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Content Provider | IEEE Xplore Digital Library |
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Author | Ruiz Blondet, M.V. Khalifian, N. Kurtz, K.J. Laszlo, S. Zhanpeng Jin |
Copyright Year | 2014 |
Description | Author affiliation: Depts. of Electr. & Comp. Eng. & Bioeng., Binghamton Univ., Binghamton, NY, USA (Zhanpeng Jin) || Dept. of Bioeng., Binghamton Univ. Binghamton, Binghamton, NY, USA (Ruiz Blondet, M.V.) || Dept. of Psychol., Binghamton Univ., Binghamton, NY, USA (Khalifian, N.; Kurtz, K.J.; Laszlo, S.) |
Abstract | Acquisition of EEG is becoming more and more affordable, and relatively high-quality signals are now digitizable even with consumer-grade hardware. The improvement in EEG hardware opens many possibilities for its applied usage. In this paper we explore the possibility of using the EEG as an secure authentication method. To achieve this goal, we process the EEG under two different methods: Cross-correlation and Divergent Autoencoding. The first method being a traditional approach to compare the similarity between two signals, and the second a classification tool originally developed to simulate aspects of human intelligence in the domain of cognitive psychology, but with potentially interesting applications in engineering. |
Starting Page | 1 |
Ending Page | 2 |
File Size | 282021 |
Page Count | 2 |
File Format | |
ISBN | 9781479937288 |
DOI | 10.1109/NEBEC.2014.6972734 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-04-25 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Electroencephalography Authentication Educational institutions Training Psychology Hardware Brain modeling |
Content Type | Text |
Resource Type | Article |
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