Privacy as part of the app decision-making process
Abstract
Smartphones have unprecedented access to sensitive personal information. While users report having privacy concerns, they may not actively consider privacy while downloading apps from smartphone application marketplaces. Currently, Android users have only the Android permissions display, which appears after they have selected an app to download, to help them understand how applications access their information. We investigate how permissions and privacy could play a more active role in app-selection decisions. We designed a short "Privacy Facts' display, which we tested in a 20-participant lab study and a 366-participant online experiment. We found that by bringing privacy information to the user when they were making the decision and by presenting it in a clearer fashion, we could assist users in choosing applications that request fewer permissions.
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Users consider factors such as cost, functionality, design, ratings, reviews, and downloads as more important than requested permissions.
“This is in line with the findings of Kelley et al. (2013) who found in their study on app decision-making process that users consider factors such as cost, functionality, design, ratings, reviews and downloads as more important than requested permissions.”
From Putting the privacy paradox to the test: Online privacy and security behaviors among users with technical knowledge, privacy awareness, and financial resources (2019) · cites this paper as Kelley et al. (2013)
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Self-citation“Desperate Times Call for Desperate Measures”: User Concerns with Mobile Loan Apps in Kenya
Munyendo, C. W., Acar, Y., & Aviv, A. J. (2022) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp46214.2022.9833779 · Cited by 26 · see citing works
PTPDroid: Detecting Violated User Privacy Disclosures to Third-Parties of Android Apps
Tan, Z., & Song, W. (2023) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1109/icse48619.2023.00050 · Cited by 25 · see citing works
FAIR: Fuzzy Alarming Index Rule for Privacy Analysis in Smartphone Apps
Hatamian, M., Serna, J., Rannenberg, K., & Igler, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-64483-7_1 · Cited by 25 · see citing works
Gerber, N., Gerber, P., Drews, H., Kirchner, E., Schlegel, N., Schmidt, T., & Scholz, L. (2018) · Workshop on Socio-Technical Aspects in Security and Trust (STAST) · doi:10.1145/3167996.3167999 · Cited by 25 · see citing works
Understanding the Impact of Information Representation on Willingness to Share Information
Schneegaß, S., Poguntke, R., & Machulla, T. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300753 · Cited by 24 · see citing works
Personality segmentation of users through mining their mobile usage patterns
Razavi, R. (2020) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2020.102470 · Cited by 24 · see citing works
Using Statistical Information to Communicate Android Permission Risks to Users
Kraus, L., Wechsung, I., & Möller, S. (2014) · Workshop on Socio-Technical Aspects in Security and Trust (STAST) · doi:10.1109/stast.2014.15 · Cited by 24 · see citing works
Does Context in Privacy Communication Really Matter? — A Survey on Consumer Concerns and Preferences
Ebert, N., Ackermann, K. A., & Heinrich, P. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376575 · Cited by 24 · see citing works
Akter, M., Alghamdi, L., Kropczynski, J., Lipford, H. R., & Wisniewski, P. J. (2023) · Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544549.3585904 · Cited by 23 · see citing works
ATLAS: Automatically Detecting Discrepancies Between Privacy Policies and Privacy Labels
Jain, A., Rodríguez, D., Álamo, J. M. D., & Sadeh, N. (2023) · IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) · doi:10.1109/eurospw59978.2023.00016 · Cited by 25 · see citing works
Self-citationBreaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?
Ravichander, A., Black, A. W., Norton, T. B., Wilson, S., & Sadeh, N. (2021) · doi:10.18653/v1/2021.acl-long.319 · Cited by 22 · see citing works
Self-citationAbraham, M., McGill, M., & Khamis, M. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642668 · Cited by 21 · see citing works
Privacy policy analysis: A scoping review and research agenda
van der Schyff, K., Prior, S., & Renaud, K. (2024) · Computers & Security · doi:10.1016/j.cose.2024.104065 · Cited by 20 · see citing works
Understanding and Supporting Self-Tracking App Selection
Lee, J. H., Schroeder, J., & Epstein, D. A. (2021) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3494980 · Cited by 20 · see citing works
Shrestha, P. S., Mohamed, M., & Saxena, N. (2016) · ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) · doi:10.1145/2939918.2939924 · Cited by 20 · see citing works
- Authors
- Kelley, P. G., Cranor, L. F., & Sadeh, N.
- Affiliations
- University of New Mexico (US)
- Carnegie Mellon University (US)
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2013-04-27
- Pages
- 3393-3402
- OpenAlex
- W2007784529
- Cited by
- 314
- References
- 17
- Citations by year
- 2026: 12 · 2025: 9 · 2024: 13 · 2023: 27 · 2022: 34 · 2021: 27 · 2020: 23 · 2019: 15 · 2018: 33 · 2017: 33 · 2016: 32 · 2015: 28 · 2014: 22 · 2013: 5 · 2012: 1
- FWCI
- 90.49
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- National Science Foundation
- Carnegie Mellon University
- Army Research Office
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- application permissions, privacy, user decision-making, personal information disclosure
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