Cover Image

A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication

Authentication is a way to enable an individual to be uniquely identified usually based on passwords and personal identification number (PIN). The main problems of such authentication techniques are the unwillingness of the users to remember long and challenging combinations of numbers, letters, an...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohamed, Prof. Madya Dr. Mohamad Afendee, Abdul Kadir, Prof. Madya Dr. Mohd Fadzil, Mamat, Prof. Dr. Mustafa, Makhtar, Prof. Ts. Dr. Mokhairi
Format: Book Section
Language:English
English
Published: Intechopen 2018
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.unisza.edu.my/3860/1/FH05-FIK-19-22886.pdf
http://eprints.unisza.edu.my/3860/2/FH05-FIK-19-22885.pdf
http://eprints.unisza.edu.my/3860/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-unisza-ir.3860
record_format eprints
spelling my-unisza-ir.38602022-01-10T04:17:51Z http://eprints.unisza.edu.my/3860/ A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication Mohamed, Prof. Madya Dr. Mohamad Afendee Abdul Kadir, Prof. Madya Dr. Mohd Fadzil Mamat, Prof. Dr. Mustafa Makhtar, Prof. Ts. Dr. Mokhairi QA75 Electronic computers. Computer science Authentication is a way to enable an individual to be uniquely identified usually based on passwords and personal identification number (PIN). The main problems of such authentication techniques are the unwillingness of the users to remember long and challenging combinations of numbers, letters, and symbols that can be lost, forged, stolen, or forgotten. In this paper, we investigate the current advances in the use of behavioral-based biometrics for user authentication. The application of behavioral-based biometric authentication basically contains three major modules, namely, data capture, feature extraction, and classifier. This application is focusing on extracting the behavioral features related to the user and using these features for authentication measure. The objective is to determine the classifier techniques that mostly are used for data analysis during authentication process. From the comparison, we anticipate to discover the gap for improving the performance of behavioral-based biometric authentication. Additionally, we highlight the set of classifier techniques that are best performing for behavioral-based biometric authentication. Intechopen 2018 Book Section NonPeerReviewed text en http://eprints.unisza.edu.my/3860/1/FH05-FIK-19-22886.pdf text en http://eprints.unisza.edu.my/3860/2/FH05-FIK-19-22885.pdf Mohamed, Prof. Madya Dr. Mohamad Afendee and Abdul Kadir, Prof. Madya Dr. Mohd Fadzil and Mamat, Prof. Dr. Mustafa and Makhtar, Prof. Ts. Dr. Mokhairi (2018) A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication. In: Recent Advances in Cryptography and Network Security. Intechopen, UK, pp. 43-59. ISBN 978-1-78984-345-3
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mohamed, Prof. Madya Dr. Mohamad Afendee
Abdul Kadir, Prof. Madya Dr. Mohd Fadzil
Mamat, Prof. Dr. Mustafa
Makhtar, Prof. Ts. Dr. Mokhairi
A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication
description Authentication is a way to enable an individual to be uniquely identified usually based on passwords and personal identification number (PIN). The main problems of such authentication techniques are the unwillingness of the users to remember long and challenging combinations of numbers, letters, and symbols that can be lost, forged, stolen, or forgotten. In this paper, we investigate the current advances in the use of behavioral-based biometrics for user authentication. The application of behavioral-based biometric authentication basically contains three major modules, namely, data capture, feature extraction, and classifier. This application is focusing on extracting the behavioral features related to the user and using these features for authentication measure. The objective is to determine the classifier techniques that mostly are used for data analysis during authentication process. From the comparison, we anticipate to discover the gap for improving the performance of behavioral-based biometric authentication. Additionally, we highlight the set of classifier techniques that are best performing for behavioral-based biometric authentication.
format Book Section
author Mohamed, Prof. Madya Dr. Mohamad Afendee
Abdul Kadir, Prof. Madya Dr. Mohd Fadzil
Mamat, Prof. Dr. Mustafa
Makhtar, Prof. Ts. Dr. Mokhairi
author_facet Mohamed, Prof. Madya Dr. Mohamad Afendee
Abdul Kadir, Prof. Madya Dr. Mohd Fadzil
Mamat, Prof. Dr. Mustafa
Makhtar, Prof. Ts. Dr. Mokhairi
author_sort Mohamed, Prof. Madya Dr. Mohamad Afendee
title A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication
title_short A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication
title_full A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication
title_fullStr A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication
title_full_unstemmed A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication
title_sort survey of machine learning techniques for behavioral-based biometric user authentication
publisher Intechopen
publishDate 2018
url http://eprints.unisza.edu.my/3860/1/FH05-FIK-19-22886.pdf
http://eprints.unisza.edu.my/3860/2/FH05-FIK-19-22885.pdf
http://eprints.unisza.edu.my/3860/
_version_ 1724079297767931904
score 13.211869

Similar Items