Abstract
Keystroke dynamics is a heavy field for researches; a lot of solutions have been proposed in this domain using different implementations usually based on Euclidean distance for measuring similarity between features vectors. However, the Euclidean distance method has a higher error equal rate comparing with other classification methods which makes the method less effective. Therefore, in the following paper, we propose our version of keystroke dynamics implementation based on K-NN, F-NN and Manhattan distance as classifiers to improve the authentication efficiency. The flight times and dwell time between keys are used in this study.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Mhenni, A., Rosenberger, C., Cherrier, E., Amara, N.E.B.: Keystroke template update with adapted thresholds. In: International Proceedings on Advanced Technologies for Signal and Image Processing (ATSIP), Tunisia (2016)
Alzubaidi, A., Kalita, J.: Authentication of smartphone users using behavioral biometrics. J. IEEE Commun. Surv. Tutor. 18, 1998–2026 (2015)
Morales, A., Fierrez, J., Tolosana, R., Ortega-Garcia, J., Galbally, J., Gomez-Barrero, M., Anjos, A., Marcel, S.: Keystroke biometrics ongoing competition. IEEE Access 4, 7736–7746 (2016)
Morales, A., Falanga, M., Fierrez, J., Sansone, C., OrtegaGarcia, J.: Keystroke dynamics recognition based on personal data: a comparative experimental evaluation implementing reproducible research. In: 7th International Proceedings on Biometrics: Theory, Applications and Systems, Arlington, USA, pp. 1–6 (2015)
Jaha, F., Kartit, A.: Pseudo code of two-factor authentication for BYOD. In: International Proceedings on Electrical and Information Technologies (ICEIT), IEEE Conferences, pp. 1– 7, Marocco (2017)
Forsen, G., Nelson, M., Staron Jr., R.: Personal attributes authentication techniques. Technical Report RADC-TR-77-333, Rome Air Development Center, October 1977
Ho, G.: Tapdynamics: strengthening user authentication on mobile phones with keystroke dynamics. Technical report, Stanford University (2014)
Kambourakis, G., Damopoulos, D., Papamartzivanos, D., Pavlidakis, E.: Introducing touchstroke: keystroke-based authentication system for smartphones. Secur. Commun. Netw. 9, 542–554 (2014)
Gascon, H., Uellenbeck, S., Wolf, C., Rieck, K.: Continuous authentication on mobile devices by analysis of typing motion behavior. In: Proceeding GI Conference “Sicherheit”, Germany, pp. 1–12 (2014)
Babaeizadeh, M., Bakhtiari, M., Aizaini Maarof, M.: Keystroke dynamic authentication in mobile cloud computing. Int. J. Comput. Appl. (0975 – 8887), 90(1) (2014)
Antal, M., Zsolt Szabo, L., Làszlo, I.: Keystroke dynamics on Android platform. Procedia Technol. 19(2015), 820–826 (2015)
Ali, M.L., Monaco, J.V., Tappert, C.C., Qiu, M.: Keystroke biometric systems for user authentication. J. Sig. Process. Syst. 86(2–3), 175–190 (2017)
Kaur, K., Virk, R.S.: Security system based on user authentication using keystroke dynamics. Int. J. Adv. Res. Comput. Commun. Eng. 2(5), 2111–2117 (2013)
Michael, O.B., Missah, Y.M.: Utilizing keystroke dynamics as an additional security measure to password security in computer web-based applications - a case study of UEW. Int. J. Comput. Appl. (0975 – 8887), 149(5) (2016)
Teh, P.S., Zhang, N., Teoh, A.B.J., Chen, K.: A survey on touch dynamics authentication in mobile devices. Comput. Secur. 59, 210–235 (2016)
Panasiuk, P., Dąbrowski, M., Saeed, K., Bocheńska-Włostowska, K.: On the comparison of the keystroke dynamics databases. In: Saeed, K., Snášel, V. (eds.) CISIM 2014. LNCS, vol. 8838, pp. 122–129. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45237-0_13
Patil, R.A., Renke, A.L.: Keystroke dynamics for user authentication and identification by using typing rhythm. Int. J. Comput. Appl. (0975 – 8887), 144(9) (2016)
Vinayak, R., Arora, K.: A survey of user authentication using keystroke dynamics. Int. J. Sci. Res. Eng. Technol. (IJSRET), 4(4) (2015)
Avasthi, S., Sanwal, T.: Biometric authentication techniques: a study on keystroke dynamics. Int. J. Sci. Eng. Appl. Sci. (IJSEAS), 2(1) (2016)
Nagargoje, Y.R., Lomte, S.S., Auti, R.A., Rokade, A.H.: Security using fusion of keystroke and mouse dynamics. Int. J. Sci. Res. Educ. 2(7), 1185–1194 (2014)
Zhong, Y., Deng, Y.: Recent advances in user authentication using keystroke dynamics. In: Science Gate Publishing, vol. 2, pp. 59–70 (2015)
Trojahn, M., Ortmeier, F.: Toward mobile authentication with keystroke dynamics on mobile phones and tablets. In: Advanced Information Networking and Applications Workshops (WAINA), pp. 697–702. IEEE (2013)
Ali, M.L., Monaco, J., Tappert, C., Qiu, M.: Authentication and identification methods used in keystroke biometric systems. In: IEEE International Symposium on Big Data Security on Cloud (Big Data Security 2015), pp. 1424–1429. IEEE (2015)
Trojahn, M., Arndt, F., Ortmeier, F.: Authentication with keystroke dynamics on touchscreen keypads—effect of different N-Graph combinations. In: 3rd International Proceedings on Mobile Services, Resources, and Users, pp. 114–119 (2013)
Bondada, M.B., Bhanu, S.: Analyzing user behavior using keystroke dynamics to protect cloud from Malicious insiders. In: International Proceedings on Cloud Computing in Emerging Markets (CCEM), pp. 1–8. IEEE (2014)
Xi, K., Tang, Y., Hu, J.: Correlation keystroke verification scheme for user access control in cloud computing environment. Comput. J. 54(10), 1632–1644 (2011). https://doi.org/10.1093/comjnl/bxr064
Giot, R., El-Abed, M., Rosenberger, C.: Web-based benchmark for keystroke dynamics biometric systems: a statistical analysis. In: 8th International Proceedings on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), pp. 11–15. IEEE (2012)
Alsultan, A., Warwick, K.: Keystroke dynamics authentication: a survey of free-text methods. Int. J. Comput. Sci. 10(4), 1–10 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Jaha, F., Kartit, A. (2018). Improving Implementation of Keystroke Dynamics Using K-NN and Manhattan Distance. In: Tabii, Y., Lazaar, M., Al Achhab, M., Enneya, N. (eds) Big Data, Cloud and Applications. BDCA 2018. Communications in Computer and Information Science, vol 872. Springer, Cham. https://doi.org/10.1007/978-3-319-96292-4_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-96292-4_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-96291-7
Online ISBN: 978-3-319-96292-4
eBook Packages: Computer ScienceComputer Science (R0)