Differentiating smartphone users by app usage

Abstract

Tracking users across websites and apps is as desirable to the marketing industry as it is unalluring to users. The central challenge lies in identifying users from the perspective of different apps/sites. While there are methods to identify users via technical settings of their phones, these are prone to countermeasures. Yet, in this paper, we show that it is possible to differentiate users via their set of used apps, their app signature. To this end, we investigate the app usage of 46726 participants from the Menthal project. Even limiting our observation to the 500 globally most frequent apps results in unique signatures for 99.67% of users. Furthermore, even under this restriction, the average minimum Hamming distance to the closest other user is 25.93. Avoiding identification would thus require a massive change in the behavior of a user. Indeed, 99.4% of all users have unique usage patterns among the top 60 globally used apps. In contrast to previous work, this paper differentiates between users based on behavior instead of technical parameters. It thus opens an entirely new discussion regarding privacy.