Authentication framework for security application developed using a pictorial P300 speller

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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.
Funding Information
  • not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors

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