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LinkDroid: Reducing Unregulated Aggregation of App Usage Behaviors
Huan Feng, Kassem Fawaz, and Kang G. Shin, University of Michigan
Usage behaviors of different smartphone apps capture different views of an individual’s life, and are largely independent of each other. However, in the current mobile app ecosystem, a curious party can covertly link and aggregate usage behaviors of the same user across different apps. We refer to this as unregulated aggregation of app usage behaviors. In this paper, we present a fresh perspective of unregulated aggregation, focusing on monitoring, characterizing and reducing the underlying linkability across apps. The cornerstone of our study is the Dynamic Linkability Graph (DLG) which tracks applevel linkability during runtime. We observed how DLG evolves on real-world users and identified real-world evidence of apps abusing IPCs and OS-level identifying information to establish linkability. Based on these observations, we propose a linkability-aware extension to current mobile operating systems, called LinkDroid,which provides runtime monitoring and mediation of linkability across different apps. LinkDroid is a client-side solution and compatible with the existing smartphone ecosystem. It helps end-users “sense” this emerging threat and provides them intuitive opt-out options.
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