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2017 | OriginalPaper | Buchkapitel

Bimodal Anti-Spoofing System for Mobile Security

verfasst von : Eugene Luckyanets, Aleksandr Melnikov, Oleg Kudashev, Sergey Novoselov, Galina Lavrentyeva

Erschienen in: Speech and Computer

Verlag: Springer International Publishing

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Abstract

Multi-modal biometric verification systems are in active development and show impressive performance nowadays. However, such systems need additional protection from spoofing attacks. In our paper we present full pipeline of anti-spoofing method (based on our previous work) for bimodal audiovisual verification system. This method allows to evaluate parameters of quality for a sequence of face images during a verification process. Based on this parameters it’s decided whether the data is suitable for processing by the standard method (fiducial points based audiovisual liveness detection, FALD). If the quality of data is not sufficient, then our system switches to a new algorithm (svm-based audiovisual liveness detection, SALD), which provides less protection quality, but is able to operate when FALD is unsuitable. To improve the quality of the FALD algorithm we have collected the special dataset. This dataset allows to get better reliability of the algorithm for searching of fiducial points on the user’s face image. Tests show that developed system can significantly improve the quality of anti-spoofing protection versus our previous work.

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Melnikov, A., Akhunzyanov, R., Kudashev, O., Luckyanets, E.: Audiovisual liveness detection. In: Murino, V., Puppo, E. (eds.) ICIAP 2015. LNCS, vol. 9280, pp. 643–652. Springer, Cham (2015). doi:10.1007/978-3-319-23234-8_59 CrossRef

Chakraborty, S., Das, D.: An overview of face liveness detection. arXiv preprint arXiv:1405.2227 (2014)

Das, D., Chakraborty, S.: Face liveness detection based on frequency and microtexture analysis. In: 2014 International Conference on Advances in Engineering and Technology Research (ICAETR), pp. 1–4. IEEE (2014)

Maatta, J., Hadid, A., Pietikainen, M.: Face spoofing detection from single images using micro-texture analysis. In: 2011 International Joint Conference on Biometrics (IJCB), pp. 1–7. IEEE (2011)

M\(\ddot{a}\ddot{a}\)tt\(\ddot{a}\), J., Hadid, A., Pietik\(\ddot{a}\)inen, M.: Face spoofing detection from single images using texture and local shape analysis. IET biometrics 1(1), 3–10 (2012)

Kim, G., Eum, S., Suhr, J.K., Kim, D.I., Park, K.R., Kim, J.: Face liveness detection based on texture and frequency analyses. In: 2012 5th IAPR International Conference on Biometrics (ICB), pp. 67–72. IEEE (2012)

Yang, L.: Face liveness detection by focusing on frontal faces and image backgrounds. In: 2014 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), pp. 93–97. IEEE (2014)

Kim, S., Yu, S., Kim, K., Ban, Y., Lee, S.: Face liveness detection using variable focusing. In: 2013 International Conference on Biometrics (ICB), pp. 1–6. IEEE (2013)

Ali, A., Deravi, F., Hoque, S.: Liveness detection using gaze collinearity. In: 2012 Third International Conference on Emerging Security Technologies (EST), pp. 62–65. IEEE (2012)

10.

Bao, W., Li, H., Li, N., Jiang, W.: A liveness detection method for face recognition based on optical flow field. In: International Conference on Image Analysis and Signal Processing, IASP 2009, pp. 233–236. IEEE (2009)

11.

Kollreider, K., Fronthaler, H., Bigun, J.: Evaluating liveness by face images and the structure tensor. In: Fourth IEEE Workshop on Automatic Identification Advanced Technologies 2005, pp. 75–80. IEEE (2005)

12.

Kollreider, K., Fronthaler, H., Bigun, J.: Non-intrusive liveness detection by face images. Image Vis. Comput. 27(3), 233–244 (2009)CrossRef

13.

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 CrossRef

14.

Lagorio, A., Tistarelli, M., Cadoni, M., Fookes, C., Sridharan, S.: Liveness detection based on 3D face shape analysis. In: 2013 International Workshop on Biometrics and Forensics (IWBF), pp. 1–4. IEEE (2013)

15.

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. IEEE (2013)

16.

Tan, X., Li, Y., Liu, J., Jiang, L.: Face liveness detection from a single image with sparse low rank bilinear discriminative model. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6316, pp. 504–517. Springer, Heidelberg (2010). doi:10.1007/978-3-642-15567-3_37 CrossRef

17.

Peixoto, B., Michelassi, C., Rocha, A.: Face liveness detection under bad illumination conditions. In: 2011 18th IEEE International Conference on Image Processing (ICIP), pp. 3557–3560. IEEE (2011)

18.

Yan, J., Zhang, Z., Lei, Z., Yi, D., Li, S.Z.: Face liveness detection by exploring multiple scenic clues. In: 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV), pp. 188–193. IEEE (2012)

19.

Pan, G., Sun, L., Wu, Z., Wang, Y.: Monocular camera-based face liveness detection by combining eyeblink and scene context. Telecommun. Syst. 47(3–4), 215–225 (2011)CrossRef

20.

Chetty, G., Wagner, M.: Automated lip feature extraction for liveness verification in audio-video authentication. In: Proceedings of Image and Vision Computing, pp. 17–22 (2004)

21.

Kollreider, K., Fronthaler, H., Faraj, M.I., Bigun, J.: Real-time face detection and motion analysis with application in “liveness” assessment. IEEE Trans. Inf. Forensics Secur. 2(3), 548–558 (2007)CrossRef

22.

Komulainen, J., Hadid, A., Pietikainen, M.: Context based face anti-spoofing. In: 2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 1–8. IEEE (2013)

23.

Shchemelinin, V., Topchina, M., Simonchik, K.: Vulnerability of voice verification systems to spoofing attacks by TTS voices based on automatically labeled telephone speech. In: Ronzhin, A., Potapova, R., Delic, V. (eds.) SPECOM 2014. LNCS (LNAI), vol. 8773, pp. 475–481. Springer, Cham (2014). doi:10.1007/978-3-319-11581-8_59

24.

Kinnunen, T., Wu, Z.Z., Lee, K.A., Sedlak, F., Chng, E.S., Li, H.: Vulnerability of speaker verification systems against voice conversion spoofing attacks: the case of telephone speech. In: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4401–4404, March 2012

25.

Novoselov, S., Pekhovsky, T., Shulipa, A., Sholokhov, A.: Text-dependent GMM-JFA system for password based speaker verification. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 729–737. IEEE (2014)

26.

Shchemelinin, V., Simonchik, K.: Study of voice verification system tolerance to spoofing attacks using a text-to-speech system. J. Instrum. Eng. 57(2), 84–88 (2014) (in Russian). ITMO University

27.

Marcel, S., Nixon, M.S., Li, S.Z.: Handbook of Biometric Anti-Spoofing. Springer, London (2014)CrossRef

28.

Wu, Z., Evans, N., Kinnunen, T., Yamagishi, J., Alegre, F., Li, H.: Spoofing and countermeasures for speaker verification: A survey. Speech Commun. 66, 130–153 (2015)CrossRef

29.

Novoselov, S., Kozlov, A., Lavrentyeva, G., Simonchik, K., Shchemelinin, V.: STC anti-spoofing systems for the asvspoof 2015 challenge. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5475–5479. IEEE (2016)

30.

Slaney, M., Covell, M.: Facesync: A linear operator for measuring synchronization of video facial images and audio tracks. In: NIPS, pp. 814–820 (2000)

31.

Chetty, G., Wagner, M.: Multi-level liveness verification for face-voice biometric authentication. In: 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, pp. 1–6. IEEE (2006)

32.

Çeting\(\ddot{u}\)l, H.E., Erzin, E., Yemez, Y., Tekalp, A.M.: Multimodal speaker/speech recognition using lip motion, lip texture and audio. Signal Process. 86(12), 3549–3558 (2006)

33.

Dean, D., Sridharan, S.: Dynamic visual features for audio-visual speaker verification. Comput. Speech Lang. 24(2), 136–149 (2010)CrossRef

34.

Baltrusaitis, T., Robinson, P., Morency, L.: 3d constrained local model for rigid and non-rigid facial tracking. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2610–2617. IEEE (2012)

35.

Cooke, M., Barker, J., Cunningham, S., Shao, X.: An audio-visual corpus for speech perception and automatic speech recognition. J. Acoust. Soc. Am. 120(5), 2421–2424 (2006)CrossRef

Titel: Bimodal Anti-Spoofing System for Mobile Security
verfasst von: Eugene Luckyanets
Aleksandr Melnikov
Oleg Kudashev
Sergey Novoselov
Galina Lavrentyeva
Verlag: Springer International Publishing
Buch: Speech and Computer
Print ISBN: 978-3-319-66428-6

Electronic ISBN: 978-3-319-66429-3

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-66429-3_20

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