Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe

Due to the increasing population in our societies, the accurate identification of individuals has become crucial. As a result, the concept of access control has gained significance. Currently, the Automatic Fingerprint Identification System (AFIS) is the predominant method used for access control in...

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Main Author:	Ametefe, Divine Senanu
Format:	Thesis
Language:	English
Published:	2023
Online Access:	https://ir.uitm.edu.my/id/eprint/89329/1/89329.pdf
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id	my-uitm-ir.89329
record_format	uketd_dc
spelling	my-uitm-ir.893292024-01-17T07:43:16Z Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe 2023 Ametefe, Divine Senanu Due to the increasing population in our societies, the accurate identification of individuals has become crucial. As a result, the concept of access control has gained significance. Currently, the Automatic Fingerprint Identification System (AFIS) is the predominant method used for access control in restricted areas like immigration borders, labs, offices, and even smart devices. However, despite its widespread use, AFIS is highly vulnerable to presentation attacks involving the fabrication and presentation of fake fingerprints to AFIS. Efforts have been made to address this concern through hardware and software-based approaches. Hardware-based methods incorporate additional sensors to capture other live human traits during fingerprint authentication, such as pulse rate, blood flow, and odor. Unfortunately, attackers have found ways to create thin layered spoofs that can deceive these systems. As a result, software-based methods have emerged, which focus on learning inherent live fingerprint features to distinguish against spoofs. 2023 Thesis https://ir.uitm.edu.my/id/eprint/89329/ https://ir.uitm.edu.my/id/eprint/89329/1/89329.pdf text en public phd doctoral Universiti Teknologi MARA (UiTM) College of Engineering Sarnin, Suzi Seroja (Ir. Ts. Dr.)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Sarnin, Suzi Seroja (Ir. Ts. Dr.)
description	Due to the increasing population in our societies, the accurate identification of individuals has become crucial. As a result, the concept of access control has gained significance. Currently, the Automatic Fingerprint Identification System (AFIS) is the predominant method used for access control in restricted areas like immigration borders, labs, offices, and even smart devices. However, despite its widespread use, AFIS is highly vulnerable to presentation attacks involving the fabrication and presentation of fake fingerprints to AFIS. Efforts have been made to address this concern through hardware and software-based approaches. Hardware-based methods incorporate additional sensors to capture other live human traits during fingerprint authentication, such as pulse rate, blood flow, and odor. Unfortunately, attackers have found ways to create thin layered spoofs that can deceive these systems. As a result, software-based methods have emerged, which focus on learning inherent live fingerprint features to distinguish against spoofs.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Ametefe, Divine Senanu
spellingShingle	Ametefe, Divine Senanu Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe
author_facet	Ametefe, Divine Senanu
author_sort	Ametefe, Divine Senanu
title	Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe
title_short	Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe
title_full	Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe
title_fullStr	Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe
title_full_unstemmed	Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe
title_sort	development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / divine senanu ametefe
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	College of Engineering
publishDate	2023
url	https://ir.uitm.edu.my/id/eprint/89329/1/89329.pdf
_version_	1794192214063054848

Development of live fingerprint generalization model using semi-supervised adversarial learned one-class classifier for fingerprint presentation attack detection / Divine Senanu Ametefe

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