after avoiding the jamming area when for example, the PDR increased from 0% to 100% before and after bypassing the jammer’s routes

An Efficient Localization and Avoidance Method of Jammers in Vehicular Ad Hoc Networks

Jamming is a terrifying attack that could harm 802.11p-based vehicular communications by occupying the communication channels by overwhelming the network with jamming packets, especially for self-driving cars, as it is essential to send/receive messages without any interruptions to control the vehicles remotely. In wireless vehicular ad hoc networks (VANET), the attacker’s mission is more accessible due to the network’s open nature, way of communication, and lack of security measures. Most of the existing studies have focused on jamming detection approaches. However, few of them have addressed the jammer localization challenge. Moreover, even in these limited studies, the solutions’ assumptions, the proposed countermeasures, and their complexity were also missing. Therefore, this paper introduces a new approach to detecting, localizing, and avoiding jamming attacks in VANETs with high efficiency in terms of accuracy, implementation and complexity. The proposed approach uses the signal strength of the jammer for estimating only the distance between jammer and receiver, while then a less complex algorithm is proposed for localizing the jammer and then redirecting the vehicles away from the roads the attacker is using. This approach was simulated using real-life maps and specialized network environments. Additionally, the performance of the new approach was evaluated using different metrics. These evaluation metrics include (1) the estimated position of the jammer, (2) the handling of the jammer by announcing its location to normal vehicles (3) the avoidance of the jammed routes by increasing their weight, which forces the cars to reroute and evade the jamming area. The high localization accuracy, measured by the Euclidean distance, and the successful communication of the attacker’s position and its avoidance have highly increased the packet delivery ratio (PDR) and the signal-to-interference-plus-noise ratio (SINR). This was noticed significantly before and after avoiding the jamming area when for example, the PDR increased from 0% to 100% before and after bypassing the jammer’s routes

SGIRP: A Secure and Greedy Intersection-Based Routing Protocol for VANET using Guarding Nodes

Vehicular Ad Hoc Network (VANET) is an advance wireless technology in the field of wireless communication to provide better Intelligent Transportation Services (ITS). It is an emerging area of research in the field of vehicular technology for its high mobility and high link disruption. VANET provides better road services to the end users by providing safety to the passengers and drivers. Multimedia sharing, e-shopping, safety systems, etc. are some of ITS services provided by VANET. VANETs are strongly affected by link disruption problem for their high mobility and randomness. Security is also a main issue in VANET nowadays, which degrades the network performance. In this thesis, we present a Secure and Greedy Intersection-Based Routing Protocol (SGIRP) to transmit the data securely from source (S) to the destination (D) in a shortest path. For this, we have set Guarding Nodes (GNs) at every intersection to relay the packet from one intersection to other in a secure manner. GN helps in calculating the updated shortest paths to D, protects the network from malicious attacks by using authentication scheme and also recovers the network from Communication Voids (CV). GN plays an important role in transmitting the data from S to D in a fast and secure way. At last, we evaluate our proposed SGIRP protocol by deriving and proving the lemmas related to the protocol. It is also proved that SGIRP protocol shows better performance than Gytar protocol in terms of shorter time delay (T)

Radio shadowing in vehicle-to-vehicle communication at urban intersections : a measurement and simulation-based evaluation

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Context Aware Drivers' Behaviour Detection System for VANET

Wireless communications and mobile computing have led to the enhancement of, and improvement in, intelligent transportation systems (ITS) that focus on road safety applications. As a promising technology and a core component of ITS, Vehicle Ad hoc Networks (VANET) have emerged as an application of Mobile Ad hoc Networks (MANET), which use Dedicated Short Range Communication (DSRC) to allow vehicles in close proximity to communicate with one another, or to communicate with roadside equipment. These types of communication open up a wide range of potential safety and non-safety applications, with the aim of providing an intelligent driving environment that will offer road users more pleasant journeys. VANET safety applications are considered to represent a vital step towards improving road safety and enhancing traffic efficiency, as a consequence of their capacity to share information about the road between moving vehicles. This results in decreasing numbers of accidents and increasing the opportunity to save people's lives. Many researchers from different disciplines have focused their research on the development of vehicle safety applications. Designing an accurate and efficient driver behaviour detection system that can detect the abnormal behaviours exhibited by drivers (i.e. drunkenness and fatigue) and alert them may have an impact on the prevention of road accidents. Moreover, using Context-aware systems in vehicles can improve the driving by collecting and analysing contextual information about the driving environment, hence, increasing the awareness of the driver while driving his/her car. In this thesis, we propose a novel driver behaviour detection system in VANET by utilising a context-aware system approach. The system is comprehensive, non-intrusive and is able to detect four styles of driving behaviour: drunkenness, fatigue, reckless and normal behaviour. The behaviour of the driver in this study is considered to be uncertain context and is defined as a dynamic interaction between the driver, the vehicle and the environment; meaning it is affected by many factors and develops over the time. Therefore, we have introduced a novel Dynamic Bayesian Network (DBN) framework to perform reasoning about uncertainty and to deduce the behaviour of drivers by combining information regarding the above mentioned factors. A novel On Board Unit (OBU) architecture for detecting the behaviour of the driver has been introduced. The architecture has been built based on the concept of context-awareness; it is divided into three phases that represent the three main subsystems of context-aware system; sensing, reasoning and acting subsystems. The proposed architecture explains how the system components interact in order to detect abnormal behaviour that is being exhibited by driver; this is done to alert the driver and prevent accidents from occurring. The implementation of the proposed system has been carried out using GeNIe version 2.0 software to construct the DBN model. The DBN model has been evaluated using synthetic data in order to demonstrate the detection accuracy of the proposed model under uncertainty, and the importance of including a large amount of contextual information within the detection process

Real-Time Detection of DoS Attacks in IEEE 802.11p Using Fog Computing for a Secure Intelligent Vehicular Network

The vehicular ad hoc network (VANET) is a method through which Intelligent Transportation Systems (ITS) have become important for the benefit of daily life. Real-time detection of all forms of attacks, including hybrid DoS attacks in IEEE 802.11p, has become an urgent issue for VANET. This is due to sporadic real-time exchange of safety and road emergency message delivery in VANET. Sporadic communication in VANET has the tendency to generate an enormous amount of messages. This leads to overutilization of the road side unit (RSU) or the central processing unit (CPU) for computation. Therefore, efficient storage and intelligent VANET infrastructure architecture (VIA), which includes trustworthiness, are required. Vehicular Cloud and Fog Computing (VFC) play an important role in efficient storage, computation, and communication needs for VANET. This research utilizes VFC integration with hybrid optimization algorithms (OAs), which also possess swarm intelligence, including Cuckoo/CSA Artificial Bee Colony (ABC) and Firefly/Genetic Algorithm (GA), to provide real-time detection of DoS attacks in IEEE 802.11p, using VFC for a secure intelligent vehicular network. Vehicles move ar a certain speed and the data is transmitted at 30 Mbps. Firefly Feed forward back propagation neural network (FFBPNN) is used as a classifier to distinguish between the attacked vehicles and the genuine vehicles. The proposed scheme is compared with Cuckoo/CSA ABC and Firefly GA by considering jitter, throughput, and prediction accuracy.http://dx.doi.org/10.3390/electronics807077

Sustainable Adoption of Connected Vehicles in the Brazilian Landscape: Policies, Technical Specifications and Challenges

This review addresses the intervehicular communication in Connected Vehicles (CV) by emphasizing V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) communications in terms of evolution, current standards, state-of-the-art studies, embedded devices, simulation, trends, challenges, and relevant legislation. This review is based on studies conducted from 2009 to 2019, government reports about the sustainable deployment of these technologies and their adoption in the Brazilian automotive market. Moreover, WAVE (Wireless Access in Vehicular Environment) and DSRC (Dedicated Short-range Communication) standards, the performance analysis of communication parameters and intervehicular available at the market are also described. The current status of ITS (Intelligent Transportation System) development in Brazil was reviewed, as well as the research institutes and governmental actions focused on introducing the concept of connected vehicles into the society. The Brazilian outlook for technological adoption concerning CVs was also discussed. Moreover, challenges related to technical aspects, safety and environmental issues, and the standardization for vehicle communication are also described. Finally, this review highlights the challenges and proposals from available technologies devoted to the roads and vehicular infrastructure communication, their evolution and upcoming trends

A Fuzzy-Based Context-Aware Misbehavior Detecting Scheme for Detecting Rogue Nodes in Vehicular Ad Hoc Network

A vehicular ad hoc network (VANET) is an emerging technology that improves road safety, traffic efficiency, and passenger comfort. VANETs’ applications rely on co-operativeness among vehicles by periodically sharing their context information, such as position speed and acceleration, among others, at a high rate due to high vehicles mobility. However, rogue nodes, which exploit the co-operativeness feature and share false messages, can disrupt the fundamental operations of any potential application and cause the loss of people’s lives and properties. Unfortunately, most of the current solutions cannot effectively detect rogue nodes due to the continuous context change and the inconsideration of dynamic data uncertainty during the identification. Although there are few context-aware solutions proposed for VANET, most of these solutions are data-centric. A vehicle is considered malicious if it shares false or inaccurate messages. Such a rule is fuzzy and not consistently accurate due to the dynamic uncertainty of the vehicular context, which leads to a poor detection rate. To this end, this study proposed a fuzzy-based context-aware detection model to improve the overall detection performance. A fuzzy inference system is constructed to evaluate the vehicles based on their generated information. The output of the proposed fuzzy inference system is used to build a dynamic context reference based on the proposed fuzzy inference system. Vehicles are classified into either honest or rogue nodes based on the deviation of their evaluation scores calculated using the proposed fuzzy inference system from the context reference. Extensive experiments were carried out to evaluate the proposed model. Results show that the proposed model outperforms the state-of-the-art models. It achieves a 7.88% improvement in the overall performance, while a 16.46% improvement is attained for detection rate compared to the state-of-the-art model. The proposed model can be used to evict the rogue nodes, and thus improve the safety and traffic efficiency of crewed or uncrewed vehicles designed for different environments, land, naval, or air

Estudo do IPFS como protocolo de distribuição de conteúdos em redes veiculares

Over the last few years, vehicular ad-hoc networks (VANETs) have been the focus of great progress due to the interest in autonomous vehicles and in distributing content not only between vehicles, but also to the Cloud. Performing a download/upload to/from a vehicle typically requires the existence of a cellular connection, but the costs associated with mobile data transfers in hundreds or thousands of vehicles quickly become prohibitive. A VANET allows the costs to be several orders of magnitude lower - while keeping the same large volumes of data - because it is strongly based in the communication between vehicles (nodes of the network) and the infrastructure. The InterPlanetary File System (IPFS) is a protocol for storing and distributing content, where information is addressed by its content, instead of its location. It was created in 2014 and it seeks to connect all computing devices with the same system of files, comparable to a BitTorrent swarm exchanging Git objects. It has been tested and deployed in wired networks, but never in an environment where nodes have intermittent connectivity, such as a VANET. This work focuses on understanding IPFS, how/if it can be applied to the vehicular network context, and comparing it with other content distribution protocols. In this dissertation, IPFS has been tested in a small and controlled network to understand its working applicability to VANETs. Issues such as neighbor discoverability times and poor hashing performance have been addressed. To compare IPFS with other protocols (such as Veniam’s proprietary solution or BitTorrent) in a relevant way and in a large scale, an emulation platform was created. The tests in this emulator were performed in different times of the day, with a variable number of files and file sizes. Emulated results show that IPFS is on par with Veniam’s custom V2V protocol built specifically for V2V, and greatly outperforms BitTorrent regarding neighbor discoverability and data transfers. An analysis of IPFS’ performance in a real scenario was also conducted, using a subset of STCP’s vehicular network in Oporto, with the support of Veniam. Results from these tests show that IPFS can be used as a content dissemination protocol, showing it is up to the challenge provided by a constantly changing network topology, and achieving throughputs up to 2.8 MB/s, values similar or in some cases even better than Veniam’s proprietary solution.Nos últimos anos, as redes veiculares (VANETs) têm sido o foco de grandes avanços devido ao interesse em veículos autónomos e em distribuir conteúdos, não só entre veículos mas também para a "nuvem" (Cloud). Tipicamente, fazer um download/upload de/para um veículo exige a utilização de uma ligação celular (SIM), mas os custos associados a fazer transferências com dados móveis em centenas ou milhares de veículos rapidamente se tornam proibitivos. Uma VANET permite que estes custos sejam consideravelmente inferiores - mantendo o mesmo volume de dados - pois é fortemente baseada na comunicação entre veículos (nós da rede) e a infraestrutura. O InterPlanetary File System (IPFS - "sistema de ficheiros interplanetário") é um protocolo de armazenamento e distribuição de conteúdos, onde a informação é endereçada pelo conteúdo, em vez da sua localização. Foi criado em 2014 e tem como objetivo ligar todos os dispositivos de computação num só sistema de ficheiros, comparável a um swarm BitTorrent a trocar objetos Git. Já foi testado e usado em redes com fios, mas nunca num ambiente onde os nós têm conetividade intermitente, tal como numa VANET. Este trabalho tem como foco perceber o IPFS, como/se pode ser aplicado ao contexto de rede veicular e compará-lo a outros protocolos de distribuição de conteúdos. Numa primeira fase o IPFS foi testado numa pequena rede controlada, de forma a perceber a sua aplicabilidade às VANETs, e resolver os seus primeiros problemas como os tempos elevados de descoberta de vizinhos e o fraco desempenho de hashing. De modo a poder comparar o IPFS com outros protocolos (tais como a solução proprietária da Veniam ou o BitTorrent) de forma relevante e em grande escala, foi criada uma plataforma de emulação. Os testes neste emulador foram efetuados usando registos de mobilidade e conetividade veicular de alturas diferentes de um dia, com um número variável de ficheiros e tamanhos de ficheiros. Os resultados destes testes mostram que o IPFS está a par do protocolo V2V da Veniam (desenvolvido especificamente para V2V e VANETs), e que o IPFS é significativamente melhor que o BitTorrent no que toca ao tempo de descoberta de vizinhos e transferência de informação. Uma análise do desempenho do IPFS em cenário real também foi efetuada, usando um pequeno conjunto de nós da rede veicular da STCP no Porto, com o apoio da Veniam. Os resultados destes testes demonstram que o IPFS pode ser usado como protocolo de disseminação de conteúdos numa VANET, mostrando-se adequado a uma topologia constantemente sob alteração, e alcançando débitos até 2.8 MB/s, valores parecidos ou nalguns casos superiores aos do protocolo proprietário da Veniam.Mestrado em Engenharia de Computadores e Telemátic