Machine Learning based Trust Model for Secure Internet of Vehicle Data Exchange
Abstract
Internet of vehicles (IoV) is an eminent road-side communication assistive technology that is designed to meet the service requirements of the users. As autonomous vehicles are the base for IoV environment, selecting authenticated neighbours is a prime task for improving the security of the communication environment. In this article, classification based trust model (CTM) for IoV is designed for improving the detection and verification of data and vehicles in the dynamic scenario. The classification and verification follows naïve Bayes machine learning model for distinguishing the vehicles as trusted and untrusted. Depending on the communication attributes of the vehicles, classification distribution is modelled for direct trust in both independent and joint manner. The proposed model is assessed using simulation experiments and it is seen that this model achieves fair trusted and untrusted vehicle detection and less verification delay.
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A classification-based trust model (CTM) for IoV using a Naïve Bayes model to indicate vehicles as trusted or untrusted gave a good answer for different kinds of vehicles and the trust factor.
“In [159], the authors proposed a classification-based trust model (CTM) for IoV to improve the security of the communication environment. They used an ML model to indicate the vehicles as trusted or untrusted, which is a Naïve Bayes model. The model gave a good answer for both the different kinds of vehicles and the trust factor.”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [159]
Cites
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- Authors
- Manogaran, G., & Rawal, B. S.
- Affiliations
- Gannon University (US)
- Venue
- 2020 IEEE Globecom Workshops (GC Wkshps
- Publisher
- IEEE
- Published
- 2020-12
- Pages
- 1-6
- OpenAlex
- W3135665540
- Cited by
- 12
- References
- 13
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 2 · 2022: 4 · 2021: 1
- FWCI
- 2.46
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Globecom Workshops (GC Wkshps) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Social Sciences › Sociology and Political Science › Access Control and Trust
- Physical Sciences › Computer Science › Computer Networks and Communications › Security in Wireless Sensor Networks
- Keywords
- Internet of Vehicles, trust model, vehicle authentication, data exchange security, Naive Bayes classifier, autonomous vehicles
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