Google Research

Wear's my Data? Understanding the Cross-Device Runtime Permission Model in Wearables

  • Doguhan Yeke
  • Muhammad Ibrahim
  • Güliz Seray Tuncay
  • Habiba Farukh
  • Abdullah Imran
  • Antonio Bianchi
  • Z. Berkay Celik
IEEE Security and Privacy (2024) (to appear)

Abstract

Google’s Wear OS is an Android version designed to manage wearable devices. The apps running on these wearable devices often work in conjunction with a "companion" app running on an Android smartphone. Currently, the wearable device and the smartphone use two separate run-time permission models. This situation creates an opaque view of permission-required data management, resulting in over-privileged data access without the user’s explicit consent. To address this issue, we performed the first systematic analysis of the interaction between Android and Wear OS permission models. Our analysis is two-fold. First, we show if and how permission-protected data flows occur between the Wear OS app and the companion app via static taint analysis, quantifying the data flows on 150 real-world wearable apps. Our taint analysis revealed 28 apps with sensitive data flows between the Wear OS app and its companion app. These data flows occur without the users’ explicit consent, thereby introducing the risk of unintended data flows. Second, to uncover users’ understanding of these data flows, we conducted an in-lab user study (n = 63), answering, are users aware of which device can access which data? We found that 66.7% of the users are unaware of the unintended data flows and have a limited understanding of the runtime permission model in general, putting their sensitive data at risk. To mitigate the potential privacy violations in the runtime permission model on cross-device apps, we suggest improvements in system prompts to enable users to make better-informed decisions.

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