Abstract
Lately, electroencephalography (EEG)-based auth-entication 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 $3.33×10-5.
Original language | English |
---|---|
Article number | 7486116 |
Pages (from-to) | 2635-2647 |
Number of pages | 13 |
Journal | IEEE Transactions on Information Forensics and Security |
Volume | 11 |
Issue number | 12 |
DOIs | |
Publication status | Published - Dec 1 2016 |
Externally published | Yes |
Fingerprint
Keywords
- authentication
- Biometrics
- brain-computer interfaces
- computer security
- dry electrodes
- EEG
- ERP
- RSVP
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications
Cite this
A High-Security EEG-Based Login System with RSVP Stimuli and Dry Electrodes. / Chen, Yiyu; Atnafu, Ayalneh Dessalegn; Schlattner, Isabella; Weldtsadik, Wendimagegn Tariku; Roh, Myung Cheol; Kim, Hyoung Joong; Lee, Seong Whan; Blankertz, Benjamin; Fazli, Siamac.
In: IEEE Transactions on Information Forensics and Security, Vol. 11, No. 12, 7486116, 01.12.2016, p. 2635-2647.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A High-Security EEG-Based Login System with RSVP Stimuli and Dry Electrodes
AU - Chen, Yiyu
AU - Atnafu, Ayalneh Dessalegn
AU - Schlattner, Isabella
AU - Weldtsadik, Wendimagegn Tariku
AU - Roh, Myung Cheol
AU - Kim, Hyoung Joong
AU - Lee, Seong Whan
AU - Blankertz, Benjamin
AU - Fazli, Siamac
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Lately, electroencephalography (EEG)-based auth-entication 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 $3.33×10-5.
AB - Lately, electroencephalography (EEG)-based auth-entication 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 $3.33×10-5.
KW - authentication
KW - Biometrics
KW - brain-computer interfaces
KW - computer security
KW - dry electrodes
KW - EEG
KW - ERP
KW - RSVP
UR - http://www.scopus.com/inward/record.url?scp=84991113044&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84991113044&partnerID=8YFLogxK
U2 - 10.1109/TIFS.2016.2577551
DO - 10.1109/TIFS.2016.2577551
M3 - Article
AN - SCOPUS:84991113044
VL - 11
SP - 2635
EP - 2647
JO - IEEE Transactions on Information Forensics and Security
JF - IEEE Transactions on Information Forensics and Security
SN - 1556-6013
IS - 12
M1 - 7486116
ER -