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Authentication framework for security application developed using a pictorial P300 speller

Authentication framework for security application developed using a pictorial P300 speller With the recent advancement in the field of information technology, online frauds have also been increased and hence password-based systems are no more secure. Therefore need for a more reliable authentication system has been growing rapidly. This study focuses on a P300 based authentication system designing. The proposed study presents a new four-choice oddball paradigm where a conventional 6 × 6 character-based speller is replaced by a novel 2 × 2 pictorial speller. In this study, three classifiers were tested: Quadratic Discriminant Analysis (QDA), K-Nearest Neighbor (KNN), and Quadratic Support Vector Machine (QSVM). Out of these three, QDA performed better. The results showed that the designed visual stimuli obtained significantly higher accuracy (97%) and information transfer rates (37.14 bits/min) as compared to the conventional paradigm. The results also show that reduced matrix size and modified stimulus typically affects the accuracy and communication speed of a P300 based authentication system. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Brain-Computer Interfaces Taylor & Francis

Authentication framework for security application developed using a pictorial P300 speller

Brain-Computer Interfaces , Volume 7 (3-4): 20 – Oct 1, 2020

Authentication framework for security application developed using a pictorial P300 speller

Abstract

With the recent advancement in the field of information technology, online frauds have also been increased and hence password-based systems are no more secure. Therefore need for a more reliable authentication system has been growing rapidly. This study focuses on a P300 based authentication system designing. The proposed study presents a new four-choice oddball paradigm where a conventional 6 × 6 character-based speller is replaced by a novel 2 × 2 pictorial...
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Publisher
Taylor & Francis
Copyright
© 2020 Informa UK Limited, trading as Taylor & Francis Group
ISSN
2326-2621
eISSN
2326-263x
DOI
10.1080/2326263X.2020.1860520
Publisher site
See Article on Publisher Site

Abstract

With the recent advancement in the field of information technology, online frauds have also been increased and hence password-based systems are no more secure. Therefore need for a more reliable authentication system has been growing rapidly. This study focuses on a P300 based authentication system designing. The proposed study presents a new four-choice oddball paradigm where a conventional 6 × 6 character-based speller is replaced by a novel 2 × 2 pictorial speller. In this study, three classifiers were tested: Quadratic Discriminant Analysis (QDA), K-Nearest Neighbor (KNN), and Quadratic Support Vector Machine (QSVM). Out of these three, QDA performed better. The results showed that the designed visual stimuli obtained significantly higher accuracy (97%) and information transfer rates (37.14 bits/min) as compared to the conventional paradigm. The results also show that reduced matrix size and modified stimulus typically affects the accuracy and communication speed of a P300 based authentication system.

Journal

Brain-Computer InterfacesTaylor & Francis

Published: Oct 1, 2020

Keywords: P300; authentication; quadratic Discriminant Analysis; k-Nearest Neighbor; information Transfer Rate

References