Evidence theory-based trust management for the Social Internet of Vehicles

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Date
2024-09-09
Authors
Shamaeian, Nasrin
Pesch, Dirk
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Institute of Electrical and Electronics Engineers (IEEE)
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https://doi.org/10.1109/LCN60385.2024.10639654
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Abstract
The Social Internet of Vehicles (SIoV) is a concept combining the principles of vehicular and social networks, where entities, such as vehicles, drivers, passengers and infrastructure, share information not only for intelligent transportation or cooperative mobility needs, but also using social network principles. Trust in the information exchanged between vehicles in a vehicular network is paramount to achieving safety and reliability of transportation. We propose a trust management model for SIoV that integrates entity trust from direct interactions between vehicles, indirect trust from recommendations, and social trust reflecting the drivers’ social attributes. We utilize Dempster–Shafer Theory to effectively manage inherent uncertainties within this network, enabling robust aggregation of various trust evidences. Our simulation results show the effectiveness of our model in accurately identifying and mitigating malicious entities within the network performing trust-related attacks. Published in: 2024 IEEE 49th Conference on Local Computer Networks (LCN)
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Keywords
Trust management , Internet of Vehicles , Social IoV , Dempster-Shafer theory
Citation
Shamaeian, N. and Pesch, D. (2024) 'Evidence theory-based trust management for the Social Internet of Vehicles', 2024 IEEE 49th Conference on Local Computer Networks (LCN), Normandy, France, 8-10 October 2024, pp. 1-7. https://doi.org/10.1109/LCN60385.2024.10639654
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https://hdl.handle.net/10468/16880
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Computer Science - Conference Items
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© 2024, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.