High-Entropy Visual Identification for Touch Screen Devices

  • Nathaniel Wesley Filardo
  • Giuseppe Ateniese
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7232)

Abstract

We exhibit a system for improving the quality of user-derived keying material on touch-screen devices. We allow a device to recover previously generated, highly entropic data suitable for use as (part of) a strong secret key from a user’s act of identifying to the device. Our system uses visual cryptography [21], using no additional electronics and no memorization on the part of the user. Instead, we require the use of a transparency overlaid on the touch-screen. Our scheme is similar to the identification scheme of [22] but tailored for constrained, touch-screen displays.

Keywords

Secret Image Visual Cryptography Visual Secret Share Visual Cryptography Scheme Keystroke Dynamic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. 1.
    Abadi, M., Warinschi, B.: Password-Based Encryption Analyzed. In: Caires, L., Italiano, G.F., Monteiro, L., Palamidessi, C., Yung, M. (eds.) ICALP 2005. LNCS, vol. 3580, pp. 664–676. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Abeni, P., Baltatu, M., D’Alessandro, R.: User authentication based on face recognition with support vector machines. In: CRV 2006: Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision, p. 42. IEEE Computer Society (2006)Google Scholar
  3. 3.
    Ateniese, G., Blundo, C., De Santis, A., Stinson, D.R.: Visual cryptography for general access structures. Inf. Comput. 129(2), 86–106 (1996)MATHCrossRefGoogle Scholar
  4. 4.
    Ateniese, G., Blundo, C., Santis, A.D., Stinson, D.R.: Extended capabilities for visual cryptography. Theor. Comput. Sci. 250(1-2), 143–161 (2001)MATHCrossRefGoogle Scholar
  5. 5.
    Chang, C.C., Yu, T.X.: Sharing a secret gray image in multiple images. In: Proceedings of the First International Symposium on Cyber Worlds, pp. 230–237 (2002)Google Scholar
  6. 6.
    Cimato, S., De Prisco, R., De Santis, A.: Colored visual cryptography without color darkening. Theor. Comput. Sci. 374(1-3), 261–276 (2007)MATHCrossRefGoogle Scholar
  7. 7.
    Dhamija, R., Perrig, A.: Déjà vu: a user study using images for authentication. In: SSYM 2000: Proceedings of the 9th Conference on USENIX Security Symposium, p. 4. USENIX Association (2000)Google Scholar
  8. 8.
    Dodis, Y., Ostrovsky, R., Reyzin, L., Smith, A.: Fuzzy extractors: How to generate strong keys from biometrics and other noisy data. SIAM J. Comput. 38, 97–139 (2008)MathSciNetMATHCrossRefGoogle Scholar
  9. 9.
    Farzin, H., Abrishami-Moghaddam, H., Moin, M.S.: A novel retinal identification system. EURASIP Journal on Advances in Signal Processing, 10 (2008)Google Scholar
  10. 10.
    Fitts, P.M.: The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology 47(6), 381–391 (1954)CrossRefGoogle Scholar
  11. 11.
    Greveler, U.: VTANs - eine anwendung visueller kryptographie in der online-sicherheit. In: GI Jahrestagung (2) 2007, pp. 210–214 (2007)Google Scholar
  12. 12.
    Hick, W.E.: On the rate of gain of information. Quarterly Journal of Experimental Psychology (4), 11–26 (1952)Google Scholar
  13. 13.
    Hou, Y.C.: Visual cryptography for color images. Pattern Recognition 36(7), 1619 (2003)CrossRefGoogle Scholar
  14. 14.
    Jain, L., et al. (eds.): Intelligent Biometric Techniques in Fingerprint and Face Recognition. CRC Press (1999)Google Scholar
  15. 15.
    Jin, D., Yan, W.Q., Kankanhalli, M.S.: Progressive color visual cryptography. Journal of Electronic Imaging 14(3), 33019 (2005)CrossRefGoogle Scholar
  16. 16.
    Kim, M.R., Park, J.H., Zheng, Y.: Human-machine identification using visual cryptography. In: Proc. the 6th IEEE Int. Workshop on Intelligent Signal Processing and Communication Systems, pp. 178–182 (1998)Google Scholar
  17. 17.
    Laboratories, R.: Pkcs #5: Password-based cryptography standard, v2.0 (1999), ftp://ftp.rsasecurity.com/pub/pkcs/pkcs-5v2/pkcs5v2-0.pdf
  18. 18.
    Lenovo: Thinkvantage®  client security solution, http://www.pc.ibm.com/us/think/thinkvantagetech/security.html
  19. 19.
    Ltda., A.S.: Fingerauth password manager, http://www.fingerauth.com/
  20. 20.
    Mackenzie, S.I., Soukoreff, W.R.: Text entry for mobile computing: Models and methods, theory and practice. Human-Computer Interaction 17(2 & 3), 147–198 (2002)CrossRefGoogle Scholar
  21. 21.
    Naor, M., Shamir, A.: Visual cryptography. Tech. rep. (1994)Google Scholar
  22. 22.
    Naor, M., Pinkas, B.: Visual Authentication and Identification. In: Kaliski Jr., B.S. (ed.) CRYPTO 1997. LNCS, vol. 1294, pp. 322–336. Springer, Heidelberg (1997)Google Scholar
  23. 23.
  24. 24.
    Paul, N., Evans, D., Rubin, A.D., Wallach, D.S.: Authentication for remote voting. In: Workshop on Human-Computer Interaction and Security Systems (2003)Google Scholar
  25. 25.
    Pavaday, N., Soyjaudah, K.: A comparative study of secret code variants in terms of keystroke dynamics, pp. 133–140 (2008)Google Scholar
  26. 26.
    Admit One Security: Keystroke dynamics, http://www.biopassword.com/keystroke_dynamics_advantages.asp
  27. 27.
    Yang, C.N., Laih, C.S.: New colored visual secret sharing schemes. Des. Codes Cryptography 20(3), 325–336 (2000)MathSciNetMATHCrossRefGoogle Scholar
  28. 28.
    Youmaran, R., Adler, A., Miri, A.: An improved visual cryptography scheme for secret hiding. In: 23rd Biennial Symposium on Communications, pp. 340–343 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nathaniel Wesley Filardo
    • 1
  • Giuseppe Ateniese
    • 1
  1. 1.Computer Science DepartmentJohns Hopkins UniversityBaltimoreUSA

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