Secure User Authentication on Smartphones via Sensor and Face Recognition on Short Video Clips

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10232)


Smartphones play a key role in our daily life, they can replace our watch, calendar, and mail box but also our credit card, house keys and in the near future our identity documents. Their increasing use in storing sensitive information, has raised the need to protect users and their data through secure authentication protocols. The main achievement of this work is to make the smartphone not only the cause of the problem but also part of the solution. Here, the Sensor Pattern Noise of the smartphone embedded camera and the HOG features of the user’s face are combined for a double check of user identity.


SOCRatES Video SPN PRNU Face recognition HOG features Smartphone 


  1. 1.
    Galdi, C., Nappi, M., Dugelay, J.-L.: Multimodal authentication on smartphones: combining iris and sensor recognition for a double check of user identity. Patt. Recogn. Lett. Part 2, 82, 144–153 (2016). ISSN: 0167-8655
  2. 2.
    Galdi, C., Nappi, M., Dugelay, J.-L.: Combining hardwaremetry and biometry for human authentication via smartphones. In: Murino, V., Puppo, E. (eds.) ICIAP 2015. LNCS, vol. 9280, pp. 406–416. Springer, Cham (2015). doi: 10.1007/978-3-319-23234-8_38 CrossRefGoogle Scholar
  3. 3.
    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
  4. 4.
    Lukáš, J., Fridrich, J., Goljan, M.: Digital camera identification from sensor pattern noise. IEEE Trans. Inf. Forensics Secur. 1(2), 205–214 (2006)CrossRefGoogle Scholar
  5. 5.
    Goljan, M., Fridrich, J., Filler, T.: Large scale test of sensor fingerprint camera identification. In: Memon, N.D., Delp, E.J., Wong, P.W., Dittmann, J. (eds.) Proceedings of SPIE. Electronic Imaging, Media Forensics and Security XI, vol. 7254, pp. 0I-01–0I-12, January 2009Google Scholar
  6. 6.
    Li, C.T.: Source camera identification using enhanced sensor pattern noise. IEEE Trans. Inf. Forensics Secur. 5(2), 280–287 (2010)CrossRefGoogle Scholar
  7. 7.
    Chuang, W.H., Su, H., Wu, M.: Exploring compression effects for improved source camera identification using strongly compressed video. In: 2011 18th IEEE International Conference on Image Processing, Brussels, pp. 1953–1956 (2011). doi: 10.1109/ICIP.2011.6115855
  8. 8.
    Chen, M., Fridrich, J., Goljan, M., Lukáš, J.: Source digital camcorder identification using sensor photo response non-uniformity. In: Electronic Imaging, p. 65051G. International Society for Optics and Photonics (2007)Google Scholar
  9. 9.
    Van Houten, W., Geradts, Z.: Using sensor noise to identify low resolution compressed videos from Youtube. In: Geradts, Z.J.M.H., Franke, K.Y., Veenman, C.J. (eds.) IWCF 2009. LNCS, vol. 5718, pp. 104–115. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-03521-0_10 CrossRefGoogle Scholar
  10. 10.
    Taspinar, S., Mohanty, M., Memon, N.: Source camera attribution using stabilized video. In: 2016 IEEE International Workshop on Information Forensics and Security (WIFS), Abu Dhabi, pp. 1–6 (2016). doi: 10.1109/WIFS.2016.7823918
  11. 11.
    Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 886–893, June 2005Google Scholar
  12. 12.
    Viola, P., Michael, J.J.: 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
  13. 13.
    Galdi, C., Hartung, F., Dugelay, J.-L.: Videos versus still images: asymmetric sensor pattern noise comparison on mobile phones. In: Electronic Imaging (2017)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.EURECOMSophia AntipolisFrance
  2. 2.Università degli Studi di SalernoFiscianoItaly

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