Towards distinguishing trust based attacks in an IoV network

Abstract The paradigm of the Internet of Vehicles (IoV) promises significant innovative advancements and is receiving an increased attention of the researchers from both academia and industry. The IoV creates an intelligent network between different road entities and their corresponding roadside infrastructure via state-of-the-art sensing and communication technologies and, therefore, facilitates in addressing a range of safety-critical and non-safety vehicular applications. Accordingly, the security of an IoV network is of importance with internal attacks being of considerable concern. Although the conventional cryptography-based schemes are extremely intelligent in tackling the external attacks, trust has been recently employed to handle the internal attacks. Nevertheless, trust-based attacks also present a formidable challenge. Therefore, in this paper, an IoV-based trust management heuristic has been envisaged that takes into account both direct trust and indirect trust to ascertain the behaviors of the vehicles vis-à-vis time in a bid to detect various trust-based attacks, i.e., zig-zag attacks, self-promoting attacks, on-off attacks, and opportunistic attacks, along with the attackers’ multiple attacking strategies. The experimental findings further demonstrate that the envisaged IoV-based trust management heuristic exhibits prompt and accurate detection of the trust-based attacks in contrast to the state-of-the-art trust management mechanisms.

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Publication Details

Journal
Journal of King Saud University - Computer and Information Sciences
Published
2025-05-20
DOI
https://doi.org/10.1007/s44443-025-00037-y
Citations
2
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
1.46
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article

Towards distinguishing trust based attacks in an IoV network

Mohamad Faizrizwan Mohd Sabri, Yingxun Wang, Adnan Mahmood, Hushairi Zen
2 citations
Journal of King Saud University - Computer and Information Sciences
Vehicular Ad Hoc Networks (VANETs)
1.46
article

Towards distinguishing trust based attacks in an IoV network

Mohamad Faizrizwan Mohd Sabri, Yingxun Wang, Adnan Mahmood, Hushairi Zen
article en
2 citations

Abstract

Abstract The paradigm of the Internet of Vehicles (IoV) promises significant innovative advancements and is receiving an increased attention of the researchers from both academia and industry. The IoV creates an intelligent network between different road entities and their corresponding roadside infrastructure via state-of-the-art sensing and communication technologies and, therefore, facilitates in addressing a range of safety-critical and non-safety vehicular applications. Accordingly, the security of an IoV network is of importance with internal attacks being of considerable concern. Although the conventional cryptography-based schemes are extremely intelligent in tackling the external attacks, trust has been recently employed to handle the internal attacks. Nevertheless, trust-based attacks also present a formidable challenge. Therefore, in this paper, an IoV-based trust management heuristic has been envisaged that takes into account both direct trust and indirect trust to ascertain the behaviors of the vehicles vis-à-vis time in a bid to detect various trust-based attacks, i.e., zig-zag attacks, self-promoting attacks, on-off attacks, and opportunistic attacks, along with the attackers’ multiple attacking strategies. The experimental findings further demonstrate that the envisaged IoV-based trust management heuristic exhibits prompt and accurate detection of the trust-based attacks in contrast to the state-of-the-art trust management mechanisms.

Journal of King Saud University - Computer and Information SciencesVol. 37(4)
Qilu University of Technology (CN), Universiti Malaysia Sarawak (MY), Swinburne University of Technology Sarawak Campus (MY), Macquarie University (AU)
Openalex Percentile: Top 17%
Vehicular Ad Hoc Networks (VANETs)
1.46
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Towards distinguishing trust based attacks in an IoV network — Mohamad Faizrizwan Mohd Sabri, Yingxun Wang, et al. · Journal of King Saud University - Computer and Information Sciences (2025) | TGRS Research Map | TGRS