Cloud-Based Secure Data Management for Internet of Vehicles Platforms
The rapid growth of Internet of Vehicles (IoV) platforms has raised significant concerns about data security and storage efficiency. This study proposes a novel approach that is integrating cloud computing, machine learning, and advanced database management to enhance IoV data security and storage. MongoDB is utilized for data storage. The logistic regression and Support Vector Machine (SVM) algorithms are combined for security detection. By this way, our method demonstrates improved performance over traditional approaches. Experimental results showed a 4.60% increase in data recognition precision, a 4.66% higher recall, and a 2.55% improvement in the F1 score compared to existing models. The proposed system also exhibits enhanced data storage efficiency and robust security detection capabilities. These findings demonstrate our method has significant potential for improving IoV platform security and data management in real-world applications.
Authors
- Yang Xing (ORCID: https://orcid.org/0000-0002-3786-2865)
- Huihui Wang (ORCID: https://orcid.org/0000-0002-9162-2934)
- Ke Xiang
Institutions
- China Telecom (China) (CN)
- Geely (China) (CN)
Publication Details
- Journal
- Tehnicki vjesnik - Technical Gazette
- Published
- 2026-05-01
- DOI
- https://doi.org/10.17559/tv-20240428001508
- Primary Topic
- Vehicular Ad Hoc Networks (VANETs)
- Type
- article
- Field-Weighted Citation Impact
- 0.00