Security issues in Internet of Vehicles (IoV): A comprehensive survey

Taslimasa, Hamideh; Dadkhah, Sajjad; Neto, Euclides Carlos Pinto; Xiong, Pulei; Ray, Suprio; Ghorbani, Ali A.

doi:10.1016/j.iot.2023.100809

Cited by 30 publications

(11 citation statements)

References 63 publications

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“…The objective of this algorithm is to classify V2X messages as either benign or malicious based on their content, behavior, and contextual information. Deep learning models, often utilizing neural networks, are capable of processing message content and behavior to learn normal patterns and differentiate them from malicious ones [41]- [44]. This real-time intrusion detection capability is vital for preventing unauthorized access and potential threats.…”

Section: Deep Learning-based Intrusion Detection Algorithm: Intrusion...mentioning

confidence: 99%

Artificial intelligence powered internet of vehicles: securing connected vehicles in 6G

Kumar Raja,

Abas,

Akula

et al. 2024

IJEECS

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<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>The rapid advancements in automotive technology and the emergence of next-generation networks such as 5G and 6G are laying the foundation for the internet of vehicles (IoV), a revolutionary concept to transform transportation systems. The convergence of artificial intelligence (AI) and connected vehicles IoV is driving a paradigm shift in the transportation sector, especially in the dynamic framework of 5G and future 6G networks. This survey paper provides a thorough survey of the evolving AI-based IoV security landscape. We explore key areas of 5G/6G networks, focusing on the complex interplay of machine learning (ML) and deep learning (DL) in enhancing vehicle-to-everything (V2X) security and connected vehicles. Addressing the unique challenges of 6G, this paper outlines future directions for improving security and highlights open research issues. This comprehensive survey, which aims to provide information and guidance to both researchers and practitioners, contributes to a detailed understanding of the security issues associated with connected vehicles in the emerging 6G era.</p></div></div></div>

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Section: Deep Learning-based Intrusion Detection Algorithm: Intrusion...mentioning

confidence: 99%

Artificial intelligence powered internet of vehicles: securing connected vehicles in 6G

Kumar Raja,

Abas,

Akula

et al. 2024

IJEECS

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“…DoS attack poses a significant threat to the IoV environment [9], [10]. These malicious endeavors aim to disrupt normal traffic, overwhelm network resources, and degrade essential service communication, to undermine the IoV's primary objective: seamless and efficient vehicular communication.…”

Section: Dos Attack In Iov Contextsmentioning

confidence: 99%

“…In an IoV topology, a successful DoS attack can have dire consequences, ranging from minor disruptions in traffic communication to catastrophic failures in emergency response communications. The primary purpose of these communications is to enhance road safety, traffic efficiency, and to pave the way for seamless integration of autonomous vehicles in smart city [11].…”

Section: Dos Attack In Iov Contextsmentioning

confidence: 99%

Dissecting Denial of Service (DoS) Syn Flood Attack Dynamics and Impacts in Vehicular Communication Systems

Zamrai,

Mohamad Yusof,

Azizan

2024

ITM Web Conf.

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In the rapidly evolving landscape of vehicular networks, the resilience of vehicular communication systems against Denial of Service (DoS) attacks is critical. Existing research often overlooks the nuanced dynamics of such attacks, particularly in terms of packet size variability and vehicle mobility within Software-Define Internet of Vehicles (SD-IoV) systems. This study addresses this research gap by conducting a detailed analysis of SYN flood DoS attack patterns and their impact on SDN-controlled vehicular networks. This research examines the effects of different packet sizes in SYN packet—1 byte, 200 bytes, 360 bytes, and 1400 bytes—and explore how these packet size variations influence the efficacy of the attacks and the resultant downtime experienced by the victim car. This research findings reveal that SYN flood attacks employing minimal 1-byte packets can cause prolonged unresponsiveness in the victim vehicle, leading to a drastic drop in packet throughput. This research underscores the subtleties of DoS attack strategies and their significant implications on the functionality and safety of IoV environments. The alarming potential of such refined and coordinated DoS attack highlights an urgent need for the development of robust defense mechanisms that can adapt to the sophisticated landscape of vehicular cyber threats.

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“…With the continuous development of Internet of Things (IoT) technology, the Internet of Vehicles (IoV) has received more and more attention. IoV is a concept rooted in IoT technology, aimed at integrating vehicles, roads, drivers, and infrastructure into a unified network for communication and information exchange [4]. Utilizing wireless communication, sensor technology, and data analysis, IoV enables vehicles to communicate with each other, interact with traffic infrastructure, and connect to drivers and cloud-based servers [5].…”

Section: Introductionmentioning

confidence: 99%

“…This review adopts a unique classification of DT's recent IoV applications over the past 3-5 years into four categories according to the application direction, presenting a fresh perspective and comprehensive analysis that offers clear insights and research directions. 4.…”

mentioning

confidence: 99%

Digital Twin-Enabled Internet of Vehicles Applications

Gao,

Peng,

Yoshinaga

et al. 2024

Electronics

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The digital twin (DT) paradigm represents a groundbreaking shift in the Internet of Vehicles (IoV) landscape, acting as an instantaneous digital replica of physical entities. This synthesis not only refines vehicular design but also substantially augments driver support systems and streamlines traffic governance. Diverging from the prevalent research which predominantly examines DT’s technical assimilation within IoV infrastructures, this review focuses on the specific deployments and goals of DT within the IoV sphere. Through an extensive review of scholarly works from the past 5 years, this paper provides a fresh and detailed perspective on the significance of DT in the realm of IoV. The applications are methodically categorized across four pivotal sectors: industrial manufacturing, driver assistance technology, intelligent transportation networks, and resource administration. This classification sheds light on DT’s diverse capabilities to confront and adapt to the intricate challenges in contemporary vehicular networks. The intent of this comprehensive overview is to catalyze innovation within IoV by providing an essential reference for researchers who aspire to swiftly grasp the complex dynamics of this evolving domain.

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Security issues in Internet of Vehicles (IoV): A comprehensive survey

Cited by 30 publications

References 63 publications

Artificial intelligence powered internet of vehicles: securing connected vehicles in 6G

Artificial intelligence powered internet of vehicles: securing connected vehicles in 6G

Dissecting Denial of Service (DoS) Syn Flood Attack Dynamics and Impacts in Vehicular Communication Systems

Digital Twin-Enabled Internet of Vehicles Applications

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