Abstract
The article concerns the issues related to a computer user verification based on the analysis of a keyboard activity in a computer system. The research focuses on the analysis of a user’s continuous work in a computer system, which constitutes a type of a free-text analysis. To ensure a high level of a users’ data protection, an encryption of keystrokes was implemented. A new method of a computer user profiling based on encrypted keystrokes is introduced. Additionally, an attempt to an intrusion detection based on the \( k \)-NN classifier is performed.
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References
Kudłacik, P., Porwik, P.: A new approach to signature recognition using the fuzzy method. Pattern Anal. Appl. 17(3), 451–463 (2014). doi:10.1007/s10044-012-0283-9
Kudłacik, P., Porwik, P., Wesołowski, T.: Fuzzy Approach for Intrusion Detection Based on User’s Commands. Soft Computing, Springer, Berlin Heidelberg (2015), doi:10.1007/s00500-015-1669-6
Pałys, M., Doroz, R., Porwik, P.: On-line signature recognition based on an analysis of dynamic feature. In: IEEE International Conference on Biometrics and Kansei Engineering, pp. 103–107, Tokyo Metropolitan University Akihabara (2013)
Porwik, P., Doroz, R., Orczyk, T.: The k-NN classifier and self-adaptive Hotelling data reduction technique in handwritten signatures recognition. Pattern Analysis and Applications, doi:10.1007/s10044-014-0419-1
Wesołowski, T., Pałys, M., Kudłacik, P.: computer user verification based on mouse activity analysis. Stud. Comput. Intell. 598, 61–70 (2015). Springer International Publishing
Alsultan, A., Warwick, K.: Keystroke dynamics authentication: a survey of free-text methods. J. Comput. Sci. Issues 10(1) 1–10 (2013) (Issue 4)
Araujo, L.C.F., Sucupira Jr., L.H.R., Lizarraga, M.G., Ling, L.L., Yabu-Uti, J.B.T.: User authentication through typing biometrics features. IEEE Trans. Signal Process. 53(2) 851–855 (2005)
Banerjee, S.P., Woodard, D.L.: Biometric authentication and identification using keystroke dynamics: a survey. J. Pattern Recognit. Res. 7, 116–139 (2012)
Teh, P.S., Teoh, A.B.J., Yue, S.: A survey of keystroke dynamics biometrics. Sci. World J. 2013, Article ID: 408280, 24 pp. (2013) doi:10.1155/2013/408280
Zhong, Y., Deng, Y., Jain, A.K.: Keystroke dynamics for user authentication. In: IEEE Computer Society Conference, Computer Vision and Pattern Recognition Workshops, pp. 117–123 (2012), doi:10.1109/CVPRW.2012.6239225
Raiyn, J.: A survey of cyber attack detection strategies. Int. J. Secur. Its Appl. 8(1), 247–256 (2014)
Salem, M.B., Hershkop, S., Stolfo, S.J.: A survey of insider attack detection research. Adv. Inf. Secur. 39, 69–90, Springer US (2008)
Dowland, P.S., Singh, H., Furnell, S.M.: A preliminary investigation of user authentication using continuous keystroke analysis. In: The 8th Annual Working Conference on Information Security Management and Small Systems Security (2001)
Saha, J., Chaki, R.: An Approach to Classify Keystroke Patterns for Remote User Authentication. J. Med. Inf. Technol. 23, 141–148 (2014)
Lopatka, M., Peetz, M.: Vibration sensitive keystroke analysis. In: Proceedings of the 18th Annual Belgian-Dutch Conference on Machine Learning, pp. 75–80 (2009)
Killourhy, K.S., Maxion, R.A.: Comparing anomaly-detection algorithms for keystroke dynamics. In: International Conference on Dependable Systems and Networks (DSN-09), pp. 125–134. IEEE Computer Society Press (2009)
Rybnik, M., Tabedzki, M., Adamski, M., Saeed, K.: An exploration of keystroke dynamics authentication using non-fixed text of various length, In: IEEE International Conference on Biometrics and Kansei Engineering, pp. 245–250 (2013)
Tappert, C.C., Villiani, M., Cha, S.: Keystroke biometric identification and authentication on long-text input. In: Wang, L., Geng, X. (eds.) Behavioral Biometrics for Human Identification: Intelligent Applications, pp. 342–367 (2010), doi:10.4018/978-1-60566-725-6.ch016
Gunetti, D., Picardi, C., Ruffo, G.: Keystroke analysis of different languages: a case study. Adv. Intell. Data Anal. 3646, 133–144 (2005)
Foster, K.R., Koprowski, R., Skufca, J.D.: Machine learning, medical diagnosis, and biomedical engineering research—commentary. Biomed. Eng. Online 13, 94 (2014), doi:10.1186/1475-925X-13-94
Hu, J., Gingrich, D., Sentosa, A.: A K-nearest Neighbor Approach for User Authentication through Biometric Keystroke Dynamics. In: IEEE International Conference on Communications, pp. 1556–1560 (2008)
Filho, J.R.M., Freire, E.O.: On the equalization of keystroke timing histogram. Pattern Recognit. Lett. 27(13), 1440–1446 (2006)
Acknowledgments
The research described in this article has been partially supported from the funds of the project “DoktoRIS—Scholarship program for innovative Silesia” co-financed by the European Union under the European Social Fund.
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Wesołowski, T.E., Porwik, P. (2016). Computer User Profiling Based on Keystroke Analysis. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 395. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2650-5_1
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DOI: https://doi.org/10.1007/978-81-322-2650-5_1
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