Vulnerabilities detection using attack recognition technique in multi-factor authentication

Authentication is one of the essentials components of information security. It has become one of the most basic security requirements for network communication. Today, there is a necessity for a strong level of authentication to guarantee a significant level of security is being conveyed to the appl...

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Main Authors: Ariffin N.A.M., Rahim F.A., Asmawi A., Ibrahim Z.-A.
Other Authors: 55349248100
Format: Article
Published: Universitas Ahmad Dahlan 2023
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spelling my.uniten.dspace-257032023-05-29T16:13:01Z Vulnerabilities detection using attack recognition technique in multi-factor authentication Ariffin N.A.M. Rahim F.A. Asmawi A. Ibrahim Z.-A. 55349248100 57350579500 25824748900 57203863738 Authentication is one of the essentials components of information security. It has become one of the most basic security requirements for network communication. Today, there is a necessity for a strong level of authentication to guarantee a significant level of security is being conveyed to the application. As such, it expedites challenging issues on security and efficiency. Security issues such as privacy and data integrity emerge because of the absence of control and authority. In addition, the bigger issue for multi-factor authentication is on the high execution time that leads to overall performance degradation. Most of existing studies related to multi-factor authentication schemes does not detect weaknesses based on user behavior. Most recent research does not look at the efficiency of the system by focusing only on improving the security aspect of authentication. Hence, this research proposes a new multi-factor authentication scheme that can withstand attacks, based on user behavior and maintaining optimum efficiency. Experiments have been conducted to evaluate this scheme. The results of the experiment show that the processing time of the proposed scheme is lower than the processing time of other schemes. This is particularly important after additional security features have been added to the scheme. � 2020 Universitas Ahmad Dahlan. Final 2023-05-29T08:13:00Z 2023-05-29T08:13:00Z 2020 Article 10.12928/TELKOMNIKA.V18I4.14898 2-s2.0-85087614936 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087614936&doi=10.12928%2fTELKOMNIKA.V18I4.14898&partnerID=40&md5=ae565f7845c9d77918716e2b9424d6a9 https://irepository.uniten.edu.my/handle/123456789/25703 18 4 1998 2003 All Open Access, Hybrid Gold, Green Universitas Ahmad Dahlan Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Authentication is one of the essentials components of information security. It has become one of the most basic security requirements for network communication. Today, there is a necessity for a strong level of authentication to guarantee a significant level of security is being conveyed to the application. As such, it expedites challenging issues on security and efficiency. Security issues such as privacy and data integrity emerge because of the absence of control and authority. In addition, the bigger issue for multi-factor authentication is on the high execution time that leads to overall performance degradation. Most of existing studies related to multi-factor authentication schemes does not detect weaknesses based on user behavior. Most recent research does not look at the efficiency of the system by focusing only on improving the security aspect of authentication. Hence, this research proposes a new multi-factor authentication scheme that can withstand attacks, based on user behavior and maintaining optimum efficiency. Experiments have been conducted to evaluate this scheme. The results of the experiment show that the processing time of the proposed scheme is lower than the processing time of other schemes. This is particularly important after additional security features have been added to the scheme. � 2020 Universitas Ahmad Dahlan.
author2 55349248100
author_facet 55349248100
Ariffin N.A.M.
Rahim F.A.
Asmawi A.
Ibrahim Z.-A.
format Article
author Ariffin N.A.M.
Rahim F.A.
Asmawi A.
Ibrahim Z.-A.
spellingShingle Ariffin N.A.M.
Rahim F.A.
Asmawi A.
Ibrahim Z.-A.
Vulnerabilities detection using attack recognition technique in multi-factor authentication
author_sort Ariffin N.A.M.
title Vulnerabilities detection using attack recognition technique in multi-factor authentication
title_short Vulnerabilities detection using attack recognition technique in multi-factor authentication
title_full Vulnerabilities detection using attack recognition technique in multi-factor authentication
title_fullStr Vulnerabilities detection using attack recognition technique in multi-factor authentication
title_full_unstemmed Vulnerabilities detection using attack recognition technique in multi-factor authentication
title_sort vulnerabilities detection using attack recognition technique in multi-factor authentication
publisher Universitas Ahmad Dahlan
publishDate 2023
_version_ 1806424252910403584
score 13.214268