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International Conference on Network-Based Information Systems

NBiS 2017: Advances in Network-Based Information Systems pp 529–538Cite as

Empirical Evaluation of Rhythm-Based Authentication Method for Mobile Devices

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Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 7))

Abstract

Mobile devices require a screen lock method for authentication. Although conventional screen locks are typically based on pattern, PIN code or password authentication, they are vulnerable to shoulder-surfing attacks and video recording attacks. To avoid such vulnerability, a rhythm-based authentication (RA) method that leverages the timing of screen taps has been proposed as an authentication factor. This method uses features, such as tap pressure, distance between taps, and tap timing, for authentication. However, this method requires a server for a user to be authenticated. In this paper, we propose an improved RA method that can be applied in a mobile device by using a Random Forest classifier. We conducted a series of experiments to clarify (i) importance of the features (ii) classification accuracy, and (iii) required number of taps. The proposed RA method was tested by 24 participants. After carefully choosing features, we show that when the number of taps is five, the accuracy is 94.16%, which is an improvement of 1.79%.

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Notes

  1. 1.

    https://upload.wikimedia.org/wikipedia/commons/5/50/Flohwalzer.pdf.

References

  1. Alzubaidi, A., Kalita, J.: Authentication of smartphone users using behavioral biometrics. IEEE Commun. Surv. Tutor. 18(3), 1998–2026 (2016)

    Article  Google Scholar 

  2. Araújo, L.C., Sucupira, L.H., 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)

    Article  MathSciNet  Google Scholar 

  3. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)

    Article  MATH  Google Scholar 

  4. Cao, K., Jain, A.K.: Hacking mobile phones using 2D printed fingerprints (2016). Accessed 27 Mar 2017

    Google Scholar 

  5. Chang, T., Peng, C., Tsai, C., Chen, Y., Cheng, P.: Personalized rhythm click based authentication system improvement using a statistical classifier. In: IEEE International Conference on Information Communication and Management (ICICM), pp. 39–43 (2012)

    Google Scholar 

  6. Chang, T.Y., Tsai, C.J., Yang, Y.J., Cheng, P.C.: User authentication using rhythm click characteristics for non-keyboard devices. In: International Conference on Asia Agriculture and Animal IPCBEE, pp 167–171 (2011)

    Google Scholar 

  7. Crawford, H.: Keystroke dynamics: characteristics and opportunities. In: Privacy Security and Trust (PST), pp. 205–212 (2010)

    Google Scholar 

  8. De Luca, A., Harbach, M., von Zezschwitz, E., Maurer, M.E., Slawik, B.E., Hussmann, H., Smith, M.: Now you see me, now you don’t: protecting smartphone authentication from shoulder surfers. In: ACM SIGCHI Conference on Human Factors in Computing Systems, pp. 2937–2946 (2014)

    Google Scholar 

  9. Goode, A.: Bring your own finger-how mobile is bringing biometrics to consumers. Biomet. Technol. Today 2014(5), 5–9 (2014)

    Article  Google Scholar 

  10. IPA: Minimum information security controls guide for organizations - IPA (2012). https://www.ipa.go.jp/security/keihatsu/shiori/management/01_guidebook_en.pdf. Accessed 21 Mar 2017

  11. Jain, A.K., Ross, A., Prabhakar, S.: An introduction to biometric recognition. IEEE Trans. Circuits Syst. Video Technol. 14(1), 4–20 (2004)

    Article  Google Scholar 

  12. Kita, Y., Aburada, K., Park, M., Okazaki, N.: Proposal of a puzzle authentication method with shoulder-surfing attack resistance and high-usability. IEICE Commun. Express 4(3), 95–98 (2015)

    Article  Google Scholar 

  13. Kita, Y., Kamizato, K., Park, M., Okazaki, N.: Proposal of rhythm authentication method using users classification by self-organizing map. In: The 18th International Conference on Network-Based Infomation System (NBiS2015) (2015)

    Google Scholar 

  14. Kohonen, T.: The self-organizing map. Neurocomputing 21(1), 1–6 (1998)

    Article  MATH  Google Scholar 

  15. Liaw, A., Wiener, M.: Classocatopm and regrwssion by randomforest. Newslett. R Proj. (R News) 2(3), 18–22 (2002)

    Google Scholar 

  16. Rogowski, M., Saeed, K., Rybnik, M., Tabedzki, M., Adamski, M.: User authentication for mobile devices. In: Computer Information Systems and Industrial Management, pp. 47–58 (2013)

    Google Scholar 

  17. Takada, T.: FakePointer: an authentication scheme for a better security against a peeping attack by a video camera. In: International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM) (2008)

    Google Scholar 

  18. Teh, P.S., Yue, S., Teoh, A.B.: Feature fusion approach on keystroke dynamics efficiency enhancement. Int. J. Cyber-Secur. Digit. Foren. (IJCSDF) 1(1), 20–31 (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Kanagawa Institute of Technology, 1030, Shimo-Ogino, Atsugi, Kanagawa, 243-0203, Japan

    Takahiro Hori & Mirang Park

  2. Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo, 192-0982, Japan

    Yoshihiro Kita

  3. Graduate School of Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa, 223-8522, Japan

    Kentaroh Toyoda

  4. University of Miyazaki, 1-1 Gakuenkibanadai-Nishi, Miyazaki, 889-2192, Japan

    Naonobu Okazaki

Authors
  1. Takahiro Hori
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  2. Yoshihiro Kita
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  3. Kentaroh Toyoda
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  4. Naonobu Okazaki
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  5. Mirang Park
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Corresponding author

Correspondence to Takahiro Hori .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Rissho University, Tokyo, Japan

    Tomoya Enokido

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

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© 2018 Springer International Publishing AG

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Hori, T., Kita, Y., Toyoda, K., Okazaki, N., Park, M. (2018). Empirical Evaluation of Rhythm-Based Authentication Method for Mobile Devices. In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_46

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  • DOI: https://doi.org/10.1007/978-3-319-65521-5_46

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65520-8

  • Online ISBN: 978-3-319-65521-5

  • eBook Packages: EngineeringEngineering (R0)

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