Data behind mobile behavioural biometrics - a survey
Data behind mobile behavioural biometrics - a survey
Behavioural biometrics are becoming more and more popular. It is hard to ?nd a sensor that is embedded in a mobile/wearable device, which can?t be exploited to extract behavioural biometric data. In this paper, we investigate data in behavioural biometrics and how this data is used in experiments, especially examining papers that introduce new datasets. We will not examine performance accomplished by the algorithms used since a system?s performance is enormously affected by the data used, its amount and quality. Altogether, 32 papers are examined, assessing how often they are cited, have databases published, what modality data are collected, and how the data is used. We offer a roadmap that should be taken into account when designing behavioural data collection and using collected data. We further look at the General Data Protection Regulation, and its signi?cance to the scienti?c research in the ?eld of biometrics. It is possible to conclude that there is a need for publicly available datasets with comprehensive experimental protocols, similarly established in facial recognition.
224-237
Eglitis, Teodors
134ab9e3-45a6-4fcc-98b7-afbacbdd749f
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Deravi, Farzin
15f7c2ec-bd1e-4819-9ca9-7e179385dfa7
31 March 2020
Eglitis, Teodors
134ab9e3-45a6-4fcc-98b7-afbacbdd749f
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Deravi, Farzin
15f7c2ec-bd1e-4819-9ca9-7e179385dfa7
Eglitis, Teodors, Guest, Richard and Deravi, Farzin
(2020)
Data behind mobile behavioural biometrics - a survey.
IET Biometrics, 9 (6), .
(doi:10.1049/iet-bmt.2018.5174).
Abstract
Behavioural biometrics are becoming more and more popular. It is hard to ?nd a sensor that is embedded in a mobile/wearable device, which can?t be exploited to extract behavioural biometric data. In this paper, we investigate data in behavioural biometrics and how this data is used in experiments, especially examining papers that introduce new datasets. We will not examine performance accomplished by the algorithms used since a system?s performance is enormously affected by the data used, its amount and quality. Altogether, 32 papers are examined, assessing how often they are cited, have databases published, what modality data are collected, and how the data is used. We offer a roadmap that should be taken into account when designing behavioural data collection and using collected data. We further look at the General Data Protection Regulation, and its signi?cance to the scienti?c research in the ?eld of biometrics. It is possible to conclude that there is a need for publicly available datasets with comprehensive experimental protocols, similarly established in facial recognition.
Text
IET Biometrics - 2020 - Eglitis - Data behind mobile behavioural biometrics a survey
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Accepted/In Press date: 25 February 2020
Published date: 31 March 2020
Identifiers
Local EPrints ID: 489470
URI: http://eprints.soton.ac.uk/id/eprint/489470
ISSN: 2047-4938
PURE UUID: 4a66130e-bc27-4fc0-a1b6-a8bad72b0e6f
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Date deposited: 25 Apr 2024 16:30
Last modified: 28 Apr 2024 02:05
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Author:
Teodors Eglitis
Author:
Richard Guest
Author:
Farzin Deravi
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