App-generated digital identities extracted through Android permission-based data access - a survey of app privacy
Zusammenfassung
Smartphone apps that run on Android devices can access many types of personal information. Such information can be used to identify, profile and track the device users when mapped into digital identity attributes. This article presents a model of identifiability through access to personal data protected by the Android access control mechanism called permissions. We present an abstraction of partial identity attributes related to such personal data, and then show how apps accumulate such attributes in a longitudinal study that was carried out over several months. We found that apps' successive access to permissions accumulates such identity attributes, where different apps show different interest in such attributes.
- Vollständige Referenz
- BibTeX
Momen, N. & Fritsch, L.,
(2020).
App-generated digital identities extracted through Android permission-based data access - a survey of app privacy.
In:
Reinhardt, D., Langweg, H., Witt, B. C. & Fischer, M.
(Hrsg.),
SICHERHEIT 2020.
Bonn:
Gesellschaft für Informatik e.V..
(S. 15-28).
DOI: 10.18420/sicherheit2020_01
@inproceedings{mci/Momen2020,
author = {Momen, Nurul AND Fritsch, Lothar},
title = {App-generated digital identities extracted through Android permission-based data access - a survey of app privacy},
booktitle = {SICHERHEIT 2020},
year = {2020},
editor = {Reinhardt, Delphine AND Langweg, Hanno AND Witt, Bernhard C. AND Fischer, Mathias} ,
pages = { 15-28 } ,
doi = { 10.18420/sicherheit2020_01 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
author = {Momen, Nurul AND Fritsch, Lothar},
title = {App-generated digital identities extracted through Android permission-based data access - a survey of app privacy},
booktitle = {SICHERHEIT 2020},
year = {2020},
editor = {Reinhardt, Delphine AND Langweg, Hanno AND Witt, Bernhard C. AND Fischer, Mathias} ,
pages = { 15-28 } ,
doi = { 10.18420/sicherheit2020_01 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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Mehr Information
ISBN: 978-3-88579-695-4
ISSN: 1617-5468
Datum: 2020
Sprache:
(en)
(en)
Typ: Text/Conference Paper

