EEG-Based Person Authentication System in Different Brain States

Nga Tran, Dat TRAN, Shuangzhe LIU, Wanli MA, Tien PHAM

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

6 Citations (Scopus)


Using EEG signals, which measure the electrical field generated by active neurons in a brain, to access a security system has received a considerable attention from researchers with a large number of publications. While elicited EEG-based credentials are known as sensitive to affective states, very few studies address that issue when utilizing brain-wave for authentication purpose. In this paper, we investigate the user-authenticating ability of an EEG-based person authentication (EBPA) system when clients are in a variety of brain states during performing mental tasks to login. The experimental results, which are supported by neuropsychological evidence, show that when people are in like or unfamilar brain states, the EBPA system has better accuracy compared to when they dislike or are familiar with stimuli. Some other issues involving human affective states are also introduced to help design a real-world EBPA system that is not only stable and high security but also comfortable.

Original languageEnglish
Title of host publication9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)9781538679210
ISBN (Print)9781538679227
Publication statusPublished - 16 May 2019
Event2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) - California, San Francisco, United States
Duration: 20 Mar 201923 Mar 2019

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554


Conference2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)
Abbreviated titleNER
Country/TerritoryUnited States
CitySan Francisco
Internet address


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