Brain–Computer Interface for EEG-Based Authentication: Advancements and Practical Implications

Authentication is a critical component of digital security, and traditional methods often encounter significant vulnerabilities and limitations. This study addresses the emerging field of EEG-based authentication systems, highlighting their theoretical advancements and practical applicability. We co...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 25; no. 16; p. 4946
Main Authors:	Alahaideb, Lamia, Al-Nafjan, Abeer, Aljumah, Hessah, Aldayel, Mashael
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 10.08.2025 MDPI
Subjects:	Accuracy Adaptive technology Algorithms Analysis authentication Biometric identification Biometrics Brain research Brain-Computer Interfaces brain–computer interface (BCI) Classification Computer Security convolutional neural networks (CNN) Data encryption chips Datasets Electroencephalography electroencephalography (EEG) Electroencephalography - methods event-related potentials (ERP) Fourier transforms Humans Literature reviews Machine learning Neural Networks, Computer Neurophysiology Rapid serial visual presentation Safety and security measures Security management Security systems Signal processing Support Vector Machine Support vector machines Systematic review Systems and data security software brain–computer interface (BCI) electroencephalography (EEG) event-related potentials (ERP) convolutional neural networks (CNN) authentication
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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