Pattern Password Authentication Based on Touching Location

  • Orcan Alpar
  • Ondrej KrejcarEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9375)


Pattern passwords are one of the embedded authentication method of touchscreen devices, however it has some major drawbacks which briefly are identifiability and imitability. The password of the user is noticeable when entering the pattern due to shining circles. Therefore, what we put forward in this paper is a novel biometric implementation of a hidden system to pattern password authentication for increasing password security. As opposed to general research concept which extracts touch or keystroke durations, we focused on the touching coordinates calculated the distance of the line between the constant pattern node and the touched place as well as the angle. Using these inputs, we trained the neural network by Gauss-Newton and Levenberg-Marquardt algorithms and conducted the experiments with these trained classifiers.


Touchscreen Biometric authentication Gauss-Newton Levenberg-Marquardt Neural network 



This work and the contribution were supported by project “SP/2014/05 - Smart Solutions for Ubiquitous Computing Environments” from University of Hradec Kralove, Faculty of Informatics and Management.


  1. 1.
    Zheng, N., Bai, K., Huang, H., Wang, H.: You are how you touch: User verification on smartphones via tapping behaviors, Technical report, College of William and Mary (2012)Google Scholar
  2. 2.
    Kwapisz, J., Weiss, G., Moore, S.: Cell phone-based biometric identification. In: Proceedings IEEE International Conference on Biometrics: Theory Applications and Systems (2010)Google Scholar
  3. 3.
    Chang, T.Y., Tsai, C.J., Lin, J.H.: A graphical-based password keystroke dynamic authentication system for touch screen handheld mobile devices. J. Syst. Softw. 85(5), 1157–1165 (2012)CrossRefGoogle Scholar
  4. 4.
    Sae-Bae, N., Ahmed, K., Isbister, K., Memon, N.: Biometric-rich gestures: a novel approach to authentication on multi-touch devices. In: CHI 2012 Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems, New York (2012)Google Scholar
  5. 5.
    De Luca, A., Hang, A., Brudy, F., Lindner, C., Hussmann, H.: Touch me once and i know it’s you!: implicit authentication based on touch screen patterns. In: CHI 2012 Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems, New York (2012)Google Scholar
  6. 6.
    Angulo, J., Wästlund, E.: Exploring touch-screen biometrics for user identification on smart phones. In: Camenisch, J., Crispo, B., Fischer-Hübner, S., Leenes, R., Russello, G. (eds.) Privacy and Identity Management for Life. IFIP AICT, vol. 375, pp. 130–143. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Shahzad, M., Liu, A.X., Samuel, A.: Secure unlocking of mobile touch screen devices by simple gestures: you can see it but you can not do it. In: Proceedings of the 19th Annual International Conference on Mobile Computing & Networking. ACM (2013)Google Scholar
  8. 8.
    Schaub, F., Deyhle, R., Weber, M.: Password entry usability and shoulder surfing susceptibility on different smartphone platforms. In: Proceedings of Mobile and Ubiquitous Multimedia, 2012Google Scholar
  9. 9.
    Shahzad, M., Zahid, S., Farooq, M.: A hybrid GA-PSO fuzzy system for user identification on smart phones. In: ACM, Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, pp. 1617–1624 (2009)Google Scholar
  10. 10.
    Maiorana, E., Campisi, P., González-Carballo, N., Neri, A.: Keystroke dynamics authentication for mobile phones. In: Proceedings of the 2011 ACM Symposium on Applied Computing, pp. 21–26. ACM (2011)Google Scholar
  11. 11.
    Rao, M.K., Aparna, P., Akash, G.A., Mounica, K.: A graphical password authentication system for touch screen based devices. Int. J. Appl. Eng. Res. 9(18), 4917–4924 (2014)Google Scholar
  12. 12.
    Alpar, O.: Intelligent biometric pattern password authentication systems for touchscreens. Expert Syst. Appl. 42(17), 6286–6294 (2015)CrossRefGoogle Scholar
  13. 13.
    Alpar, O.: Keystroke recognition in user authentication using ANN based RGB histogram technique. Eng. Appl. Artif. Intell. 32, 213–217 (2014)CrossRefGoogle Scholar
  14. 14.
    Trojahn, M., Arndt, F., Ortmeier, F.: Authentication with time features for keystroke dynamics on touchscreens. In: De Decker, B., Dittmann, J., Kraetzer, C., Vielhauer, C. (eds.) CMS 2013. LNCS, vol. 8099, pp. 197–199. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  15. 15.
    Jeanjaitrong, N., Bhattarakosol, P.: Feasibility study on authentication based keystroke dynamic over touch-screen devices. In: 2013 13th International Symposium on Communications and Information Technologies (ISCIT), pp. 238–242. IEEE (2013)Google Scholar
  16. 16.
    Kambourakis, G., Damopoulos, D., Papamartzivanos, D., Pavlidakis, E.: Introducing touchstroke: keystroke‐based authentication system for smartphones. Secur. Commun. Netw. (2014). doi: 10.1002/sec.1061
  17. 17.
    Tasia, C.J., Chang, T.Y., Cheng, P.C., Lin, J.H.: Two novel biometric features in keystroke dynamics authentication systems for touch screen devices. Secur. Commun. Netw. 7(4), 750–758 (2014)CrossRefGoogle Scholar
  18. 18.
    Frank, M., Biedert, R., Ma, E., Martinovic, I., Song, D.: Touchalytics: On the applicability of touchscreen input as a behavioral biometric for continuous authentication. IEEE Trans. Inf. Forensics Secur. 8(1), 136–148 (2013)CrossRefGoogle Scholar
  19. 19.
    Sae-Bae, N., Memon, N., Isbister, K., Ahmed, K.: Multitouch gesture-based authentication. IEEE Trans. Inf. Forensics Secur. 9(4), 568–582 (2014)CrossRefGoogle Scholar
  20. 20.
    Zhao, X., Feng, T., Shi, W., Kakadiaris, I.: Mobile user authentication using statistical touch dynamics images. IEEE Trans. Inf. Forensics Secur. 9(11), 1780–1789 (2014)CrossRefGoogle Scholar
  21. 21.
    Rogowski, M., Saeed, K., Rybnik, M., Tabedzki, M., Adamski, M.: User authentication for mobile devices. In: Saeed, K., Chaki, R., Cortesi, A., Wierzchoń, S. (eds.) CISIM 2013. LNCS, vol. 8104, pp. 47–58. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  22. 22.
    Kang, P., Cho, S.: Keystroke dynamics-based user authentication using long and free text strings from various input devices. Inf. Sci. (2014).

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Faculty of Informatics and Management, Center for Basic and Applied ResearchUniversity of Hradec KraloveHradec KraloveCzech Republic

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