• Automotive
• Data Privacy
• Data Security
• Privacy Policy
• VANET

In the last years, our cars have seen a fast evolution with the application of big data, in particular Vehicular-ad-hoc-Networks (VANETs) are the new routes to communicate and to receive information in automotive. These new technologies require a deep study of the privacy and the security of our data that are collected from car companies to perform different services.
In the first part of this work, we performed an analysis of the privacy policy documents of twelve car companies to find, creating a specific taxonomy, which data they declare to collect and to perform a classification of them according also to GDPR categories. In the second part, we defined the main attacks that a VANET can suffer and, following the retrieved data in the first part, it were found the most vulnerable cars and which attacks can be performed on each car. All the information were summarized in a dynamic dashboard for a synthetic and fast reference.
The achieved results suggest the need for more readable privacy policies to make users aware on the collection of their personal data and the need to minimize the type of data that the car can collect to expose the users to less possible attacks. Moreover, it is necessary to study new combined defence strategies to protect information against attacks that use different categories of data to be performed.