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Towards a role-based authentication system based on SSVEP-P300 hybrid brain–computer interfacing

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  • Nikhil Rathi
  • Rajesh Singla
  • Sheela Tiwari

Abstract

Billion-dollar investment has been made globally in different industries, and hence, protection of organisational assets against theft or leakage of confidential information becomes a prime objective. Therefore, industries have to build their security system according to the job profile of workers. In this study, a pictorial hybrid brain–computer interface (hBCI) based 2 × 2 speller was proposed that combines P300 with steady-state-evoked potential (SSVEP) reactions to enhance the authentication system’s performance. Each run displays pictures of various objects at four corners of the screen where each location flickers and flashes simultaneously. Here, P300 and SSVEP stimulation are used in such a way that the position of the target picture is detected by SSVEP while the target picture is identified by P300 stimulus. The classification accuracies of hybrid and only P300 system are 97.63% and 94.61%, respectively, while the information transfer rates obtained were 70.34 and 30.26 bit/min, respectively.

Suggested Citation

  • Nikhil Rathi & Rajesh Singla & Sheela Tiwari, 2022. "Towards a role-based authentication system based on SSVEP-P300 hybrid brain–computer interfacing," Behaviour and Information Technology, Taylor & Francis Journals, vol. 41(15), pages 3301-3317, November.
    • Handle: RePEc:taf:tbitxx:v:41:y:2022:i:15:p:3301-3317
    DOI: 10.1080/0144929X.2021.1979655
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