User identification and verification based on auditory evoked potentials using CNN

Vida Ghalami and Tohid Yousefi Rezaii and Mohammad Ali Tinati and Ali Farzamnia and Azam Khalili and Amir Rastegarnia and Ervin Gubin Moung (2025) User identification and verification based on auditory evoked potentials using CNN. Circuits, Systems, and Signal Processing, 44. pp. 575-591. ISSN 0278-081X

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Abstract

In recent years, researchers have focused on the biometric applications of bioelectrical signals, particularly electroencephalograms (EEG), to enhance information security. Using EEG as a biometric offers advantages that cannot be forgotten or forged. One approach to utilizing EEG signals for biometric purposes involves recording auditory evoked potentials (AEP). AEPs are electrical potentials that arise in response to auditory stimulation in the cerebral cortex. These signals are stimulus-dependent and can vary with the auditory stimulus, allowing these signals to be employed even if the registered signal was compromised. In this paper, discriminative features are extracted and classified using convolutional neural networks. A dataset recorded from 20 users using auditory stimulation is analyzed. The reported results demonstrate a classification accuracy of 98.99% in identification mode and an equal error rate of 1.18% in verification mode. These outcomes showcase the proposed method’s high accuracy, marking an improvement over existing methods. Furthermore, the system’s practicality is enhanced by utilizing fewer channels, and its performance is assessed by reducing the number of channels.

Item Type:	Article
Keyword:	Auditory evoked potentials, Auditory late latency response, Biometrics, User identification and verification
Subjects:	Q Science > QA Mathematics > QA1-939 Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK7800-8360 Electronics
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	SITI AZIZAH BINTI IDRIS -
Date Deposited:	23 Jul 2025 14:59
Last Modified:	23 Jul 2025 14:59
URI:	https://eprints.ums.edu.my/id/eprint/44610

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