The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
POSTER: Design Ideas for Privacy-aware User Interfaces for Mobile Devices
Abstract
Privacy in mobile applications is an important topic, especially when it concerns applications that gather and process health data. Using MyFitnessPal as an example eHealth app, we analyze how privacy-aware its user interface is, i.e. how well users are informed about privacy and how much control they have. We find several issues with the current interface and develop five design ideas that make the interface more privacy-aware. In a small pilot user study, we find that most of the design ideas seem to work well and enhance end users' understanding and awareness of privacy.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Examples of the evaluation methods here include studies of privacy in app user interfaces [66] and analysis of publicly available information in relation to the privacy and security of existing apps, such as privacy policies [1] or data handling information [60], [79].”
From Security and Privacy of mHealth Applications: A Scoping Review (2020) · cites this paper as [66]
Citations
Cites
Privacy as part of the app decision-making process
Kelley, P. G., Cranor, L. F., & Sadeh, N. (2013) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2466466 · Cited by 314
Cited by
Sorted by citations
Security and Privacy of mHealth Applications: A Scoping Review
Nurgalieva, L., O'Callaghan, D., & Doherty, G. (2020) · IEEE Access · doi:10.1109/access.2020.2999934 · Cited by 132
“studies of privacy in app user interfaces [66] and analysis of publicly available information in relation to the privacy and security of existing apps, such as privacy policies [1] or data”
Background
Metadata
- Authors
- Tailor, N., He, Y., & Wagner, I.
- Affiliations
- De Montfort University (GB)
- Venue
- Proceedings of the 9th ACM Conference on Security & Privacy in Wireless and Mobile Networks
- Publisher
- ACM
- Published
- 2016-07-18
- Pages
- 219-220
- OpenAlex
- W2472606104
- Cited by
- 2
- References
- 1
- Citations by year
- 2020: 1 · 2018: 1
- FWCI
- 1.06
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) (publishedVersion)
- DMU Open Research Archive (De Montfort University) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- mobile health apps, MyFitnessPal, health data privacy, user privacy awareness, privacy by design, e-health
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
