A survey on internet of vehicles: Applications, security issues &amp; solutions

Sharma, Surbhi; Kaushik, Baijnath

doi:10.1016/j.vehcom.2019.100182

Cited by 223 publications

(178 citation statements)

References 97 publications

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“…Recently, connected and automated vehicles are becoming an increasingly important topic in IoV to improve transportation mechanisms. Along with the various benefits of IoV technology, the development of these automated intelligent devices has led to various security issues, especially when sharing/transferring data and making real-time decisions [12], [13]. With the exploit of intelligent devices, the applications may be compromised by the attackers to inject a huge amount of information into the network to make the network resource unavailable for others.…”

Section: A Research Objective and Motivationmentioning

confidence: 99%

Trusted Orchestration for Smart Decision-Making in Internet of Vehicles

et al. 2020

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Decision-making is of critical significance in Internet-of-Vehicles (IoV), where vehicles need to quickly make decisions in real-time when sharing or transferring the information. In addition, it is necessary to identify the significant factors of an entity while measuring its legitimacy or to record the real-time data generated by it. Traditional automated schemes in IoV are confronted by the issues related to real-time processing and the manner they respond, such as traffic congestion information, fastest route selection, and road accidental information. The exchange of accurate information among vehicles is critical, but the decision-making for IoV has still not been fully investigated in the literature. Further, the involvement of malicious devices in the network may disgrace the network performance by consuming network resources. In this paper, we propose a hybrid decision-making scheme in vehicular informatics for data transferring and processing through VIKOR and analytic hierarchy process (AHP) methods. The proposed model is scrutinized and verified rigorously through several sensing and decision-making metrics against a conventional solution. The simulation results depict that the proposed model leads to 93 percent competence in terms of decision-making, identification of legitimate sensors, and data alteration process when sharing the information through various sensors in IoV.

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Section: A Research Objective and Motivationmentioning

confidence: 99%

Trusted Orchestration for Smart Decision-Making in Internet of Vehicles

et al. 2020

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“…Nevertheless, with the emergence of IoV, the desired commercial interests have begun to emerge. VANETs can thus be considered as a subset of IoV [9], offering more expansive coverage and application as such IoV is capable of providing services to a much larger area, such as a city or even a country. In comparison to VANETs, IoV treats a vehicle as a smart-entity equipped with various sensors and computational capability.…”

Section: Introductionmentioning

confidence: 99%

Evolution of VANETS to IoV

Lone

Verma

Sharma

2021

Teh. glas. (Online)

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Advancement in wireless communication technology along with the evolution of low power computational devices, have given rise to the Internet of things paradigm. This paradigm is transforming conventional VANETs into Internet-of- vehicles. This transition has led to a substantial commercial interest; as a result, there has been a significant boost in the field of the Internet of vehicles during the past few years. IoV promises a wide range of applications of commercial interest as well as public entertainment and convenience (collision warning systems, on-demand in-car entertainment, smart parking, traffic information). Applications related to vehicular and passenger safety are particularly of great commercial as well as a research interest as such IoV is going to be a core component in implementing the smart city concept. This paper gives an overview of the transition of conventional VANETs to IoV and highlights the potential applications and challenges faced by the Internet of Vehicles (IoV) paradigm.

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“…Various models in assisting this technology were proposed and implemented. This ranges from the level of network aspects such as vehicular ad hoc network VANET routing [1], clustering [2], reliability analysis [3], congestion solutions [4], internet of vehicles [5], etc., to the level of the road protocols for both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications [4]. Also, with the assistance of technology of long term evolution LTE [6] and handover [7], it became important to develop mature VANET models to solve various issues of networks performance in terms of quality of service QoS [8], throughput, stability [2] [9], scalability [10], security [11] [12], robustness,….etc.…”

Section: Introductionmentioning

confidence: 99%

A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning and Extended Mobility Features for VANETs

Talib

Hassan

Alamery³

et al. 2020

IEEE Access

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VANETs clustering is an emerging research topic that serves in the intelligent transportation systems of today's technology. It aims at segmenting the moving vehicles in the road environment into subgroups named clusters, with cluster heads for enabling effective and stable routing. Most of the VANETs clustering approaches are based on distributed models which make the decision of clusters creation lacking the global view of the vehicle's distribution and mobility in the environment. However, the availability of the LTE and long ranges of base station motivated researchers recently to provide center-based approaches. Unlike existing center-based clustering approaches of VANETs, this article uses the road segmenting phase named grid partitioning before providing summarized information to the clustering center. Furthermore, it presents an integrated approach as a combination of all the clustering tasks including assigning, cluster head selection, removing, and merging. Evaluation of the proposed approach named center-based evolving clustering based on grid partitioning (CEC-GP) is proven superior from the perspective of efficiency, stability, and consistency. An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively. INDEX TERMS vehicular ad hoc networks, VANETs clustering, Center-based clustering, evolving clustering, grid based-clustering.

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A survey on internet of vehicles: Applications, security issues & solutions

Cited by 223 publications

References 97 publications

Trusted Orchestration for Smart Decision-Making in Internet of Vehicles

Trusted Orchestration for Smart Decision-Making in Internet of Vehicles

Evolution of VANETS to IoV

A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning and Extended Mobility Features for VANETs

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