Intelligent Intrusion Detection of Grey Hole and Rushing Attacks in Self-Driving Vehicular Networks

Vehicular ad hoc networks (VANETs) play a vital role in the success of self-driving and semi self-driving vehicles, where they improve safety and comfort. Such vehicles depend heavily on external communication with the surrounding environment via data control and Cooperative Awareness Messages (CAMs) exchanges. VANETs are potentially exposed to a number of attacks, such as grey hole, black hole, wormhole and rushing attacks. This work presents an intelligent Intrusion Detection System (IDS) that relies on anomaly detection to protect the external communication system from grey hole and rushing attacks. These attacks aim to disrupt the transmission between vehicles and roadside units. The IDS uses features obtained from a trace file generated in a network simulator and consists of a feed-forward neural network and a support vector machine. Additionally, the paper studies the use of a novel systematic response, employed to protect the vehicle when it encounters malicious behaviour. Our simulations of the proposed detection system show that the proposed schemes possess outstanding detection rates with a reduction in false alarms. This safe mode response system has been evaluated using four performance metrics, namely, received packets, packet delivery ratio, dropped packets and the average end to end delay, under both normal and abnormal conditions

An intelligent security system for autonomous cars based on infrared sensors

Safety and non-safety applications in the external communication systems of self-driving vehicles require authentication of control data, cooperative awareness messages and notification messages. Traditional security systems can prevent attackers from hacking or breaking important system functionality in autonomous vehicles. This paper presents a novel security system designed to protect vehicular ad hoc networks in self-driving and semi-autonomous vehicles that is based on Integrated Circuit Metric technology (ICMetrics). ICMetrics has the ability to secure communication systems in autonomous vehicles using features of the autonomous vehicle system itself. This security system is based on unique extracted features from vehicles behaviour and its sensors. Specifically, features have been extracted from bias values of infrared sensors which are used alongside semantically extracted information from a trace file of a simulated vehicular ad hoc network. The practical experimental implementation and evaluation of this system demonstrates the efficiency in identifying of abnormal/malicious behaviour typical for an attack

An enhanced AODV protocol for external communication in self-driving vehicles

The increasing number of autonomous and semi-autonomous vehicles on the road leads to an increasing need for external vehicle communication, in particular through emerging vehicular ad hoc networks also known as VANETs. This technology has the ability to facilitate intelligent transportation applications, comfort and other required services for self-driving vehicles. However, suitable routing protocols need to be utilised in order to provide stable routing and enable high performance for this external communication in autonomous vehicles. Ad hoc on Demand Distance Vector routing (AODV) is to date rarely used in mobile ad hoc network but offers great potential as a reactive routing protocol. However, the AODV protocol is affected by poor performance, when directly employed in VANETs. In this paper, two improvements are presented to the route selection and route discovery of AODV to improve its performance in forms of packet delivery rate and communication link stability for VANETs. Thus, we obtain new vehicle V-AODV that suits the specific requirements of autonomous vehicles communications. Simulation results demonstrate that V-AODV can enhance the route stability, reduce overhead and improve communication performance between vehicles

An intelligent intrusion detection scheme for self-driving vehicles based on magnetometer sensors

Both safety and non-safety applications require authentication of messages and vehicles in cooperative vehicular ad hoc networks. Access control can prevent external attackers from achieving their goal of breaking or hacking important information from road side units and self-driving vehicles. However, internal attacks on vehicular systems and networks remain possible. A novel intelligent intrusion detection is proposed to secure the external communication system of self-driving and semi-self-driving vehicles. This system is based on the Integrated Circuit Metric technology, which has the ability to protect systems using features of the system itself. The detection system, called the ICMetric-IDS, is based on novel and unique features, which have been generated from bias values of magnetometer sensors as well as features which have been extracted from a trace file of simulated vehicle network traffic. Practical implementation and testing of the system demonstrate the efficiency in the detection of malicious behaviour

BIBLIOMETRIC STUDY ON THE DEVELOPMENT AND IMPLEMENTATION OF CYBERSECURITY IN AUTONOMOUS VEHICLES

The main objective was to examine the trajectory of scientific research in this domain, identify the most influential publications related to cybersecurity in autonomous vehicles and pinpoint research opportunities, supported by the PRISMA method. Additionally, the study explores cybersecurity themes in autonomous vehicles, emphasizing the significance of concepts like blockchain, machine learning, and deep learning essential in formulating business strategies. Furthermore, the research identifies influential scientific publications, predominant journals, the most productive countries, and authors with the most publications on cybersecurity in autonomous vehicles. It identifies research opportunities organized into two distinct clusters to provide a comprehensive understanding of the current state of research in this field and offer insights for companies and academics interested in contributing to future advancements in the cybersecurity of autonomous vehicles. The article demonstrates that cybersecurity is a fundamental area for the development and implementation of secure and reliable autonomous vehicles.info:eu-repo/semantics/publishedVersio

BIBLIOMETRIC STUDY ON THE DEVELOPMENT AND IMPLEMENTATION OF CYBERSECURITY IN AUTONOMOUS VEHICLES

The main objective was to examine the trajectory of scientific research in this domain, identify the most influential publications related to cybersecurity in autonomous vehicles and pinpoint research opportunities, supported by the PRISMA method. Additionally, the study explores cybersecurity themes in autonomous vehicles, emphasizing the significance of concepts like blockchain, machine learning, and deep learning essential in formulating business strategies. Furthermore, the research identifies influential scientific publications, predominant journals, the most productive countries, and authors with the most publications on cybersecurity in autonomous vehicles. It identifies research opportunities organized into two distinct clusters to provide a comprehensive understanding of the current state of research in this field and offer insights for companies and academics interested in contributing to future advancements in the cybersecurity of autonomous vehicles. The article demonstrates that cybersecurity is a fundamental area for the development and implementation of secure and reliable autonomous vehicles.info:eu-repo/semantics/publishedVersio

Security Improvements for Connected Vehicles Position-Based Routing

The constant growing on the number of vehicles is increasing the complexity of traffic in urban and highway environments. It is paramount to improve traffic management to guarantee better road usage and people’s safety. Through efficient communications, Vehicular Ad hoc Networks (VANETs) can provide enough information for traffic safety initiatives, daily traffic data processing, and entertainment information. However, VANETs are vulnerable to malicious nodes applying different types of net-work attacks, where an attacker can, for instance, forge its position to receive the data packet and drop the message. This can lead vehicles and authorities to make incorrect assumptions and decisions, which can result in dangerous situations. Therefore, any data dissemination protocol designed for VANET should consider security issues when selecting the next-hop forwarding node. In this paper, we propose a security scheme designed for position-based routing algorithms, which analyzes nodes position, transmission range, and hello packet interval. The scheme deals with malicious nodes performing network attacks, faking their positions forcing packets to be dropped. We used the Simulation of Urban MObility (SUMO) and Network Simulator-version 3 (NS-3) to compare our proposed scheme integrated with two well-known position-based algorithms. The results were collected in an urban Manhattan grid environment varying the number of nodes, the number of malicious nodes, as well as the number of source-destination pairs. The results show that the proposed security scheme can successfully improve the packet delivery ratio while maintaining low average end-to-end delay of the algorithms.

Mind the Gap: Developments in Autonomous Driving Research and the Sustainability Challenge

Scientific knowledge on autonomous-driving technology is expanding at a faster-than-ever pace. As a result, the likelihood of incurring information overload is particularly notable for researchers, who can struggle to overcome the gap between information processing requirements and information processing capacity. We address this issue by adopting a multi-granulation approach to latent knowledge discovery and synthesis in large-scale research domains. The proposed methodology combines citation-based community detection methods and topic modeling techniques to give a concise but comprehensive overview of how the autonomous vehicle (AV) research field is conceptually structured. Thirteen core thematic areas are extracted and presented by mining the large data-rich environments resulting from 50 years of AV research. The analysis demonstrates that this research field is strongly oriented towards examining the technological developments needed to enable the widespread rollout of AVs, whereas it largely overlooks the wide-ranging sustainability implications of this sociotechnical transition. On account of these findings, we call for a broader engagement of AV researchers with the sustainability concept and we invite them to increase their commitment to conducting systematic investigations into the sustainability of AV deployment. Sustainability research is urgently required to produce an evidence-based understanding of what new sociotechnical arrangements are needed to ensure that the systemic technological change introduced by AV-based transport systems can fulfill societal functions while meeting the urgent need for more sustainable transport solutions