Advancing security measures: A brainwave-based biometric system for user identification and authentication

In contemporary organizational contexts, the imperative for robust user identification and authentication systems to safeguard assets is paramount. Conventional methods like passwords, secret codes, and personal identification numbers are prone to compromise and human error. This study explores the...

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Main Authors: Muhammad Nur Arif, Mohd Farid, Hasan, Md Mahmudul, Norizam, Sulaiman, Mahfuzah, Mustafa, Siti Armiza, Mohd Aris
Format: Article
Language:English
Published: Penerbit UMP 2024
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/41828/
http://umpir.ump.edu.my/id/eprint/41828/1/Advancing%20Security%20Measures_%20%20A%20Brainwave%20Based%20Biometric.pdf
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author Muhammad Nur Arif, Mohd Farid
Hasan, Md Mahmudul
Norizam, Sulaiman
Mahfuzah, Mustafa
Siti Armiza, Mohd Aris
author_facet Muhammad Nur Arif, Mohd Farid
Hasan, Md Mahmudul
Norizam, Sulaiman
Mahfuzah, Mustafa
Siti Armiza, Mohd Aris
author_sort Muhammad Nur Arif, Mohd Farid
building UMP Institutional Repository
collection Online Access
description In contemporary organizational contexts, the imperative for robust user identification and authentication systems to safeguard assets is paramount. Conventional methods like passwords, secret codes, and personal identification numbers are prone to compromise and human error. This study explores the feasibility of utilizing human brainwaves, specifically Electroencephalogram (EEG) signals, as a biometric authentication system. Employing the Unicorn Hybrid Black EEG device for measurement and LabVIEW software for analysis, the research focuses on discerning EEG features pertinent to authentication. Through controlled activities encompassing imaginative (imagining singing a favorite song, imagining opening a locked door) and physical tasks (engaging in a mobile game, solving a Rubik's cube), the study elucidates the dominance of the EEG Theta band across varied cognitive and motor processes. Further analysis underscores the heightened power of the EEG Alpha band during relaxation phases and the prevalence of the EEG Beta band during heightened cognitive engagement. The classification of selected EEG features highlights the efficacy of utilizing Standard Deviation as a discriminative factor, achieving a commendable accuracy of 93.35% with a training-testing ratio of 80:20. This research underscores the potential of EEG-based authentication systems in fortifying organizational security protocols.
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spelling ump-418282024-07-09T07:41:13Z http://umpir.ump.edu.my/id/eprint/41828/ Advancing security measures: A brainwave-based biometric system for user identification and authentication Muhammad Nur Arif, Mohd Farid Hasan, Md Mahmudul Norizam, Sulaiman Mahfuzah, Mustafa Siti Armiza, Mohd Aris TK Electrical engineering. Electronics Nuclear engineering In contemporary organizational contexts, the imperative for robust user identification and authentication systems to safeguard assets is paramount. Conventional methods like passwords, secret codes, and personal identification numbers are prone to compromise and human error. This study explores the feasibility of utilizing human brainwaves, specifically Electroencephalogram (EEG) signals, as a biometric authentication system. Employing the Unicorn Hybrid Black EEG device for measurement and LabVIEW software for analysis, the research focuses on discerning EEG features pertinent to authentication. Through controlled activities encompassing imaginative (imagining singing a favorite song, imagining opening a locked door) and physical tasks (engaging in a mobile game, solving a Rubik's cube), the study elucidates the dominance of the EEG Theta band across varied cognitive and motor processes. Further analysis underscores the heightened power of the EEG Alpha band during relaxation phases and the prevalence of the EEG Beta band during heightened cognitive engagement. The classification of selected EEG features highlights the efficacy of utilizing Standard Deviation as a discriminative factor, achieving a commendable accuracy of 93.35% with a training-testing ratio of 80:20. This research underscores the potential of EEG-based authentication systems in fortifying organizational security protocols. Penerbit UMP 2024-05 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/41828/1/Advancing%20Security%20Measures_%20%20A%20Brainwave%20Based%20Biometric.pdf Muhammad Nur Arif, Mohd Farid and Hasan, Md Mahmudul and Norizam, Sulaiman and Mahfuzah, Mustafa and Siti Armiza, Mohd Aris (2024) Advancing security measures: A brainwave-based biometric system for user identification and authentication. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 6 (1). pp. 66-80. ISSN 2637-0883. (Published) https://doi.org/10.15282/mekatronika.v6i1.10185 https://doi.org/10.15282/mekatronika.v6i1.10185
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Muhammad Nur Arif, Mohd Farid
Hasan, Md Mahmudul
Norizam, Sulaiman
Mahfuzah, Mustafa
Siti Armiza, Mohd Aris
Advancing security measures: A brainwave-based biometric system for user identification and authentication
title Advancing security measures: A brainwave-based biometric system for user identification and authentication
title_full Advancing security measures: A brainwave-based biometric system for user identification and authentication
title_fullStr Advancing security measures: A brainwave-based biometric system for user identification and authentication
title_full_unstemmed Advancing security measures: A brainwave-based biometric system for user identification and authentication
title_short Advancing security measures: A brainwave-based biometric system for user identification and authentication
title_sort advancing security measures: a brainwave-based biometric system for user identification and authentication
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/41828/
http://umpir.ump.edu.my/id/eprint/41828/
http://umpir.ump.edu.my/id/eprint/41828/
http://umpir.ump.edu.my/id/eprint/41828/1/Advancing%20Security%20Measures_%20%20A%20Brainwave%20Based%20Biometric.pdf