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A High-Security EEG-Based Login System with RSVP Stimuli and Dry Electrodes
- Authors
- Chen, Yiyu; Atnafu, Ayalneh Dessalegn; Schlattner, Isabella; Weldtsadik, Wendimagegn Tariku; Roh, Myung-Cheol; Kim, Hyoung Joong; Lee, Seong-Whan; Blankertz, Benjamin; Fazli, Siamac
- Issue Date
- Dec-2016
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Biometrics; EEG; brain-computer interfaces; computer security; authentication; RSVP; dry electrodes; ERP
- Citation
- IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, v.11, no.12, pp.2635 - 2647
- Indexed
- SCIE
SCOPUS
- Volume
- 11
- Number
- 12
- Start Page
- 2635
- End Page
- 2647
- ISSN
- 1556-6013
- Abstract
- Lately, electroencephalography (EEG)-based authentication has received considerable attention from the scientific community. However, the limited usability of wet EEG electrodes as well as low accuracy for large numbers of users have so far prevented this new technology to become commonplace. In this study a novel EEG-based authentication system is presented, which is based on the rapid serial visual presentation paradigm and uses a knowledge-based approach for authentication. Twenty-nine subjects' data were recorded and analyzed with wet EEG electrodes as well as dry ones. A true acceptance rate of 100% can be reached for all subjects with an average required login time of 13.5 s for wet and 27 s for dry electrodes. Average false acceptance rates for the dry electrode setup were estimated to be 3.33 x 10(-5).
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Collections - Graduate School > Department of Artificial Intelligence > 1. Journal Articles
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Related Researcher
- Lee, Seong Whan
- Department of Artificial Intelligence