@inproceedings {pub5705,
	title = {A Graph-based Model for Vehicle-centric Data-sharing Ecosystem},
	author = {Haiyue Yuan AND Ali Raza AND Nikolay Matyunin AND Jibesh Patra AND Shujun Li},
	year = {2024},
	month = {September},
	abstract = {The development of technologies has prompted a paradigm shift in the automotive industry, with an increasing focus on connected services and autonomous driving capabilities. This transformation allows vehicles to be able to collect and share vast amounts of vehicle-specific and personal data. While these technological advancements offer enhanced user experiences, they also raise privacy concerns. To understand the ecosystem of data collection and sharing in modern vehicles, we adopted the ontology 101 methodology to incorporate information extracted from different sources, including privacy policies analysis using GPT-4, a systematic literature review, and an existing ontology, to develop a high-level conceptual graph-based model, aiming to get insights into how modern vehicles handle data exchange among different parties. This serves as a foundational model that has the flexibility and scalability to further expand for modelling and analysing data-sharing practices across diverse transportation contexts. Two realistic examples were developed to demonstrate its potential applications in informing and improving users{\textquoteright} privacy awareness. We also recommended several future research directions such as exploring advanced ontology languages for reasoning tasks, supporting topological analysis for discovering data privacy risks/concerns, developing useful tools for interactive and comparative analysis, etc., to further enhance the understanding of the vehicle-centric data-sharing ecosystem.},
	publisher = {IEEE},
	booktitle = {27th IEEE International Conference on Intelligent Transportation Systems},
	city = {Edmonton}
}