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)
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Abstract
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.
| Item Type: | Article |
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| Uncontrolled Keywords: | Biometric Authentication System; Electroencephalogram; EEG Theta Band; EEG Alpha Band; EEG Beta Band; Classification Accuracy |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 09 Jul 2024 07:41 |
| Last Modified: | 09 Jul 2024 07:41 |
| URI: | http://umpir.ump.edu.my/id/eprint/41828 |
| Download Statistic: | View Download Statistics |
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