A study on user-specific threshold configuration for keystroke dynamics in the context of adaptive biometric systems
Resumo
Keystroke dynamics is a biometric modality which can be applied as an additional authentication factor. Some studies have shown that keystroke data can change over time and, consequently, a biometric system which does not update the biometric reference acquired at enrolment time may face performance degradation. Adaptive biometric systems can be applied in this case and automatically adapt the biometric reference. An important aspect of these systems is how the thresholds are defined. Thresholds can be used for classification and to define which samples will be used for adaptation. A few studies have worked on how to adapt the thresholds. This paper studies user-specific thresholds for keystroke dynamics in adaptive biometric systems.Referências
AlQahtani, A. A. S., El-Awadi, Z., and Min, M. (2021). A survey on user authentication factors. In 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), pages 0323–0328.
Dias, T., ao Vitorino, J., Maia, E., Sousa, O., and Praça, I. (2023). KeyRecs: A keystroke dynamics and typing pattern recognition dataset. Data in Brief, 50:109509.
Giot, R., Dorizzi, B., and Rosenberger, C. (2011a). Analysis of template update strategies for keystroke dynamics. In 2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM), pages 21–28.
Giot, R., El-Abed, M., Hemery, B., and Rosenberger, C. (2011b). Unconstrained keystroke dynamics authentication with shared secret. Computers & Security, 30(6):427 – 445.
Giot, R., Rosenberger, C., and Dorizzi, B. (2012). Hybrid template update system for uni-modal biometric systems. In 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pages 1–7. IEEE.
Giot, R., Rosenberger, C., and Dorizzi, B. (2013). A new protocol to evaluate the resistance of template update systems against zero-effort attacks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
Hosseinzadeh, D. and Krishnan, S. (2008). Gaussian mixture modeling of keystroke patterns for biometric applications. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 38(6):816–826.
Jain, A. K., Nandakumar, K., and Ross, A. (2016). 50 years of biometric research: Accomplishments, challenges, and opportunities. Pattern Recog. Letters, 79:80 – 105.
Kang, P., Hwang, S.-s., and Cho, S. (2007). Continual retraining of keystroke dynamics based authenticator. In Lee, S.-W. and Li, S. Z., editors, Advances in Biometrics, pages 1203–1211, Berlin, Heidelberg. Springer Berlin Heidelberg.
Killourhy, K. S. and Maxion, R. A. (2009). Comparing anomaly-detection algorithms for keystroke dynamics. Proceedings of the International Conference on Dependable Systems and Networks, pages 125–134.
Magalhães, S. T., Revett, K., and Santos, H. M. D. (2005). Password secured sites - stepping forward with keystroke dynamics. In International Conference on Next Generation Web Services Practices (NWeSP’05), page 293–298.
Mhenni, A., Cherrier, E., Rosenberger, C., and Essoukri Ben Amara, N. (2019). Double serial adaptation mechanism for keystroke dynamics authentication based on a single password. Computers & Security, 83:151–166.
Mhenni, A., Rosenberger, C., Cherrier, E., and Ben Amara, N. E. (2016). Keystroke template update with adapted thresholds. In 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pages 483–488.
Precise Biometrics (2014). Understanding biometric performance evaluation.
Roy, S., Pradhan, J., Kumar, A., Adhikary, D. R. D., Roy, U., Sinha, D., and Pal, R. K. (2022). A systematic literature review on latest keystroke dynamics based models. IEEE Access, 10:92192–92236.
Ryu, R., Yeom, S., Herbert, D., and Dermoudy, J. (2023). The design and evaluation of adaptive biometric authentication systems: Current status, challenges and future direction. ICT Express, 9(6):1183–1197.
Sae-Bae, N. and Memon, N. (2022). Distinguishability of keystroke dynamic template. PLOS ONE, 17(1):1–17.
Dias, T., ao Vitorino, J., Maia, E., Sousa, O., and Praça, I. (2023). KeyRecs: A keystroke dynamics and typing pattern recognition dataset. Data in Brief, 50:109509.
Giot, R., Dorizzi, B., and Rosenberger, C. (2011a). Analysis of template update strategies for keystroke dynamics. In 2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM), pages 21–28.
Giot, R., El-Abed, M., Hemery, B., and Rosenberger, C. (2011b). Unconstrained keystroke dynamics authentication with shared secret. Computers & Security, 30(6):427 – 445.
Giot, R., Rosenberger, C., and Dorizzi, B. (2012). Hybrid template update system for uni-modal biometric systems. In 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pages 1–7. IEEE.
Giot, R., Rosenberger, C., and Dorizzi, B. (2013). A new protocol to evaluate the resistance of template update systems against zero-effort attacks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
Hosseinzadeh, D. and Krishnan, S. (2008). Gaussian mixture modeling of keystroke patterns for biometric applications. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 38(6):816–826.
Jain, A. K., Nandakumar, K., and Ross, A. (2016). 50 years of biometric research: Accomplishments, challenges, and opportunities. Pattern Recog. Letters, 79:80 – 105.
Kang, P., Hwang, S.-s., and Cho, S. (2007). Continual retraining of keystroke dynamics based authenticator. In Lee, S.-W. and Li, S. Z., editors, Advances in Biometrics, pages 1203–1211, Berlin, Heidelberg. Springer Berlin Heidelberg.
Killourhy, K. S. and Maxion, R. A. (2009). Comparing anomaly-detection algorithms for keystroke dynamics. Proceedings of the International Conference on Dependable Systems and Networks, pages 125–134.
Magalhães, S. T., Revett, K., and Santos, H. M. D. (2005). Password secured sites - stepping forward with keystroke dynamics. In International Conference on Next Generation Web Services Practices (NWeSP’05), page 293–298.
Mhenni, A., Cherrier, E., Rosenberger, C., and Essoukri Ben Amara, N. (2019). Double serial adaptation mechanism for keystroke dynamics authentication based on a single password. Computers & Security, 83:151–166.
Mhenni, A., Rosenberger, C., Cherrier, E., and Ben Amara, N. E. (2016). Keystroke template update with adapted thresholds. In 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pages 483–488.
Precise Biometrics (2014). Understanding biometric performance evaluation.
Roy, S., Pradhan, J., Kumar, A., Adhikary, D. R. D., Roy, U., Sinha, D., and Pal, R. K. (2022). A systematic literature review on latest keystroke dynamics based models. IEEE Access, 10:92192–92236.
Ryu, R., Yeom, S., Herbert, D., and Dermoudy, J. (2023). The design and evaluation of adaptive biometric authentication systems: Current status, challenges and future direction. ICT Express, 9(6):1183–1197.
Sae-Bae, N. and Memon, N. (2022). Distinguishability of keystroke dynamic template. PLOS ONE, 17(1):1–17.
Publicado
16/09/2024
Como Citar
PISANI, Paulo Henrique.
A study on user-specific threshold configuration for keystroke dynamics in the context of adaptive biometric systems. In: SIMPÓSIO BRASILEIRO DE SEGURANÇA DA INFORMAÇÃO E DE SISTEMAS COMPUTACIONAIS (SBSEG), 24. , 2024, São José dos Campos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 725-731.
DOI: https://doi.org/10.5753/sbseg.2024.241289.
