A novel algorithm to model the neuromuscular system from the eye to fingers to authenticate individuals through a typing process
Author:
Publisher
Springer Science and Business Media LLC
Subject
Human-Computer Interaction,Economics, Econometrics and Finance (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s10660-022-09594-0.pdf
Reference43 articles.
1. Salem, A., & Obaidat, M. S. (2019). A novel security scheme for behavioral authentication systems based on keystroke dynamics. Security and Privacy, 2(2), e64. https://doi.org/10.1002/spy2.64
2. Monaro, M., Galante, C., Spolaor, R., Li, Q. Q., Gamberini, L., Conti, M., & Sartori, G. (2018). Covert lie detection using keyboard dynamics. Scientific Reports, 8(1), https://doi.org/10.1038/s41598-018-20462-6
3. ÇEKER, H. (2017). Keystroke dynamics for enhanced user recognition in active authentication
4. Dwivedi, C., Kalra, D., Naidu, D., & Aggarwal, S. (2018). Keystroke dynamics based biometric authentication: A hybrid classifier approach. 2018 IEEE Symposium Series on Computational Intelligence (SSCI). Published. https://doi.org/10.1109/ssci.2018.8628852
5. Alshanketi, F., Traore, I., & Ahmed, A. A. (2016). Improving Performance and Usability in Mobile Keystroke Dynamic Biometric Authentication. 2016 IEEE Security and Privacy Workshops (SPW). Published. https://doi.org/10.1109/spw.2016.12
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