A High-Security EEG-Based Login System with RSVP Stimuli and Dry Electrodes

Yiyu Chen, Ayalneh Dessalegn Atnafu, Isabella Schlattner, Wendimagegn Tariku Weldtsadik, Myung Cheol Roh, Hyong Joong Kim, Seong Whan Lee, Benjamin Blankertz, Siamac Fazli

Research output: Contribution to journalArticle

42 Citations (Scopus)

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 languageEnglish
Article number7486116
Pages (from-to)2635-2647
Number of pages13
JournalIEEE Transactions on Information Forensics and Security
Volume11
Issue number12
DOIs
Publication statusPublished - 2016 Dec 1

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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

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