Biometric Counter-Spoofing for Mobile Devices Using Gaze Information

  • Asad Ali
  • Nawal Alsufyani
  • Sanaul Hoque
  • Farzin DeraviEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10597)


With the rise in the use of biometric authentication on mobile devices, it is important to address the security vulnerability of spoofing attacks where an attacker using an artefact representing the biometric features of a genuine user attempts to subvert the system. In this paper, techniques for presentation attack detection are presented using gaze information with a focus on their applicability for use on mobile devices. Novel features that rely on directing the gaze of the user and establishing its behaviour are explored for detecting spoofing attempts. The attack scenarios considered in this work include the use of projected photos, 2D and 3D masks. The proposed features and the systems based on them were extensively evaluated using data captured from volunteers performing genuine and spoofing attempts. The results of the evaluations indicate that gaze-based features have the potential for discriminating between genuine attempts and imposter attacks on mobile devices.


Biometrics Spoofing Presentation attacks Mobile security Liveness detection 


  1. 1.
    Sun, L., Pan, G., Wu, Z., Lao, S.: Blinking-based live face detection using conditional random fields. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 252–260. Springer, Heidelberg (2007). doi: 10.1007/978-3-540-74549-5_27 CrossRefGoogle Scholar
  2. 2.
    Pan, G., Sun, L., Wu, Z., Lao, S.: Eyeblink-based anti-spoofing in face recognition from a generic webcamera. In: IEEE 11th International Conference on Computer Vision (ICCV), pp. 1–8 (2007)Google Scholar
  3. 3.
    Schwartz, W.R., Rocha, A., Pedrini, H.: Face spoofing detection through partial least squares and low-level descriptors. In: International Joint Conference on Biometrics (IJCB), pp. 1–8 (2011)Google Scholar
  4. 4.
    Chingovska, I., Anjos, A., Marcel, S.: On the effectiveness of local binary patterns in face anti-spoofing. In: Proceedings of IEEE BIOSIG, pp. 1–7 (2012)Google Scholar
  5. 5.
    Pinto, A., Schwartz, W.R., Pedrini, H., Rocha, A.: Using visual rhythms for detecting video-based facial spoof attacks. IEEE Trans. Inf. Forensics Secur. 10(5), 1025–1038 (2015)CrossRefGoogle Scholar
  6. 6.
    Maatta, J., Hadid, A., Pietikainen, M.: Face spoofing detection from single images using texture and local shape analysis. IET Biometrics 1(1), 3–10 (2012)CrossRefGoogle Scholar
  7. 7.
    Peixoto, B., Michelassi, C., Rocha, A.: Face liveness detection under bad illumination conditions. In: 18th IEEE International Conference on Image Processing, pp. 3557–3560 (2011)Google Scholar
  8. 8.
    Wen, D., Han, H., Jain, A.K.: Face spoof detection with image distortion analysis. IEEE Trans. Inf. Forensics Secur. 10(4), 746–761 (2015)CrossRefGoogle Scholar
  9. 9.
    Georghiades, A.S., Belhumeur, P.N., Kriegman, D.J.: From few to many: illumination cone models for face recognition under variable lighting and pose. IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 643–660 (2001)CrossRefGoogle Scholar
  10. 10.
    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
  11. 11.
    Lagorio, A., Tistarelli, M., Cadoni, M., Fookes, C., Sridharan, S.: Liveness detection based on 3d face shape analysis. In: International Workshop on Biometrics and Forensics (IWBF), pp. 1–4 (2013)Google Scholar
  12. 12.
    Wang, T., Yang, J., Lei, Z., Liao, S., Li, S.Z.: Face liveness detection using 3d structure recovered from a single camera. In: 2013 International Conference on Biometrics (ICB), pp. 1–6 (2013)Google Scholar
  13. 13.
    De Marsico, M., Galdi, C., Nappi, M., Riccio, D.: Firme: face and iris recognition for mobile engagement. Image Vis. Comput. 32(12), 1161–1172 (2014)CrossRefGoogle Scholar
  14. 14.
    Frischholz R.W., Werner, A.: Avoiding replay-attacks in a face recognition system using head-pose estimation. In: IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG), pp. 234–235 (2003)Google Scholar
  15. 15.
    Ali, A., Deravi, F., Hoque, S.: Liveness detection using gaze collinearity. In: 2012 Third International Conference on Emerging Security Technologies (EST), pp. 62–65 (2012)Google Scholar
  16. 16.
    Ali, A., Deravi, F., Hoque, S.: Spoofing attempt detection using gaze colocation. In: 2013 International Conference of the Biometrics Special Interest Group (BIOSIG), pp. 1–12 (2013)Google Scholar
  17. 17.
    Ali, A., Deravi, F., Hoque, S.: Directional sensitivity of gaze-collinearity features in liveness detection. In: 4th International Conference on Emerging Security Technologies (EST), pp. 8–11 (2013)Google Scholar
  18. 18.
    Singh, A.K., Joshi, P., Nandi, G.C.: Face recognition with liveness detection using eye and mouth movement. In: 2014 International Conference on Signal Propagation and Computer Technology (IC- SPCT), pp. 592–597 (2014)Google Scholar
  19. 19.
    Smith, D.F., Wiliem, A., Lovell, C.: Face recognition on consumer devices: reflections on replay attacks. IEEE Trans. Inf. Forensics Secur. 10(4), 736–745 (2015)CrossRefGoogle Scholar
  20. 20.
    Boehm, A., Chen, D., Frank, M., Huang, L., Kuo, C., Lolic, T., Martinovic, I., Song, D.: Safe: secure authentication with face and eyes. In: 2013 International Conference on Privacy and Security in Mobile Systems (PRISMS), pp. 1–8 (2013)Google Scholar
  21. 21.
    Cai, L., Huang, L., Liu, C.: Person-specific face spoofing detection for replay attack based on gaze estimation. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds.) Biometric Recognition. LNCS, vol. 9428, pp. 201–211. Springer, Cham (2015). doi: 10.1007/978-3-319-25417-3_25 CrossRefGoogle Scholar
  22. 22.
    Kollreider, K., Fronthaler, H., Bigun, J.: Evaluating liveness by face images and the structure tensor. In: 4th IEEE Workshop on Automatic Identification Advanced Technologies (AutoID 2005), pp. 75–80 (2005)Google Scholar
  23. 23.
    Ali, A., Hoque, S., Deravi, F.: Gaze stability for liveness detection. Pattern Anal. Applic. (2016). doi: 10.1007/s10044-016-0587-2
  24. 24.
    Asthana, A., Zafeiriou, S., Cheng, S., Pantic, M.: Incremental face alignment in the wild. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1859–1866 (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Engineering and Digital ArtsUniversity of KentCanterburyUK

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