Ratee-Based Trust Management System for Internet of Vehicles

Gai, Fangyu; Zhang, Jiexin; Zhu, Peidong; Jiang, Xinwen

doi:10.1007/978-3-319-60033-8_31

Cited by 7 publications

(6 citation statements)

References 14 publications

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“…This is an extension of the paper titled "Ratee-Based Trust Management System for Internet of Vehicles" [1]. Internet of Vehicles (IoV) is a new paradigm brought by the integration of Vehicular Ad hoc NETworks (VANETs) and Internet of Things (IoT) in the last few years [2].…”

Section: Introductionmentioning

confidence: 93%

“…Over the last few decades, there has not been any successful implementation of VANETs. In contrast to VANETs, IoV has two main technology directions [4]: (1) vehicles' networking, which consists of VANETs, Vehicle Telematics, and Mobile Internet; (2) Vehicles' intelligence, which is the integration of drivers and intelligent vehicles by applying technologies such as deep learning, cognitive computing, and artificial intelligence. IoV consists of two types of communications: Vehicle-to-Vehicle (V2V) communication and Vehicle-to-Infrastructure (V2I) communication, which enable tremendous applications ranging from safety to entertainment and commercial services [5].…”

Section: Introductionmentioning

confidence: 99%

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Trust on the Ratee: A Trust Management System for Social Internet of Vehicles

Gai

Zhang

Zhu

et al. 2017

Wireless Communications and Mobile Computing

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The integration of social networking concepts with Internet of Vehicles (IoV) has led to the novel paradigm "Social Internet of Vehicles (SIoV)," which enables vehicles to establish social relationships autonomously to improve traffic conditions and service discovery. There is a growing requirement for effective trust management in the SIoV, considering the critical consequences of acting on misleading information spread by malicious nodes. However, most existing trust models are rater-based, where the reputation information of each node is stored in other nodes it has interacted with. This is not suitable for vehicular environment due to the ephemeral nature of the network. To fill this gap, we propose a Ratee-based Trust Management (RTM) system, where each node stores its own reputation information rated by others during past transactions, and a credible CA server is introduced to ensure the integrality and the undeniability of the trust information. RTM is built based on the concept of SIoV, so that the relationships established between nodes can be used to increase the accuracy of the trustworthiness. Experimental results demonstrate that our scheme achieves faster information propagation and higher transaction success rate than the rater-based method, and the time cost when calculating trustworthiness can meet the demand of vehicular networks.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Trust on the Ratee: A Trust Management System for Social Internet of Vehicles

Gai

Zhang

Zhu

et al. 2017

Wireless Communications and Mobile Computing

Self Cite

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“…In this type of attack, malicious worms or viruses are transferred from one point to another through electronic files. The files can then infect the network instantly or gradually [ 109 ].…”

Section: The Concept Of Iovmentioning

confidence: 99%

Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions

Alalwany,

Mahgoub

2024

Sensors

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The Internet of Vehicles (IoV) is a technology that is connected to the public internet and is a subnetwork of the Internet of Things (IoT) in which vehicles with sensors are connected to a mobile and wireless network. Numerous vehicles, users, things, and networks allow nodes to communicate information with their surroundings via various communication channels. IoV aims to enhance the comfort of driving, improve energy management, secure data transmission, and prevent road accidents. Despite IoV’s advantages, it comes with its own set of challenges, particularly in the highly important aspects of security and trust. Trust management is one of the potential security mechanisms aimed at increasing reliability in IoV environments. Protecting IoV environments from diverse attacks poses significant challenges, prompting researchers to explore various technologies for security solutions and trust evaluation methods. Traditional approaches have been employed, but innovative solutions are imperative. Amid these challenges, machine learning (ML) has emerged as a potent solution, leveraging its remarkable advancements to effectively address IoV’s security and trust concerns. ML can potentially be utilized as a powerful technology to address security and trust issues in IoV environments. In this survey, we delve into an overview of IoV and trust management, discussing security requirements, challenges, and attacks. Additionally, we introduce a classification scheme for ML techniques and survey ML-based security and trust management schemes. This research provides an overview for understanding IoV and the potential of ML in improving its security framework. Additionally, it provides insights into the future of trust and security enhancement.

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“…Cryptography focuses on ciphering data to ensure confidentiality and to prevent unauthorized entities from interpreting the information [101]. This subsection discusses, in detail, the recent research employing the notion of trust along with cryptography [102][103][104][105][106]. Muhlbauer et al [102] proposed a trust management model, wherein the notion of digital certificates and reputation are amalgamated in a centralized vehicular architecture without the necessity of constant connectivity with the road infrastructure.…”

Section: Cryptography-based Trust Modelmentioning

confidence: 99%

“…Gai et al [103] proposed a trust management model, wherein cookies are used by an inquirer to rate, in the range [0, 1], the services provided by another vehicle which are then signed by a certificate authority to keep the vehicle from counterfeiting them. Whenever a vehicle entertains a request by another vehicle, it forwards its cookies along with the service requested which is used by the requester to evaluate the trustworthiness of the service provider.…”

Section: Cryptography-based Trust Modelmentioning

confidence: 99%

A Survey of Trust Management in the Internet of Vehicles

et al. 2021

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Over the past decade, the groundbreaking technological advancements in the Internet of Vehicles (IoV) coupled with the notion of trust have attracted increasing attention from researchers and experts in intelligent transportation systems (ITS), wherein vehicles establish a belief towards their peers in the pursuit of ensuring safe and efficacious traffic flows. Diverse domains have been taking advantage of trust management models in the quest of alleviating diverse insider attacks, wherein messages generated by legitimate users are altered or counterfeited by malicious entities, subsequently, endangering the lives of drivers, passengers, and vulnerable pedestrians. In the course of vehicles forming perceptions towards other participating vehicles, a range of contributing parameters regarding the interactions among these vehicles are accumulated to establish a final opinion towards a target vehicle. The significance of these contributing parameters is typically represented by associating a weighting factor to each contributing attribute. The values assigned to these weighting factors are often set manually, i.e., these values are predefined and do not take into consideration any affecting parameters. Furthermore, a threshold is specified manually that classifies the vehicles into honest and dishonest vehicles relying on the computed trust. Moreover, adversary models as an extension to trust management models in order to tackle the variants of insider attacks are being extensively emphasized in the literature. This paper, therefore, reviews the state of the art in the vehicular trust management focusing on the aforementioned factors such as quantification of weights, quantification of threshold, misbehavior detection, etc. Moreover, an overarching IoV architecture, constituents within the notion of trust, and attacks relating to the IoV have also been presented in addition to open research challenges in the subject domain.

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Ratee-Based Trust Management System for Internet of Vehicles

Cited by 7 publications

References 14 publications

Trust on the Ratee: A Trust Management System for Social Internet of Vehicles

Trust on the Ratee: A Trust Management System for Social Internet of Vehicles

Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions

A Survey of Trust Management in the Internet of Vehicles

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