Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps

It is the basic right of a user to know how the permissions are used within the Android app’s scope and to refuse the app if granted permissions are used for the activities other than specified use which can amount to malicious behavior. This paper proposes an approach and a vision to automatically...

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Main Authors: MALVIYA, Vikas Kumar, LEOW, Chee Wei, ASHOK KASTHURI, YAN, Naing Tun, SHAR, Lwin Khin, JIANG, Lingxiao
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Language:English
Published: Institutional Knowledge at Singapore Management University 2022
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Online Access:https://ink.library.smu.edu.sg/sis_research/7777
https://ink.library.smu.edu.sg/context/sis_research/article/8780/viewcontent/ase22nier.pdf
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spelling sg-smu-ink.sis_research-87802023-04-04T03:24:23Z Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps MALVIYA, Vikas Kumar LEOW, Chee Wei ASHOK KASTHURI, YAN, Naing Tun SHAR, Lwin Khin JIANG, Lingxiao It is the basic right of a user to know how the permissions are used within the Android app’s scope and to refuse the app if granted permissions are used for the activities other than specified use which can amount to malicious behavior. This paper proposes an approach and a vision to automatically model the permissions necessary for Android apps from users’ perspective and enable fine-grained permission controls by users, thus facilitating users in making more well-informed and flexible permission decisions for different app functionalities, which in turn improve the security and data privacy of the App and enforce apps to reduce permission misuses. Our proposed approach works in mainly two stages. First, it looks for discrepancies between the permission uses perceivable by users and the permissions actually used by apps via program analysis techniques. Second, it runs prediction algorithms using machine learning techniques to catch the discrepancies in permission usage and thereby alert the user for action about data violation. We have evaluated preliminary implementations of our approach and achieved promising fine-grained permission control accuracy. In addition to the benefits of users’ privacy protection, we envision that wider adoption of the approach may also enforce better privacy-aware design by responsible bodies such as app developers, governments, and enterprises. 2022-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7777 info:doi/10.1145/3551349.3559556 https://ink.library.smu.edu.sg/context/sis_research/article/8780/viewcontent/ase22nier.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University automated permission control UI perception Android application analysis Android permissions machine learning Information Security Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic automated permission control
UI perception
Android application analysis
Android permissions
machine learning
Information Security
Software Engineering
spellingShingle automated permission control
UI perception
Android application analysis
Android permissions
machine learning
Information Security
Software Engineering
MALVIYA, Vikas Kumar
LEOW, Chee Wei
ASHOK KASTHURI,
YAN, Naing Tun
SHAR, Lwin Khin
JIANG, Lingxiao
Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps
description It is the basic right of a user to know how the permissions are used within the Android app’s scope and to refuse the app if granted permissions are used for the activities other than specified use which can amount to malicious behavior. This paper proposes an approach and a vision to automatically model the permissions necessary for Android apps from users’ perspective and enable fine-grained permission controls by users, thus facilitating users in making more well-informed and flexible permission decisions for different app functionalities, which in turn improve the security and data privacy of the App and enforce apps to reduce permission misuses. Our proposed approach works in mainly two stages. First, it looks for discrepancies between the permission uses perceivable by users and the permissions actually used by apps via program analysis techniques. Second, it runs prediction algorithms using machine learning techniques to catch the discrepancies in permission usage and thereby alert the user for action about data violation. We have evaluated preliminary implementations of our approach and achieved promising fine-grained permission control accuracy. In addition to the benefits of users’ privacy protection, we envision that wider adoption of the approach may also enforce better privacy-aware design by responsible bodies such as app developers, governments, and enterprises.
format text
author MALVIYA, Vikas Kumar
LEOW, Chee Wei
ASHOK KASTHURI,
YAN, Naing Tun
SHAR, Lwin Khin
JIANG, Lingxiao
author_facet MALVIYA, Vikas Kumar
LEOW, Chee Wei
ASHOK KASTHURI,
YAN, Naing Tun
SHAR, Lwin Khin
JIANG, Lingxiao
author_sort MALVIYA, Vikas Kumar
title Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps
title_short Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps
title_full Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps
title_fullStr Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps
title_full_unstemmed Right to know, right to refuse: Towards UI perception-based automated fine-grained permission controls for Android apps
title_sort right to know, right to refuse: towards ui perception-based automated fine-grained permission controls for android apps
publisher Institutional Knowledge at Singapore Management University
publishDate 2022
url https://ink.library.smu.edu.sg/sis_research/7777
https://ink.library.smu.edu.sg/context/sis_research/article/8780/viewcontent/ase22nier.pdf
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