Mobile applications often require access to private user informtion, such as the user or device ID, the location or the contact list. Usage of such data varies across different applications. A notable example is advertising. For contextual advertising, some applications release precise data, such as the user’s exact address, while other applications release only the user’s country. Another dimension is the user. Some users are more privacy demanding than others. Existing solutions for privacy enforcement are neither app- nor user- sensitive, instead performing general tracking of private data into release points like the Internet. The main contribution of this paper is in refining privacy enforcement by letting the user configure privacy preferences through a visual interface that captures the application’s screens enriched with privacy-relevant information. We demonstrate the efficacy of our approach w.r.t. advertising and analytics, which are the main (third-party) consumers of private user information. We have implemented our approach for Android as the VisiDroid system. We demonstrate VisiDroid’s efficacy via both quantitative and qualitative experiments involving top-popular Google Play apps. Our experiments include objective metrics, such as the average number of configuration actions per app, as well as a user study to validate the usability of VisiDroid.

Visual configuration of mobile privacy policies

Ferrara P;
2017

Abstract

Mobile applications often require access to private user informtion, such as the user or device ID, the location or the contact list. Usage of such data varies across different applications. A notable example is advertising. For contextual advertising, some applications release precise data, such as the user’s exact address, while other applications release only the user’s country. Another dimension is the user. Some users are more privacy demanding than others. Existing solutions for privacy enforcement are neither app- nor user- sensitive, instead performing general tracking of private data into release points like the Internet. The main contribution of this paper is in refining privacy enforcement by letting the user configure privacy preferences through a visual interface that captures the application’s screens enriched with privacy-relevant information. We demonstrate the efficacy of our approach w.r.t. advertising and analytics, which are the main (third-party) consumers of private user information. We have implemented our approach for Android as the VisiDroid system. We demonstrate VisiDroid’s efficacy via both quantitative and qualitative experiments involving top-popular Google Play apps. Our experiments include objective metrics, such as the average number of configuration actions per app, as well as a user study to validate the usability of VisiDroid.
FASE 2017: Fundamental Approaches to Software Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10278/3730037
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