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Gaze-based Presentation Attack Detection for Users Wearing Tinted Glasses

Ali, Asad, Alsufyani, Nawal, Hoque, Sanaul, Deravi, Farzin (2019) Gaze-based Presentation Attack Detection for Users Wearing Tinted Glasses. In: 2019 Eighth International Conference on Emerging Security Technologies (EST). 2019 Eighth International Conference on Emerging Security Technologies (EST). . IEEE ISBN 978-1-72815-547-0. E-ISBN 978-1-72815-546-3. (doi:10.1109/EST.2019.8806201) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:74614)

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Biometric authentication is vulnerable to presentation (spoofing) attacks. It is important to address the security vulnerability of spoofing attacks where an attacker uses an artefact presented at the sensor to subvert the system. Gaze-tracking has been proposed for such attack detection. In this paper, we explore the sensitivity of a gaze-based approach to spoofing detection in the presence of eye-glasses that may impact detection performance. In particular, we investigate the use of partially tinted glasses such as may be used in hazardous environments or outdoors in mobile application scenarios The attack scenarios considered in this work include the use of projected photos, 2D and 3D masks. A gaze-based spoofing detection system has been extensively evaluated using data captured from volunteers performing genuine attempts (with and without wearing such tinted glasses) as well as spoofing attempts using various artefacts. The results of the evaluations indicate that the presence of tinted glasses has a small impact on the accuracy of attack detection, thereby making the use of such gaze-based features possible for a wider range of applications.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/EST.2019.8806201
Uncontrolled keywords: biometrics, spoofing, liveness, mobile security, gaze tracking, challenge-response technique
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Sanaul Hoque
Date Deposited: 26 Feb 2020 10:17 UTC
Last Modified: 27 Feb 2020 11:43 UTC
Resource URI: (The current URI for this page, for reference purposes)
Hoque, Sanaul:
Deravi, Farzin:
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