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Towards Secure Personal Device Unlock Using Stereo Camera Pan Shots

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Computer Aided Systems Theory - EUROCAST 2013 (EUROCAST 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8112))

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Abstract

Personal mobile devices hold sensitive data and can be used to access services with associated cost. For security reasons, most mobile platforms hence implement automatic device locking after a period of inactivity. Unlocking them using approaches like PIN, password or an unlock pattern is both problematic in terms of usability and potentially insecure, as it is prone to the shoulder surfing attack: an attacker watching the display during user authentication. Therefore, face unlock – using biometric face information for authentication – was developed as a more secure as well as more usable personal device unlock. Unfortunately, when using frontal face information only, authentication can still be circumvented by a photo attack: presenting a photo/video of the authorized person to the camera. We propose a variant of face unlock which is harder to circumvent by using all face information that is available during a 180° pan shot around the user’s head. Based on stereo vision, 2D and range images of the user’s head are recorded and classified along with sensor data of the device movement. We evaluate different classifiers for both grayscale 2D and range images and present our current results based on a new stereo vision face database.

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References

  1. Anjos, A., Marcel, S.: Counter-measures to photo attacks in face recognition: A public database and a baseline. In: 2011 International Joint Conference on Biometrics (IJCB), pp. 1–7 (2011)

    Google Scholar 

  2. Aviv, A.J., Gibson, K., Mossop, E., Blaze, M., Smith, J.M.: Smudge attacks on smartphone touch screens. In: Proceedings of the 4th USENIX Conference on Offensive Technologies, Berkeley, CA, USA, pp. 1–7 (2010)

    Google Scholar 

  3. Findling, R., Mayrhofer, R.: Towards face unlock: On the difficulty of reliably detecting faces on mobile phones. In: Proc. MoMM 2012: 10th International Conference on Advances in Mobile Computing and Multimedia, pp. 275–280. ACM (December 2012)

    Google Scholar 

  4. Freund, Y., Schapire, R.E.: A Decision Theoretic Generalization of On-Line Learning and an Application to Boosting. In: Vitányi, P.M.B. (ed.) Second European Conference on Computational Learning Theory, pp. 23–37 (1995)

    Google Scholar 

  5. Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: A statistical view of boosting. Annals of Statistics 28, 2000 (1998)

    MathSciNet  Google Scholar 

  6. Hsu, C.W., Chang, C.C., Lin, C.J.: A practical guide to support vector classification. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan (2003)

    Google Scholar 

  7. Konolige, K.: Small vision systems: Hardware and implementation. In: Shirai, Y., Hirose, S. (eds.) Robotics Research, pp. 203–212. Springer, London (1998)

    Chapter  Google Scholar 

  8. Lienhart, R., Maydt, J.: An extended set of haar-like features for rapid object detection. In: IEEE International Conference on Image Processing 2002, pp. 900–903 (2002)

    Google Scholar 

  9. Matthews, I., Baker, S.: Active appearance models revisited. Int. J. Comput. Vision 60(2), 135–164 (2004)

    Article  Google Scholar 

  10. Mitchell, T.M.: Machine Learning, 1st edn. McGraw-Hill, Inc., New York (1997)

    MATH  Google Scholar 

  11. Pan, G., Wu, Z., Sun, L.: Recent Advances in Face Recognition. In: Liveness Detection for Face Recognition, p. 236. InTech (2008)

    Google Scholar 

  12. Phillips, P.J.: Support vector machines applied to face recognition. In: Jordan, M.I., Kearns, M.J., Solla, S.A. (eds.) Neural Information Processing Systems, vol. 10, pp. 803–809 (1998)

    Google Scholar 

  13. Rother, C., Kolmogorov, V., Blake, A.: “grabcut”: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23(3), 309–314 (2004)

    Article  Google Scholar 

  14. Santana, M.C., Déniz-Suárez, O., Antón-Canalís, L., Lorenzo-Navarro, J.: Face and facial feature detection evaluation - performance evaluation of public domain haar detectors for face and facial feature detection. In: Ranchordas, A., Arajo, H. (eds.) International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, vol. 2, pp. 167–172 (2008)

    Google Scholar 

  15. Schaub, F., Deyhle, R., Weber, M.: Password entry usability and shoulder surfing susceptibility on different smartphone platforms. In: Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia, MUM 2012, pp. 13:1–13:10. ACM, New York (2012)

    Google Scholar 

  16. Segundo, M., Silva, L., Bellon, O., Queirolo, C.: Automatic face segmentation and facial landmark detection in range images. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 40(5), 1319–1330 (2010)

    Article  Google Scholar 

  17. Seibert, H.: Efficient segmentation of 3d face reconstructions. In: 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), pp. 31–34 (July 2012)

    Google Scholar 

  18. Tari, F., Ozok, A.A., Holden, S.H.: A comparison of perceived and real shoulder-surfing risks between alphanumeric and graphical passwords. In: Proceedings of the Second Symposium on Usable Privacy and Security, SOUPS 2006, pp. 56–66. ACM, New York (2006)

    Chapter  Google Scholar 

  19. Tronci, R., Muntoni, D., Fadda, G., Pili, M., Sirena, N., Murgia, G., Ristori, M., Roli, F.: Fusion of multiple clues for photo-attack detection in face recognition systems. In: International Joint Conference on Biometrics, pp. 1–6 (October 2011)

    Google Scholar 

  20. Turk, M., Pentland, A.: Eigenfaces for recognition. Cognitive Neuroscience 3(1), 71–86 (1991)

    Article  Google Scholar 

  21. Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 511–518 (2001)

    Google Scholar 

  22. von Zezschwitz, E., Koslow, A., De Luca, A., Hussmann, H.: Making graphic-based authentication secure against smudge attacks. In: Proceedings of the 2013 International Conference on Intelligent User Interfaces, pp. 277–286. ACM, New York (2013)

    Chapter  Google Scholar 

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Findling, R.D., Mayrhofer, R. (2013). Towards Secure Personal Device Unlock Using Stereo Camera Pan Shots. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2013. EUROCAST 2013. Lecture Notes in Computer Science, vol 8112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53862-9_53

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  • DOI: https://doi.org/10.1007/978-3-642-53862-9_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53861-2

  • Online ISBN: 978-3-642-53862-9

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