Toward a non-intrusive, physio-behavioral biometric for smartphones

Esther Vasiete; Vishal Patel; Yan Chen; Larry Davis; Ian Char; Rama Chellappa; Tom Yeh

doi:10.1145/2628363.2634223

Toward a non-intrusive, physio-behavioral biometric for smartphones

Esther Vasiete, Vishal Patel, Yan Chen, Larry Davis, Ian Char, Rama Chellappa, Tom Yeh

Department of Psychology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

Biometric authentication relies on an individual's inner characteristics and traits. We propose an active authentication system on a mobile device that relies on two biometric modalities: 3D gestures and face recognition. The novelty of our approach is to combine 3D gesture and face recognition in a non-intrusive and unconstrained environment; the active authentication system is running in the background while the user is performing his/her main task.

Original language	English
Title of host publication	MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services
Publisher	Association for Computing Machinery
Pages	501-506
Number of pages	6
ISBN (Electronic)	9781450327718
DOIs	https://doi.org/10.1145/2628363.2634223
State	Published - 23 Sep 2014
Event	16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2014 - Toronto, Canada Duration: 23 Sep 2014 → 26 Sep 2014

Publication series

Name	MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services

Conference

Conference	16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2014
Country/Territory	Canada
City	Toronto
Period	23/09/14 → 26/09/14

Keywords

3D gesture recognition
Behavioral biometric authentication
Face recognition
Fusion system

Access to Document

10.1145/2628363.2634223

Cite this

Vasiete, E., Patel, V., Chen, Y., Davis, L., Char, I., Chellappa, R., & Yeh, T. (2014). Toward a non-intrusive, physio-behavioral biometric for smartphones. In MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services (pp. 501-506). (MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services). Association for Computing Machinery. https://doi.org/10.1145/2628363.2634223

Vasiete, Esther ; Patel, Vishal ; Chen, Yan et al. / Toward a non-intrusive, physio-behavioral biometric for smartphones. MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services. Association for Computing Machinery, 2014. pp. 501-506 (MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services).

@inproceedings{bc0cafc072de42c2ba7293e1d23383a7,

title = "Toward a non-intrusive, physio-behavioral biometric for smartphones",

abstract = "Biometric authentication relies on an individual's inner characteristics and traits. We propose an active authentication system on a mobile device that relies on two biometric modalities: 3D gestures and face recognition. The novelty of our approach is to combine 3D gesture and face recognition in a non-intrusive and unconstrained environment; the active authentication system is running in the background while the user is performing his/her main task.",

keywords = "3D gesture recognition, Behavioral biometric authentication, Face recognition, Fusion system",

author = "Esther Vasiete and Vishal Patel and Yan Chen and Larry Davis and Ian Char and Rama Chellappa and Tom Yeh",

year = "2014",

month = sep,

day = "23",

doi = "10.1145/2628363.2634223",

language = "English",

series = "MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services",

publisher = "Association for Computing Machinery",

pages = "501--506",

booktitle = "MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services",

note = "16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2014 ; Conference date: 23-09-2014 Through 26-09-2014",

}

Vasiete, E, Patel, V, Chen, Y, Davis, L, Char, I, Chellappa, R & Yeh, T 2014, Toward a non-intrusive, physio-behavioral biometric for smartphones. in MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services. MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, Association for Computing Machinery, pp. 501-506, 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2014, Toronto, Canada, 23/09/14. https://doi.org/10.1145/2628363.2634223

Toward a non-intrusive, physio-behavioral biometric for smartphones. / Vasiete, Esther; Patel, Vishal; Chen, Yan et al.
MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services. Association for Computing Machinery, 2014. p. 501-506 (MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Toward a non-intrusive, physio-behavioral biometric for smartphones

AU - Vasiete, Esther

AU - Patel, Vishal

AU - Chen, Yan

AU - Davis, Larry

AU - Char, Ian

AU - Chellappa, Rama

AU - Yeh, Tom

PY - 2014/9/23

Y1 - 2014/9/23

N2 - Biometric authentication relies on an individual's inner characteristics and traits. We propose an active authentication system on a mobile device that relies on two biometric modalities: 3D gestures and face recognition. The novelty of our approach is to combine 3D gesture and face recognition in a non-intrusive and unconstrained environment; the active authentication system is running in the background while the user is performing his/her main task.

AB - Biometric authentication relies on an individual's inner characteristics and traits. We propose an active authentication system on a mobile device that relies on two biometric modalities: 3D gestures and face recognition. The novelty of our approach is to combine 3D gesture and face recognition in a non-intrusive and unconstrained environment; the active authentication system is running in the background while the user is performing his/her main task.

KW - 3D gesture recognition

KW - Behavioral biometric authentication

KW - Face recognition

KW - Fusion system

UR - http://www.scopus.com/inward/record.url?scp=84908565795&partnerID=8YFLogxK

U2 - 10.1145/2628363.2634223

DO - 10.1145/2628363.2634223

M3 - Conference contribution

AN - SCOPUS:84908565795

T3 - MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services

SP - 501

EP - 506

BT - MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services

PB - Association for Computing Machinery

T2 - 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2014

Y2 - 23 September 2014 through 26 September 2014

ER -

Vasiete E, Patel V, Chen Y, Davis L, Char I, Chellappa R et al. Toward a non-intrusive, physio-behavioral biometric for smartphones. In MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services. Association for Computing Machinery. 2014. p. 501-506. (MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services). doi: 10.1145/2628363.2634223

Toward a non-intrusive, physio-behavioral biometric for smartphones

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Cite this