Hand-Based Biometric System Using Convolutional Neural Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F20%3A39916037" target="_blank" >RIV/00216275:25410/20:39916037 - isvavai.cz</a>

Result on the web

<a href="https://aip.vse.cz/pdfs/aip/2020/01/04.pdf" target="_blank" >https://aip.vse.cz/pdfs/aip/2020/01/04.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18267/j.aip.131" target="_blank" >10.18267/j.aip.131</a>

Result language

angličtina

Original language name

Hand-Based Biometric System Using Convolutional Neural Networks

Original language description

Today, data security is an increasingly hot topic, and thus also the security and reliability of end-user identity verification, i.e. authentication. In recent years, banks began to substitute password authentication by more secure ways of authentication because passwords were not considered to be secure enough. Current legislation even forces banks to implement multi-factor authentication of their clients. Banks, therefore, consider using biometric authentication as one of the possible ways. To verify a user&apos;s identity, biometric authentication uses unique biometric characteristics of the user. Examples of such methods are facial recognition, iris scanning, fingerprints, and so on. This paper deals with another biometric feature that could be used for authentication in mobile banking applications; as almost all mobile phones have an integrated camera, hand authentication can make a banking information system more secure and its user interface more convenient. Although the idea of hand biometric authentication is not entirely new and there exist many ways of implementing it, our approach based on using convolutional neural networks is not only innovative, but its results are promising as well. This paper presents a modern approach to identifying users by convolutional neural networks when this type of neural network is used both for hand features extraction and bank user identity validation.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Acta Informatica Pragensia

ISSN

1805-4951

e-ISSN

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Volume of the periodical

9

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

10

Pages from-to

48-57

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85090222040