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 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.

KEYWORDS:

• P300
• authentication
• quadratic Discriminant Analysis
• k-Nearest Neighbor
• information Transfer Rate

Acknowledgments

The authors would like to thank the subjects for participating in this experiment.

Disclosure statement

The authors declare that they have no competing interests.

Ethics approval and consent to participate

Experiments on human subjects had conducted with the ethical approval of the ethics committee of the institute

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.