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Title: Permission vs. App Limiters: Profiling Smartphone Users to Understand Differing Strategies for Mobile Privacy Management
We conducted a user study with 380 Android users, profiling them according to two key privacy behaviors: the number of apps installed, and the Dangerous permissions granted to those apps. We identified four unique privacy profiles: 1) Privacy Balancers (49.74% of participants), 2) Permission Limiters (28.68%), 3) App Limiters (14.74%), and 4) the Privacy Unconcerned (6.84%). App and Permission Limiters were significantly more concerned about perceived surveillance than Privacy Balancers and the Privacy Unconcerned. App Limiters had the lowest number of apps installed on their devices with the lowest intention of using apps and sharing information with them, compared to Permission Limiters who had the highest number of apps installed and reported higher intention to share information with apps. The four profiles reflect the differing privacy management strategies, perceptions, and intentions of Android users that go beyond the binary decision to share or withhold information via mobile apps.  more » « less
Award ID(s):
1814439
NSF-PAR ID:
10374188
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
The 2022 ACM Conference on Human Factors in Computing Systems
Page Range / eLocation ID:
1 to 18
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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