EEG-Based User Authentication Using a Convolutional Neural Network

Ting Yu, Chun-Shu Wei, Kuan Jung Chiang, Masaki Nakanishi, Tzyy Ping Jung

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

In this study, we explore the feasibility of using a convolutional neural network (CNN) to decode human electroencephalographic (EEG) response for user authentication. In particular, we exploit the low-frequency components of the steady-state visual-evoked potentials (SSVEP) that contain consistent individualized patterns as the biometric. We evaluate the discriminating capabilities across different parameter configurations to optimize the CNN model. We also investigate how the length of EEG data impact the authentication performance. Our proposed framework achieved ~97% accuracy of crossday user authentication across 8 subjects, shedding light on a practical EEG-based biometric powered by the CNN-based brain decoding.

原文English
主出版物標題9th International IEEE EMBS Conference on Neural Engineering, NER 2019
發行者IEEE Computer Society
頁面1011-1014
頁數4
ISBN(電子)9781538679210
DOIs
出版狀態Published - 16 五月 2019
事件9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States
持續時間: 20 三月 201923 三月 2019

出版系列

名字International IEEE/EMBS Conference on Neural Engineering, NER
2019-March
ISSN(列印)1948-3546
ISSN(電子)1948-3554

Conference

Conference9th International IEEE EMBS Conference on Neural Engineering, NER 2019
國家United States
城市San Francisco
期間20/03/1923/03/19

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