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The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras †

Even though biometric technology increases the security of systems that use it, they are prone to spoof attacks where attempts of fraudulent biometrics are used. To overcome these risks, techniques on detecting liveness of the biometric measure are employed. For example, in systems that utilise face...

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Autores principales: Albakri, Ghazel, Alghowinem, Sharifa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515036/
https://www.ncbi.nlm.nih.gov/pubmed/31022904
http://dx.doi.org/10.3390/s19081928
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author Albakri, Ghazel
Alghowinem, Sharifa
author_facet Albakri, Ghazel
Alghowinem, Sharifa
author_sort Albakri, Ghazel
collection PubMed
description Even though biometric technology increases the security of systems that use it, they are prone to spoof attacks where attempts of fraudulent biometrics are used. To overcome these risks, techniques on detecting liveness of the biometric measure are employed. For example, in systems that utilise face authentication as biometrics, a liveness is assured using an estimation of blood flow, or analysis of quality of the face image. Liveness assurance of the face using real depth technique is rarely used in biometric devices and in the literature, even with the availability of depth datasets. Therefore, this technique of employing 3D cameras for liveness of face authentication is underexplored for its vulnerabilities to spoofing attacks. This research reviews the literature on this aspect and then evaluates the liveness detection to suggest solutions that account for the weaknesses found in detecting spoofing attacks. We conduct a proof-of-concept study to assess the liveness detection of 3D cameras in three devices, where the results show that having more flexibility resulted in achieving a higher rate in detecting spoofing attacks. Nonetheless, it was found that selecting a wide depth range of the 3D camera is important for anti-spoofing security recognition systems such as surveillance cameras used in airports. Therefore, to utilise the depth information and implement techniques that detect faces regardless of the distance, a 3D camera with long maximum depth range (e.g., 20 m) and high resolution stereo cameras could be selected, which can have a positive impact on accuracy.
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spelling pubmed-65150362019-05-30 The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras † Albakri, Ghazel Alghowinem, Sharifa Sensors (Basel) Article Even though biometric technology increases the security of systems that use it, they are prone to spoof attacks where attempts of fraudulent biometrics are used. To overcome these risks, techniques on detecting liveness of the biometric measure are employed. For example, in systems that utilise face authentication as biometrics, a liveness is assured using an estimation of blood flow, or analysis of quality of the face image. Liveness assurance of the face using real depth technique is rarely used in biometric devices and in the literature, even with the availability of depth datasets. Therefore, this technique of employing 3D cameras for liveness of face authentication is underexplored for its vulnerabilities to spoofing attacks. This research reviews the literature on this aspect and then evaluates the liveness detection to suggest solutions that account for the weaknesses found in detecting spoofing attacks. We conduct a proof-of-concept study to assess the liveness detection of 3D cameras in three devices, where the results show that having more flexibility resulted in achieving a higher rate in detecting spoofing attacks. Nonetheless, it was found that selecting a wide depth range of the 3D camera is important for anti-spoofing security recognition systems such as surveillance cameras used in airports. Therefore, to utilise the depth information and implement techniques that detect faces regardless of the distance, a 3D camera with long maximum depth range (e.g., 20 m) and high resolution stereo cameras could be selected, which can have a positive impact on accuracy. MDPI 2019-04-24 /pmc/articles/PMC6515036/ /pubmed/31022904 http://dx.doi.org/10.3390/s19081928 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Albakri, Ghazel
Alghowinem, Sharifa
The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras †
title The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras †
title_full The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras †
title_fullStr The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras †
title_full_unstemmed The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras †
title_short The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras †
title_sort effectiveness of depth data in liveness face authentication using 3d sensor cameras †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515036/
https://www.ncbi.nlm.nih.gov/pubmed/31022904
http://dx.doi.org/10.3390/s19081928
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