NDLI: On the Unicity of Smartphone Applications

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On the Unicity of Smartphone Applications

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On the Unicity of Smartphone Applications

Content Provider	ACM Digital Library
Author	Achara, Jagdish Prasad Castelluccia, Claude Acs, Gergely
Abstract	Prior works have shown that the list of apps installed by a user reveal a lot about user interests and behavior. These works rely on the semantics of the installed apps and show that various user traits could be learnt automatically using off-the-shelf machine-learning techniques. In this work, we focus on the re-identifiability issue and thoroughly study the unicity of smartphone apps on a dataset containing 54,893 Android users collected over a period of 7 months. Our study finds that any 4 apps installed by a user are enough (more than 95% times) for the re-identification of the user in our dataset. As the complete list of installed apps is unique for 99% of the users in our dataset, it can be easily used to track/profile the users by a service such as Twitter that has access to the whole list of installed apps of users. As our analyzed dataset is small as compared to the total population of Android users, we also study how unicity would vary with larger datasets. This work emphasizes the need of better privacy guards against collection, use and release of the list of installed apps.
Starting Page	27
Ending Page	36
Page Count	10
File Format	PDF
ISBN	9781450338202
DOI	10.1145/2808138.2808146
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Privacy Smartphone applications Unicity Uniqueness Re-identifiability User profiling
Content Type	Text
Resource Type	Article

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