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A Hand Gesture-Based Method for Biometric Authentication

  • Satoru Imura
  • Hiroshi HosobeEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10901)

Abstract

With the spread of computers to ordinary people, computer security is becoming increasingly important. User authentication is one of the most important technologies for computer security. Although passwords are used in many personal computers, they are known to sometimes have problems. As an alternative to passwords, biometric authentication, such as fingerprint authentication and face recognition-based authentication, is becoming more widely used. In this paper, we propose a hand gesture-based method as a new kind of biometric authentication. It supports three-dimensional (3D) gestures that allow its user to move the user’s hand without touching an input device. Using the motions of fingertips and finger joints as biometric data, the method improves the performance of authentication. Also, we propose seven 3D gestures that can be classified into three types. We implemented the method by using a 3D motion sensor called the Leap Motion controller. We present the results of an experiment that we conducted with nine participants to evaluate the method. For all the gestures, the true acceptance rates were more than 90%, and the equal error rates were less than 4%.

Keywords

Biometric authentication Hand gesture Motion sensor 

Notes

Acknowledgment

This work was partly supported by JSPS KAKENHI Grant Number JP15KK0016.

References

  1. 1.
    Ataş, M.: Hand tremor based biometric recognition using Leap Motion device. IEEE Access 5, 23320–23326 (2017)CrossRefGoogle Scholar
  2. 2.
    Bača, M., Grd, P., Fotak, T.: Basic principles and trends in hand geometry and hand shape biometrics. In: New Trends and Developments in Biometrics, pp. 77–99. InTech (2012)Google Scholar
  3. 3.
    Chan, A., Halevi, T., Memon, N.: Leap motion controller for authentication via hand geometry and gestures. In: Tryfonas, T., Askoxylakis, I. (eds.) HAS 2015. LNCS, vol. 9190, pp. 13–22. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-20376-8_2CrossRefGoogle Scholar
  4. 4.
    Cherifi, F., Hemery, B., Giot, R., Pasquet, M., Rosenberger, C.: Performance evaluation of behavioral biometric systems. In: Behavioral Biometrics for Human Identification: Intelligent Applications, pp. 57–74. IGI Global (2009)Google Scholar
  5. 5.
    Clark, G.D., Lindqvist, J.: Engineering gesture-based authentication systems. IEEE Pervasive Comput. 14(1), 18–25 (2015)CrossRefGoogle Scholar
  6. 6.
    El-Abed, M., Charrier, C.: Evaluation of biometric systems. In: New Trends and Developments in Biometrics, pp. 149–169. InTech (2012)Google Scholar
  7. 7.
    Fong, S., Zhuang, Y., Fister, I., Fister Jr., I.: A biometric authentication model using hand gesture images. Biomed. Eng. Online 12(111), 1–18 (2013)Google Scholar
  8. 8.
    Guerra-Casanova, J., Sánchez-Ávila, C., Bailador, G., de Santos Sierra, A.: Authentication in mobile devices through hand gesture recognition. Int. J. Inf Secur. 11(2), 65–83 (2012)CrossRefGoogle Scholar
  9. 9.
    Imura, S., Hosobe, H.: Biometric authentication using the motion of a hand (poster). In: Proceedings of ACM SUI, p. 221 (2016)Google Scholar
  10. 10.
    Jain, A.K., Ross, A., Prabhakar, S.: A prototype hand geometry-based verification system. In: Proceedings of International Conference on Audio- and Video-Based Biometric Person Authentication (AVBPA), pp. 166–171 (1999)Google Scholar
  11. 11.
    Jain, A.K., Ross, A., Prabhakar, S.: An introduction to biometric recognition. IEEE Trans. Circ. Syst. Video Technol. 14(1), 4–20 (2004)CrossRefGoogle Scholar
  12. 12.
    Kholmatov, A., Yanikoglu, B.: Identity authentication using improved online signature verification method. Pattern Recogn. Lett. 26(15), 2400–2408 (2005)CrossRefGoogle Scholar
  13. 13.
    Kim, D., Dunphy, P., Briggs, P., Hook, J., Nicholson, J., Nicholson, J., Olivier, P.: Multi-touch authentication on tabletops. In: Proceedings of ACM CHI, pp. 1093–1102 (2010)Google Scholar
  14. 14.
    Leap Motion. Leap Motion for Mac and PC. https://www.leapmotion.com/product/desktop/
  15. 15.
    Mahfouza, A., Mahmouda, T.M., Eldinc, A.S.: A survey on behavioral biometric authentication on smartphones. J. Inf. Secur. Appl. 37, 28–37 (2017)Google Scholar
  16. 16.
    Sae-Bae, N., Ahmed, K., Isbister, K., Memon, N.: Biometric-rich gestures: a novel approach to authentication on multi-touch devices. In: Proceedings of ACM CHI, pp. 977–986 (2012)Google Scholar
  17. 17.
    Saritha, L.R., Thomas, D., Mohandas, N., Ramnath, P.: Behavioral biometric authentication using Leap Motion sensor. Int. J. Latest Trends Eng. Technol. 8(1), 643–649 (2017)Google Scholar
  18. 18.
    Shabtai, A., Fledel, Y., Kanonov, U.: Google Android: a comprehensive security assessment. IEEE Secur. Priv. 8(2), 35–44 (2010)CrossRefGoogle Scholar
  19. 19.
    Sherman, M., Clark, G., Yang, Y., Sugrim, S., Modig, A., Lindqvist, J., Oulasvirta, A., Roos, T.: User-generated free-form gestures for authentication: security and memorability. In: Proceedings of MobiSys, pp. 176–189. ACM (2014)Google Scholar
  20. 20.
    Sun, Z., Wang, Y., Qu, G., Zhou, Z.: A 3-D hand gesture signature based biometric authentication system for smartphones. Secur. Comm. Netw. 9(11), 1359–1373 (2016)CrossRefGoogle Scholar
  21. 21.
    Wayman, J., Jain, A., Maltoni, D., Maio, D.: An introduction to biometric authentication systems. In: Biometric Systems, pp. 1–20. Springer, London (2005)Google Scholar
  22. 22.
    Wayman, J.L.: Fundamentals of biometric authentication technologies. Int. J. Image Graph. 1(1), 93–113 (2001)CrossRefGoogle Scholar
  23. 23.
    Wong, A.M.H., Kang, D.-K.: Stationary hand gesture authentication using edit distance on finger pointing direction interval. Sci. Program. 2016(7427980), 1–15 (2016)Google Scholar
  24. 24.
    Xiao, G., Milanova, M., Xie, M.: Secure behavioral biometric authentication with Leap Motion. In: Proceedings of ISDFS, pp. 112–118. IEEE (2016)Google Scholar
  25. 25.
    Yampolskiy, R.V., Govindaraju, V.: Taxonomy of behavioural biometrics. In: Behavioral Biometrics for Human Identification: Intelligent Applications, pp. 1–43. IGI Global (2009)Google Scholar
  26. 26.
    Ye, G., Tang, Z., Fang, D., Chen, X., Kim, K.I., Taylor, B., Wang, Z.: Cracking Android pattern lock in five attempts. In: Proceedings of NDSS Internet Society (2017)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Computer and Information SciencesHosei UniversityTokyoJapan

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