A privacy threat model for identity verification based on facial recognition
Fecha
2023
Autores
Título de la revista
ISSN de la revista
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Editor
Elsevier
Resumen
The proliferation of different types of photographic and video cameras makes it relatively simple and
non-intrusive to acquire facial fingerprints with sufficient quality to perform individuals’ identity verification. In most democratic societies, a debate has been occurring regarding using such techniques in
different application domains. Discussions usually revolve around the tradeoffs between utility (security
in access control, mobile phone unlocking, payment processing, etc.), usability or economic gain and risks
to citizens’ rights and freedoms (privacy) or ethics. This paper identifies the common aspects of different
solutions for identity verification based on facial recognition techniques within different application domains. It then performs a privacy threat modelling based on these common aspects to identify the most
critical risk factors and a minimum set of safeguards to be considered for their management.
Descripción
This research has been funded by a research contract with the Spanish Data Protection Agency (art.83 M2659). Miguel Calvo is supported by grants from Rey Juan Carlos University (ref. C-PREDOC21-007).
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Citación
Marta Beltrán, Miguel Calvo, A privacy threat model for identity verification based on facial recognition, Computers & Security, Volume 132, 2023, 103324, ISSN 0167-4048, https://doi.org/10.1016/j.cose.2023.103324
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