Temporal and cultural limits of privacy in smartphone app usage
(2021) In Scientific Reports 11(1).- Abstract
Large-scale collection of human behavioural data by companies raises serious privacy concerns. We show that behaviour captured in the form of application usage data collected from smartphones is highly unique even in large datasets encompassing millions of individuals. This makes behaviour-based re-identification of users across datasets possible. We study 12 months of data from 3.5 million people from 33 countries and show that although four apps are enough to uniquely re-identify 91.2% of individuals using a simple strategy based on public information, there are considerable seasonal and cultural variations in re-identification rates. We find that people have more unique app-fingerprints during summer months making it easier to... (More)
Large-scale collection of human behavioural data by companies raises serious privacy concerns. We show that behaviour captured in the form of application usage data collected from smartphones is highly unique even in large datasets encompassing millions of individuals. This makes behaviour-based re-identification of users across datasets possible. We study 12 months of data from 3.5 million people from 33 countries and show that although four apps are enough to uniquely re-identify 91.2% of individuals using a simple strategy based on public information, there are considerable seasonal and cultural variations in re-identification rates. We find that people have more unique app-fingerprints during summer months making it easier to re-identify them. Further, we find significant variations in uniqueness across countries, and reveal that American users are the easiest to re-identify, while Finns have the least unique app-fingerprints. We show that differences across countries can largely be explained by two characteristics of the country specific app-ecosystems: the popularity distribution and the size of app-fingerprints. Our work highlights problems with current policies intended to protect user privacy and emphasizes that policies cannot directly be ported between countries. We anticipate this will nuance the discussion around re-identifiability in digital datasets and improve digital privacy.
(Less)
- author
- Sekara, Vedran ; Alessandretti, Laura ; Mones, Enys and Jonsson, Håkan LU
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Scientific Reports
- volume
- 11
- issue
- 1
- article number
- 3861
- publisher
- Nature Publishing Group
- external identifiers
-
- pmid:33594096
- scopus:85100941364
- ISSN
- 2045-2322
- DOI
- 10.1038/s41598-021-82294-1
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
- id
- 28e8c7e5-9e7c-40e1-a358-c662b6546f8b
- date added to LUP
- 2021-03-01 07:47:02
- date last changed
- 2024-09-19 16:59:44
@article{28e8c7e5-9e7c-40e1-a358-c662b6546f8b,
abstract = {{<p>Large-scale collection of human behavioural data by companies raises serious privacy concerns. We show that behaviour captured in the form of application usage data collected from smartphones is highly unique even in large datasets encompassing millions of individuals. This makes behaviour-based re-identification of users across datasets possible. We study 12 months of data from 3.5 million people from 33 countries and show that although four apps are enough to uniquely re-identify 91.2% of individuals using a simple strategy based on public information, there are considerable seasonal and cultural variations in re-identification rates. We find that people have more unique app-fingerprints during summer months making it easier to re-identify them. Further, we find significant variations in uniqueness across countries, and reveal that American users are the easiest to re-identify, while Finns have the least unique app-fingerprints. We show that differences across countries can largely be explained by two characteristics of the country specific app-ecosystems: the popularity distribution and the size of app-fingerprints. Our work highlights problems with current policies intended to protect user privacy and emphasizes that policies cannot directly be ported between countries. We anticipate this will nuance the discussion around re-identifiability in digital datasets and improve digital privacy.</p>}},
author = {{Sekara, Vedran and Alessandretti, Laura and Mones, Enys and Jonsson, Håkan}},
issn = {{2045-2322}},
language = {{eng}},
number = {{1}},
publisher = {{Nature Publishing Group}},
series = {{Scientific Reports}},
title = {{Temporal and cultural limits of privacy in smartphone app usage}},
url = {{http://dx.doi.org/10.1038/s41598-021-82294-1}},
doi = {{10.1038/s41598-021-82294-1}},
volume = {{11}},
year = {{2021}},
}