Towards a role-based authentication system based on SSVEP-P300 hybrid brain–computer interfacing.
Saved in:
| Title: | Towards a role-based authentication system based on SSVEP-P300 hybrid brain–computer interfacing. |
|---|---|
| Authors: | Rathi, Nikhil, Singla, Rajesh, Tiwari, Sheela |
| Source: | Behaviour & Information Technology. Dec2022, Vol. 41 Issue 15, p3301-3317. 17p. 2 Color Photographs, 3 Diagrams, 1 Chart, 5 Graphs. |
| Subjects: | College students, Brain-computer interfaces, Projective techniques, Security systems, Paradigms (Social sciences), T-test (Statistics), Data security, Descriptive statistics, Biometry, Visual evoked response |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
|
Full text is not displayed to guests.
Login for full access.
|
|
| 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. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 0144929X |
| DOI: | 10.1080/0144929X.2021.1979655 |
