Security enhancement of dynamic signature by utilizing local features with individual threshold

Security enhancement of dynamic signature by utilizing local features with individual threshold

Dynamic signature has potential to replace conventional signature in verifying an authorised person since it is legal and widely accepted by society. To date, most of the existing researches emphasise in obtaining a high performance of Genuine Acceptance Rate (GAR). However, at the same time, a high...

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Main Authors: Suryanti, Awang, Nor Faradilla, Mohamed Idris, Junaida, Sulaiman
Format: Article
Language:English
Published: American Scientific Publisher 2018
Subjects:
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/19446/
http://umpir.ump.edu.my/id/eprint/19446/
http://umpir.ump.edu.my/id/eprint/19446/
http://umpir.ump.edu.my/id/eprint/19446/1/56.%20Security%20Enhancement%20of%20Dynamic%20Signature%20by%20Utilizing%20Local%20Features%20with%20Individual%20Threshold1.pdf
id ump-19446
recordtype eprints
spelling ump-194462018-11-22T04:29:36Z http://umpir.ump.edu.my/id/eprint/19446/ Security enhancement of dynamic signature by utilizing local features with individual threshold Suryanti, Awang Nor Faradilla, Mohamed Idris Junaida, Sulaiman QA76 Computer software Dynamic signature has potential to replace conventional signature in verifying an authorised person since it is legal and widely accepted by society. To date, most of the existing researches emphasise in obtaining a high performance of Genuine Acceptance Rate (GAR). However, at the same time, a high percentage of False Acceptance Rate (FAR) is achieved which indicates the verification system has a high-security vulnerability that exposes the signature being forged by an imposter. Therefore, this research aims to enhance the security level by fully utilising the advantages of all local features with the deployment of individual threshold in verifying a genuine signature. The features are based on time and strokes of the dynamic signature. The individual threshold is obtained during the training process to acquire an accurate verification setting for each signature to improve the performance of FAR. Subsequently, experiments are conducted using different classifiers including Neural Network (NN), Bayes Network and Linear Discriminant Analysis (LDA) and their outputs are measured using Genuine Acceptance Rate (GAR), False Rejection Rate (FRR) and False Acceptance Rate (FAR). The results showed that signature verification using individual threshold produced the highest GAR of 98.2%, the smallest FRR and FAR of 1.8% and 1.0% respectively, and outperformed the results with a common threshold. Thus, the proposed technique increased the security in signature verification with a lower error rate in FAR. American Scientific Publisher 2018 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/19446/1/56.%20Security%20Enhancement%20of%20Dynamic%20Signature%20by%20Utilizing%20Local%20Features%20with%20Individual%20Threshold1.pdf Suryanti, Awang and Nor Faradilla, Mohamed Idris and Junaida, Sulaiman (2018) Security enhancement of dynamic signature by utilizing local features with individual threshold. Advanced Science Letters, 24 (10). pp. 7636-7642. ISSN 1936-6612 https://doi.org/10.1166/asl.2018.12992 doi: 10.1166/asl.2018.12992
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Suryanti, Awang
Nor Faradilla, Mohamed Idris
Junaida, Sulaiman
Security enhancement of dynamic signature by utilizing local features with individual threshold
description Dynamic signature has potential to replace conventional signature in verifying an authorised person since it is legal and widely accepted by society. To date, most of the existing researches emphasise in obtaining a high performance of Genuine Acceptance Rate (GAR). However, at the same time, a high percentage of False Acceptance Rate (FAR) is achieved which indicates the verification system has a high-security vulnerability that exposes the signature being forged by an imposter. Therefore, this research aims to enhance the security level by fully utilising the advantages of all local features with the deployment of individual threshold in verifying a genuine signature. The features are based on time and strokes of the dynamic signature. The individual threshold is obtained during the training process to acquire an accurate verification setting for each signature to improve the performance of FAR. Subsequently, experiments are conducted using different classifiers including Neural Network (NN), Bayes Network and Linear Discriminant Analysis (LDA) and their outputs are measured using Genuine Acceptance Rate (GAR), False Rejection Rate (FRR) and False Acceptance Rate (FAR). The results showed that signature verification using individual threshold produced the highest GAR of 98.2%, the smallest FRR and FAR of 1.8% and 1.0% respectively, and outperformed the results with a common threshold. Thus, the proposed technique increased the security in signature verification with a lower error rate in FAR.
format Article
author Suryanti, Awang
Nor Faradilla, Mohamed Idris
Junaida, Sulaiman
author_facet Suryanti, Awang
Nor Faradilla, Mohamed Idris
Junaida, Sulaiman
author_sort Suryanti, Awang
title Security enhancement of dynamic signature by utilizing local features with individual threshold
title_short Security enhancement of dynamic signature by utilizing local features with individual threshold
title_full Security enhancement of dynamic signature by utilizing local features with individual threshold
title_fullStr Security enhancement of dynamic signature by utilizing local features with individual threshold
title_full_unstemmed Security enhancement of dynamic signature by utilizing local features with individual threshold
title_sort security enhancement of dynamic signature by utilizing local features with individual threshold
publisher American Scientific Publisher
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/19446/
http://umpir.ump.edu.my/id/eprint/19446/
http://umpir.ump.edu.my/id/eprint/19446/
http://umpir.ump.edu.my/id/eprint/19446/1/56.%20Security%20Enhancement%20of%20Dynamic%20Signature%20by%20Utilizing%20Local%20Features%20with%20Individual%20Threshold1.pdf
first_indexed 2023-09-18T22:27:44Z
last_indexed 2023-09-18T22:27:44Z
_version_ 1777416079904079872

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