A Survey of Security Threats and Trust Management in Vehicular Ad Hoc Networks

This paper presents a survey of state-of-the-art trust models for Vehicular Ad Hoc Networks (VANETs). Trust management plays an essential role in isolating malicious insider attacks in VANETs which traditional security approaches fail to thwart. To this end, many trust models are presented; some of them only address trust management, while others address security and privacy aspects besides trust management. This paper first reviews, classifies, and summarizes state-of-the-art trust models, and then compares their achievements. From this literature survey, our reader will easily identify two broad classes of trust models that exist in literature, differing primarily in their evaluation point. For example, most trust models follow receiver-side trust evaluation and to the best of our knowledge, there is only one trust model for VANETs which evaluates trust at the sender-side unless a dispute arises. In the presence of a dispute, a Roadside Unit (RSU) rules on the validity of an event. In receiver-side trust models, each receiver becomes busy while computing the trust of a sender and its messages upon the messages' arrival. Conversely, in the sender-side class, receivers are free from any kind of computation as the trust is verified at the time the message is announced. Also, vehicles can quickly act on the information, such as taking a detour to an alternate route, as it supports fast decision-making. We provide a comparison between these two evaluation techniques using a sequence diagram. We then conclude the survey by suggesting future work for sender-side evaluation of trust in VANETs. Additionally, the challenges (real-time constraints and efficiency) are emphasized whilst considering the deployment of a trust model in VANETs.

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Publication Details

Journal
Transactions on Machine Learning and Artificial Intelligence
Published
2025-05-25
DOI
https://doi.org/10.14738/tmlai.1303.18943
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

A Survey of Security Threats and Trust Management in Vehicular Ad Hoc Networks

Transactions on Machine Learning and Artificial Intelligence
Geochemistry and Geologic Mapping
article

A Survey of Security Threats and Trust Management in Vehicular Ad Hoc Networks

article en

Abstract

This paper presents a survey of state-of-the-art trust models for Vehicular Ad Hoc Networks (VANETs). Trust management plays an essential role in isolating malicious insider attacks in VANETs which traditional security approaches fail to thwart. To this end, many trust models are presented; some of them only address trust management, while others address security and privacy aspects besides trust management. This paper first reviews, classifies, and summarizes state-of-the-art trust models, and then compares their achievements. From this literature survey, our reader will easily identify two broad classes of trust models that exist in literature, differing primarily in their evaluation point. For example, most trust models follow receiver-side trust evaluation and to the best of our knowledge, there is only one trust model for VANETs which evaluates trust at the sender-side unless a dispute arises. In the presence of a dispute, a Roadside Unit (RSU) rules on the validity of an event. In receiver-side trust models, each receiver becomes busy while computing the trust of a sender and its messages upon the messages' arrival. Conversely, in the sender-side class, receivers are free from any kind of computation as the trust is verified at the time the message is announced. Also, vehicles can quickly act on the information, such as taking a detour to an alternate route, as it supports fast decision-making. We provide a comparison between these two evaluation techniques using a sequence diagram. We then conclude the survey by suggesting future work for sender-side evaluation of trust in VANETs. Additionally, the challenges (real-time constraints and efficiency) are emphasized whilst considering the deployment of a trust model in VANETs.

Transactions on Machine Learning and Artificial IntelligenceVol. 13(03)
University of Dhaka (BD)
Peace, Justice and strong institutions
Openalex Percentile: Top 36%
Geochemistry and Geologic Mapping
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