To protect the privacy of end users from intended or unintended malicious behaviour, the Android operating system provides a permissions-based security model that restricts access to privacy-relevant parts of the platform. Starting with Android 6, the permission system has been revamped, moving to a run-time model. Users are now prompted for confirmation when an app attempts to access a restricted part of the platform. We conducted a large-scale empirical study to investigate how end users perceive the new run-time permission system of Android, collecting and inspecting over 4.3 million user reviews about 5,572 apps published in the Google Play Store. Among them, we identified, classified, and analyzed 3,574 permission-related reviews, employing machine learning and Natural Language Processing techniques. Out of the permission-related reviews, we determined recurring points made by users about the new permission system and classified them into a taxonomy. Results of our analysis suggest that, even with the new system, permission-related issues are widespread, with 8% of collected apps having user reviews with negative comments about permissions. We identify a number of points for improvement in the Android run-time permission system, and provide recommendations for future research.

An investigation into Android run-time permissions from the end users' perspective

SCOCCIA, GIAN LUCA;Malavolta, Ivano;Autili, Marco;Inverardi, Paola
2018-01-01

Abstract

To protect the privacy of end users from intended or unintended malicious behaviour, the Android operating system provides a permissions-based security model that restricts access to privacy-relevant parts of the platform. Starting with Android 6, the permission system has been revamped, moving to a run-time model. Users are now prompted for confirmation when an app attempts to access a restricted part of the platform. We conducted a large-scale empirical study to investigate how end users perceive the new run-time permission system of Android, collecting and inspecting over 4.3 million user reviews about 5,572 apps published in the Google Play Store. Among them, we identified, classified, and analyzed 3,574 permission-related reviews, employing machine learning and Natural Language Processing techniques. Out of the permission-related reviews, we determined recurring points made by users about the new permission system and classified them into a taxonomy. Results of our analysis suggest that, even with the new system, permission-related issues are widespread, with 8% of collected apps having user reviews with negative comments about permissions. We identify a number of points for improvement in the Android run-time permission system, and provide recommendations for future research.
978-1-4503-5712-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/125886
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