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TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles

The emerging and promising paradigm of the Internet of Vehicles (IoV) employ vehicle-toeverything communication for facilitating vehicles to not only communicate with one another but also with the supporting roadside infrastructure, vulnerable pedestrians, and the backbone network in a bid to primar...

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Main Authors: Yingxun, Wang, Adnan, Mahmood, Mohamad Faizrizwan, Mohd Sabri, Hushairi, Zen
Format: Article
Language:English
Published: MDPI 2024
Subjects:
QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://ir.unimas.my/id/eprint/47232/1/384614872.pdf
http://ir.unimas.my/id/eprint/47232/
https://www.mdpi.com/2306-5729/9/9/103
https://doi.org/10.3390/data9090103
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spelling my.unimas.ir-472322025-01-03T02:02:04Z http://ir.unimas.my/id/eprint/47232/ TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles Yingxun, Wang Adnan, Mahmood Mohamad Faizrizwan, Mohd Sabri Hushairi, Zen QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering The emerging and promising paradigm of the Internet of Vehicles (IoV) employ vehicle-toeverything communication for facilitating vehicles to not only communicate with one another but also with the supporting roadside infrastructure, vulnerable pedestrians, and the backbone network in a bid to primarily address a number of safety-critical vehicular applications. Nevertheless, owing to the inherent characteristics of IoV networks, in particular, of being (a) highly dynamic in nature and which results in a continual change in the network topology and (b) non-deterministic owing to the intricate nature of its entities and their interrelationships, they are susceptible to a number of malicious attacks. Such kinds of attacks, if and when materialized, jeopardizes the entire IoV network, thereby putting human lives at risk. Whilst the cryptographic-based mechanisms are capable of mitigating the external attacks, the internal attacks are extremely hard to tackle. Trust, therefore, is an indispensable tool since it facilitates in the timely identification and eradication of malicious entities responsible for launching internal attacks in an IoV network. To date, there is no dataset pertinent to trust management in the context of IoV networks and the same has proven to be a bottleneck for conducting an in-depth research in this domain. The manuscript-at-hand, accordingly, presents a first of its kind trust-based IoV dataset encompassing 96,707 interactions amongst 79 vehicles at different time instances. The dataset involves nine salient trust parameters, i.e., packet delivery ratio, similarity, external similarity, internal similarity, familiarity, external familiarity, internal familiarity, reward/punishment, and context, which play a considerable role in ascertaining the trust of a vehicle within an IoV network MDPI 2024-08-31 Article PeerReviewed text en http://ir.unimas.my/id/eprint/47232/1/384614872.pdf Yingxun, Wang and Adnan, Mahmood and Mohamad Faizrizwan, Mohd Sabri and Hushairi, Zen (2024) TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles. Data, 9 (9). pp. 1-10. ISSN 23065729 https://www.mdpi.com/2306-5729/9/9/103 https://doi.org/10.3390/data9090103
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
Yingxun, Wang
Adnan, Mahmood
Mohamad Faizrizwan, Mohd Sabri
Hushairi, Zen
TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles
description The emerging and promising paradigm of the Internet of Vehicles (IoV) employ vehicle-toeverything communication for facilitating vehicles to not only communicate with one another but also with the supporting roadside infrastructure, vulnerable pedestrians, and the backbone network in a bid to primarily address a number of safety-critical vehicular applications. Nevertheless, owing to the inherent characteristics of IoV networks, in particular, of being (a) highly dynamic in nature and which results in a continual change in the network topology and (b) non-deterministic owing to the intricate nature of its entities and their interrelationships, they are susceptible to a number of malicious attacks. Such kinds of attacks, if and when materialized, jeopardizes the entire IoV network, thereby putting human lives at risk. Whilst the cryptographic-based mechanisms are capable of mitigating the external attacks, the internal attacks are extremely hard to tackle. Trust, therefore, is an indispensable tool since it facilitates in the timely identification and eradication of malicious entities responsible for launching internal attacks in an IoV network. To date, there is no dataset pertinent to trust management in the context of IoV networks and the same has proven to be a bottleneck for conducting an in-depth research in this domain. The manuscript-at-hand, accordingly, presents a first of its kind trust-based IoV dataset encompassing 96,707 interactions amongst 79 vehicles at different time instances. The dataset involves nine salient trust parameters, i.e., packet delivery ratio, similarity, external similarity, internal similarity, familiarity, external familiarity, internal familiarity, reward/punishment, and context, which play a considerable role in ascertaining the trust of a vehicle within an IoV network
format Article
author Yingxun, Wang
Adnan, Mahmood
Mohamad Faizrizwan, Mohd Sabri
Hushairi, Zen
author_facet Yingxun, Wang
Adnan, Mahmood
Mohamad Faizrizwan, Mohd Sabri
Hushairi, Zen
author_sort Yingxun, Wang
title TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles
title_short TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles
title_full TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles
title_fullStr TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles
title_full_unstemmed TM–IoV : A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles
title_sort tm–iov : a first-of-its-kind multilabeled trust parameter dataset for evaluating trust in the internet of vehicles
publisher MDPI
publishDate 2024
url http://ir.unimas.my/id/eprint/47232/1/384614872.pdf
http://ir.unimas.my/id/eprint/47232/
https://www.mdpi.com/2306-5729/9/9/103
https://doi.org/10.3390/data9090103
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score 13.244413

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