A survey of privacy vulnerabilities of mobile device sensors
A survey of privacy vulnerabilities of mobile device sensors
The number of mobile devices, such as smartphones and smartwatches, is relentlessly increasing, to almost 6.8 billion by 2022, and along with it, the amount of personal and sensitive data captured by them. This survey overviews the state of the art of what personal and sensitive user attributes can be extracted from mobile device sensors, emphasizing critical aspects such as demographics, health and body features, activity and behavior recognition, and so forth. In addition, we review popular metrics in the literature to quantify the degree of privacy and discuss powerful privacy methods to protect the sensitive data while preserving data utility for analysis. Finally, open research questions are presented for further advancements in the field.
Delgado-Santos, Paula
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Stragapede, Giuseppe
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Tolosana, Ruben
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Guest, Richard
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Deravi, Farzin
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Vera-Rodriguez, Ruben
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9 September 2022
Delgado-Santos, Paula
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Stragapede, Giuseppe
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Tolosana, Ruben
93125127-5ac2-4e76-94aa-4d09f28a3e51
Guest, Richard
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Deravi, Farzin
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Vera-Rodriguez, Ruben
d9c7e17e-332c-47ac-a9a9-30cc75d26a3e
Delgado-Santos, Paula, Stragapede, Giuseppe, Tolosana, Ruben, Guest, Richard, Deravi, Farzin and Vera-Rodriguez, Ruben
(2022)
A survey of privacy vulnerabilities of mobile device sensors.
ACM Computing Surveys, 54 (11s), [224].
(doi:10.1145/3510579).
Abstract
The number of mobile devices, such as smartphones and smartwatches, is relentlessly increasing, to almost 6.8 billion by 2022, and along with it, the amount of personal and sensitive data captured by them. This survey overviews the state of the art of what personal and sensitive user attributes can be extracted from mobile device sensors, emphasizing critical aspects such as demographics, health and body features, activity and behavior recognition, and so forth. In addition, we review popular metrics in the literature to quantify the degree of privacy and discuss powerful privacy methods to protect the sensitive data while preserving data utility for analysis. Finally, open research questions are presented for further advancements in the field.
Text
3510579
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Published date: 9 September 2022
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Local EPrints ID: 489421
URI: http://eprints.soton.ac.uk/id/eprint/489421
ISSN: 0360-0300
PURE UUID: c6467c2a-cc67-4504-99a7-5fd2acee7c67
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Date deposited: 24 Apr 2024 16:30
Last modified: 25 Apr 2024 02:09
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Contributors
Author:
Paula Delgado-Santos
Author:
Giuseppe Stragapede
Author:
Ruben Tolosana
Author:
Richard Guest
Author:
Farzin Deravi
Author:
Ruben Vera-Rodriguez
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