In the quest for optimal EEG-based biometric authentication, this study investigates the pivotal balance for accurate identification without sacrificing performance or adding unnecessary computational complexity. Through a methodical exploration of segment durations, and employing a variety of sophisticated machine learning models, the research seeks to pinpoint a threshold where EEG data provides maximum informational yield for authentication purposes. The findings are set to advance the field of non-invasive biometric technologies, proposing a practical approach to secure and user-friendly identity verification systems while also raising considerations for the real-world application of EEG-based biometric authentication beyond controlled environments.
@article{arxiv.2403.12644,
title = {When Does Your Brain Know You? Segment Length and Its Impact on EEG-based Biometric Authentication Accuracy},
author = {Nibras Abo Alzahab and Lorenzo Scalise and Marco Baldi},
journal= {arXiv preprint arXiv:2403.12644},
year = {2024}
}