Blockchain-Enabled Trust Management in Internet of Vehicles: A Joint Pre-Reward-Penalty and Consensus Approach

The Internet of Vehicles (IoV) is a transformative technology extensively employed in modern intelligent transportation systems. However, managing trust within the IoV presents significant challenges owing to its decentralized architecture, inclusivity, and widespread network. This article proposes a novel trust management scheme for IoV that integrates blockchain technology with a pre-reward-penalty incentive mechanism and trust-based consensus algorithm to address the existing issues of security, scalability, and transparency. The proposed scheme establishes a decentralized trust management system that assesses the reliability of vehicle nodes using a combination of initial trust, local trust, and global trust metrics. Furthermore, it introduces an innovative pre-reward-penalty mechanism that leverages convolutional neural networks (CNNs) to predict message authenticity, thereby promoting truthful participation and information sharing among nodes and enhancing the system’s overall credibility. The trust-based consensus algorithm, supported by the pre-reward-penalty incentive mechanism, ensures data consistency and reliability, thereby improving security and robustness. The experimental results demonstrate significant improvements in security, scalability, and efficiency compared to conventional trust management approaches. These findings offer a pioneering solution for trust management in IoV, with substantial theoretical implications and practical applications.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-11-05
DOI
https://doi.org/10.1109/jiot.2024.3491852
Citations
2
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
1.56

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article

Blockchain-Enabled Trust Management in Internet of Vehicles: A Joint Pre-Reward-Penalty and Consensus Approach

Chen Chen, Lankai Wang, Quan Shi
2 citations
IEEE Internet of Things Journal
Blockchain Technology Applications and Security
1.56
article

Blockchain-Enabled Trust Management in Internet of Vehicles: A Joint Pre-Reward-Penalty and Consensus Approach

Chen Chen, Lankai Wang, Quan Shi
article en
2 citations

Abstract

The Internet of Vehicles (IoV) is a transformative technology extensively employed in modern intelligent transportation systems. However, managing trust within the IoV presents significant challenges owing to its decentralized architecture, inclusivity, and widespread network. This article proposes a novel trust management scheme for IoV that integrates blockchain technology with a pre-reward-penalty incentive mechanism and trust-based consensus algorithm to address the existing issues of security, scalability, and transparency. The proposed scheme establishes a decentralized trust management system that assesses the reliability of vehicle nodes using a combination of initial trust, local trust, and global trust metrics. Furthermore, it introduces an innovative pre-reward-penalty mechanism that leverages convolutional neural networks (CNNs) to predict message authenticity, thereby promoting truthful participation and information sharing among nodes and enhancing the system’s overall credibility. The trust-based consensus algorithm, supported by the pre-reward-penalty incentive mechanism, ensures data consistency and reliability, thereby improving security and robustness. The experimental results demonstrate significant improvements in security, scalability, and efficiency compared to conventional trust management approaches. These findings offer a pioneering solution for trust management in IoV, with substantial theoretical implications and practical applications.

IEEE Internet of Things JournalVol. 12(6)
Nantong University (CN)
National Natural Science Foundation of China
Peace, Justice and strong institutions
Openalex Percentile: Top 12%
Blockchain Technology Applications and Security
1.56
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Blockchain-Enabled Trust Management in Internet of Vehicles: A Joint Pre-Reward-Penalty and Consensus Approach — Chen Chen, Lankai Wang, et al. · IEEE Internet of Things Journal (2024) | TGRS Research Map | TGRS