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Keystroke analysis of free text
Abstract
Keystroke dynamics can be useful to ascertain personal identity even after an authentication phase has been passed, provided that we are able to deal with the typing rhythms of free text, chosen and entered by users without any specific constraint. In this paper we present a method to compare typing samples of free text that can be used to verify personal identity. We have tested our technique with a wide set of experiments on 205 individuals, obtaining a False Alarm Rate of less than 5% and an Impostor Pass Rate of less than 0.005%. Different trade-offs are, however, possible. Our approach can rely on what is typed by people because of their normal job, and a few lines of text, even collected in different working sessions, are sufficient to reach a high level of accuracy, which improves proportionally to the amount of available information: As a consequence, we argue that our method can be useful in computer security as a complementary or alternative way to user authentication and as an aid to intrusion detection.
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Cited by
Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research
Zhang, Z., Hamadi, H. A., Damiani, E., Yeun, C. Y., & Taher, F. (2022) · IEEE Access · doi:10.1109/access.2022.3204051 · Cited by 450
HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users
Sitova, Z., Sedenka, J., Yang, Q., Peng, G., Zhou, G., Gasti, P., & Balagani, K. S. (2016) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2506542 · Cited by 398
Biometric Authentication and Identification Using Keystroke Dynamics: A Survey
Banerjee, S. P., & Woodard, D. (2012) · Journal of Pattern Recognition Research · doi:10.13176/11.427 · Cited by 369
Identifying emotional states using keystroke dynamics
Epp, C., Lippold, M., & Mandryk, R. L. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979046 · Cited by 364
A review of emotion recognition methods based on keystroke dynamics and mouse movements
Kolakowska, A. (2013) · 2013 6th International Conference on Human System Interactions (HSI) · doi:10.1109/hsi.2013.6577879 · Cited by 130
Metadata
- Authors
- Gunetti, D., & Picardi, C.
- Venue
- ACM Transactions on Information and System Security
- Published
- 2005-08
- Volume
- 8
- Issue
- 3
- Pages
- 312-347
- ISSN
- 1094-9224 (ISSN-L)
- 1557-7406
- OpenAlex
- W1983159352
- Cited by
- 474
- References
- 0
- FWCI
- 29.01
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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