Article
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Preserved in Portico This version is not peer-reviewed
Blockchain-Assisted Reputation Management Scheme for Internet of Vehicles
Version 1
: Received: 15 April 2023 / Approved: 17 April 2023 / Online: 17 April 2023 (10:40:19 CEST)
A peer-reviewed article of this Preprint also exists.
Liu, Q.; Gong, J.; Liu, Q. Blockchain-Assisted Reputation Management Scheme for Internet of Vehicles. Sensors 2023, 23, 4624. Liu, Q.; Gong, J.; Liu, Q. Blockchain-Assisted Reputation Management Scheme for Internet of Vehicles. Sensors 2023, 23, 4624.
Abstract
With the rapid development of Internet of Vehicles (IoV), particularly the introduction of mobile edge computing (MEC), vehicles can efficiently share data with one another. However, edge computing nodes are vulnerable to various network attacks, posing security risks to data storage and sharing. Moreover, the presence of abnormal vehicles during the sharing process poses significant security threats to the entire network. To address these issues, this paper proposes a novel reputation management scheme, which proposes an improved multi-source multi-weight subjective logic algorithm. This algorithm fuses direct and indirect opinion feedback of nodes through the subjective logic trust model while considering factors such as event validity, familiarity, timeliness, and trajectory similarity. Vehicle reputation values are periodically updated, and abnormal vehicles are identified through reputation thresholds. Finally, blockchain technology is employed to ensure the security of data storage and sharing. By analyzing real vehicle trajectory datasets, the algorithm is proven to effectively improve the differentiation and detection rate of abnormal vehicles.
Keywords
IoV; MEC; Data Sharing; Reputation Management; Subjective Logic Trust Model; Blockchain
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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