Data leakage prevention model for vehicular networks

The vehicle adhoc network (VANET) is a promising technology that enables numerous vehicular network applications to improve road safety, navigation, and many other purposes. Android automotive supports many applications for vehicles. Each application has a list of accesses, called permissions, required for specific interfaces or sensitive data. However, some applications request permissions unrelated to functionalities or unnecessary permissions. Furthermore, they improperly collect user data. Given the privacy risk associated with applications, it is necessary to study the permissions requested by the application before installation. A permission system is a solution to deal with abusive applications. However, such a system suffers from limitations as users may ignore it during the installation phase due to the complexity of understanding the permissions. This article proposes a graph-based model to determine abusive applications by automatically analyzing the requested permissions. This aims to build a confidence indicator to choose the applications with more respect for privacy. This model would inform the user about the possibility of data leakage risks by assigning a privacy score.