Within the last two decades recent technological advancements surrounding automobiles have changed the landscape and caused vehicles to become huge repositories and generators of digital information. The generated data has many values within both digital forensics and related research fields. Though the data has value, there are not very many openly available methods for accessing this data. In this paper, a dataset was created which was then used in a machine learning algorithm to help assess the data collected and ascertain certain correlations between specific data points collected in the last year from a fellow classmate’s vehicle. These data points were processed, cleaned and imported into Google Colab where a machine learning algorithm was applied. Results from this work showed that the models we trained found a weak correlation between the speed and weather metrics.

Recommended Citation: Ayers A., Vetter R., Dogan G., Stoker G., (2023). Vehicle Forensics: Applied Machine Learning Using Vehicle Data. UNCW MS CSIS Proceedings. V. 17 , N. 24 .