Approaches to online handwritten signature verification

Handwritten signature is one of the most common methods of biometric authentication, where static and dynamic signature characteristics are used to confirm the user's identity. The existing developments are based on various technologies, such as the neural network, the hidden Markov model, and...

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Published in:Безопасность информационных технологий
Main Authors: Anastasia V. Beresneva, Anna V. Epishkina
Format: Article
Language:English
Published: Joint Stock Company "Experimental Scientific and Production Association SPELS 2020-06-01
Subjects:
Online Access:https://bit.mephi.ru/index.php/bit/article/view/1272
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author Anastasia V. Beresneva
Anna V. Epishkina
author_facet Anastasia V. Beresneva
Anna V. Epishkina
author_sort Anastasia V. Beresneva
collection DOAJ
container_title Безопасность информационных технологий
description Handwritten signature is one of the most common methods of biometric authentication, where static and dynamic signature characteristics are used to confirm the user's identity. The existing developments are based on various technologies, such as the neural network, the hidden Markov model, and machine learning algorithms. This topic is rapidly developing, new approaches and algorithms for solving the problem improve the accuracy of verification and learning speed. The purpose of this study is to analyze existing approaches to the signature verification. The most promising algorithm will be used as the basis for the developed authentication system based on a handwritten signature.
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spelling doaj-art-709b2ea0bfcd41219151ebfb2a2c5f982025-08-19T22:13:40ZengJoint Stock Company "Experimental Scientific and Production Association SPELSБезопасность информационных технологий2074-71282074-71362020-06-01272788510.26583/bit.2020.2.061190Approaches to online handwritten signature verificationAnastasia V. Beresneva0Anna V. Epishkina1National Nuclear Research University MEPHI (Moscow Engineering Physics Institute)National Nuclear Research University MEPHI (Moscow Engineering Physics Institute)Handwritten signature is one of the most common methods of biometric authentication, where static and dynamic signature characteristics are used to confirm the user's identity. The existing developments are based on various technologies, such as the neural network, the hidden Markov model, and machine learning algorithms. This topic is rapidly developing, new approaches and algorithms for solving the problem improve the accuracy of verification and learning speed. The purpose of this study is to analyze existing approaches to the signature verification. The most promising algorithm will be used as the basis for the developed authentication system based on a handwritten signature.https://bit.mephi.ru/index.php/bit/article/view/1272verification, authentication, biometric authentication, handwritten signature, machine learning, neural network.
spellingShingle Anastasia V. Beresneva
Anna V. Epishkina
Approaches to online handwritten signature verification
verification, authentication, biometric authentication, handwritten signature, machine learning, neural network.
title Approaches to online handwritten signature verification
title_full Approaches to online handwritten signature verification
title_fullStr Approaches to online handwritten signature verification
title_full_unstemmed Approaches to online handwritten signature verification
title_short Approaches to online handwritten signature verification
title_sort approaches to online handwritten signature verification
topic verification, authentication, biometric authentication, handwritten signature, machine learning, neural network.
url https://bit.mephi.ru/index.php/bit/article/view/1272
work_keys_str_mv AT anastasiavberesneva approachestoonlinehandwrittensignatureverification
AT annavepishkina approachestoonlinehandwrittensignatureverification