research-article

Permission vs. App Limiters: Profiling Smartphone Users to Understand Differing Strategies for Mobile Privacy Management

Authors:

Ashwaq Alsoubai,

Reza Ghaiumy Anaraky,

Bart Knijnenburg,

Pamela J. WisniewskiAuthors Info & Claims

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Article No.: 406, Pages 1 - 18

https://doi.org/10.1145/3491102.3517652

Published: 29 April 2022 Publication History

Abstract

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.

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https://dl.acm.org/doi/10.5555/3696899.3696923
Slade CBenzo RWashington P(2024)Design Guidelines for Improving Mobile Sensing Data Collection: Prospective Mixed Methods StudyJournal of Medical Internet Research10.2196/5569426(e55694)Online publication date: 18-Nov-2024
https://doi.org/10.2196/55694
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Index Terms

Permission vs. App Limiters: Profiling Smartphone Users to Understand Differing Strategies for Mobile Privacy Management
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Embedded systems
2. Networks
  1. Network properties
    1. Network reliability

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cover image ACM Conferences

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

April 2022

10459 pages

ISBN:9781450391573

DOI:10.1145/3491102

Editors:
Simone Barbosa
PUC-Rio, Brazil
,
Cliff Lampe
University of Michigan, USA
,
Caroline Appert
Université Paris-Saclay, France
,
David A. Shamma
Toyota Research Institute, USA
,
Steven Drucker
Microsoft Research, USA
,
Julie Williamson
University of Glasgow, UK
,
Koji Yatani
University of Tokyo, Japan

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Published: 29 April 2022

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https://dl.acm.org/doi/10.5555/3696899.3696923
Slade CBenzo RWashington P(2024)Design Guidelines for Improving Mobile Sensing Data Collection: Prospective Mixed Methods StudyJournal of Medical Internet Research10.2196/5569426(e55694)Online publication date: 18-Nov-2024
https://doi.org/10.2196/55694
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