Turning the Table Around: Monitoring App Behavior

Abstract

Since Android apps receive whitecard access through permissions, users struggle to understand the actual magnitude of app access to their personal data. Due to unavailability of statistical or other tools that would provide an overview of data access or privilege use, users can hardly assess privacy risks or identify app misbehavior. This is a problem for data subjects. The presented PhD research project aims at creating a transparency-enhancing technology that helps users to assess the magnitude of data access of installed apps by monitoring the Android permission access control system. This article will present how apps exercise their permissions, based on a pilot study with an app monitoring tool. It then presents a prototypical implementation of a networked laboratory for crowdsourcing app behavior data. Finally, the article presents and discusses a model that will use the collected data to calculate and visualize risk signals based on individual risk preferences and measured app data access efforts.