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Three-dimensional and two-and-a-half-dimensional face recognition spoofing using three-dimensional printed models

Three-dimensional and two-and-a-half-dimensional face recognition spoofing using three-dimensional printed models

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The vulnerability of biometric systems to external attacks using a physical artefact in order to impersonate the legitimate user has become a major concern over the last decade. Such a threat, commonly known as ‘spoofing’, poses a serious risk to the integrity of biometric systems. The usual low-complexity and low-cost characteristics of these attacks make them accessible to the general public, rendering each user a potential intruder. The present study addresses the spoofing issue analysing the feasibility to perform low-cost attacks with self-manufactured three-dimensional (3D) printed models to 2.5D and 3D face recognition systems. A new database with 2D, 2.5D and 3D real and fake data from 26 subjects was acquired for the experiments. Results showed the high vulnerability of the three tested systems, including a commercial solution, to the attacks.

References

    1. 1)
      • 1. Thalheim, L., Krissler, J.: ‘Body check: biometric access protection devices and their programs put to the test’. ct magazine, November 2002, pp. 114121.
    2. 2)
      • 2. Matsumoto, T., Matsumoto, H., Yamada, K., Hoshino, S.: ‘Impact of artificial gummy fingers on fingerprint systems’. Proc. SPIE Optical Security and Counterfeit Deterrence Techniques IV, 2002, vol. 4677, pp. 275289.
    3. 3)
      • 3. Matsumoto, T.: ‘Artificial irises: importance of vulnerability analysis’. Proc. Asian Biometrics Workshop (AWB), 2004.
    4. 4)
      • 4. Marasco, E.: ‘Secure multibiometric systems’. PhD dissertation, University of Naples Federico II, 2010.
    5. 5)
      • 5. Galbally, J.: ‘Vulnerabilities and attack protection in security systems based on biometric recognition’. PhD dissertation, Universidad Autonoma de Madrid, 2009.
    6. 6)
      • 6. Coli, P.: ‘Vitality detection in personal authentication systems using fingerprints’. PhD dissertation, Universita di Cagliari, 2008.
    7. 7)
      • 7. Marcel, S., Nixon, M., Li, S.Z. (Eds.): ‘Handbook of biometric anti-spoofing: trusted biometrics under spoofing attacks’ (Springer, London2014).
    8. 8)
      • 8. ISO/IEC WD 30107. Information Technology – Biometrics – Presentation Attack Detection, ISO/IEC Std., 2016, under development.
    9. 9)
      • 9. TABULA RASA: ‘Trusted biometrics under spoofing attacks’, 2010. Available at http://www.tabularasa-euproject.org/.
    10. 10)
      • 10. IEEE Int. Conf. on Acoustics Speech and Signal Processing (ICASSP). IEEE, 2013. Available at http://www.icassp2013.com/SpecialSessions.asp.
    11. 11)
      • 11. Annual Conf. of the Int. Speech Communication Association (INTERSPEECH), 2013.
    12. 12)
      • 12. Chingovska, I., Yang, J., Lei, Z., et al: ‘The 2nd competition on counter measures to 2D face spoofing attacks’. Proc. IAPR Int. Conf. on Biometrics (ICB), 2013.
    13. 13)
      • 13. Ghiani, L., Mura, V., Tocco, S., Marcialis, G.L., Roli, F.: ‘LivDet 2013 fingerprint liveness detection competition 2013’. Proc. IAPR Int. Conf. on Biometrics (ICB), 2013.
    14. 14)
      • 14. Clarkson University: ‘Livdet-iris 2013: Liveness detection-iris competition 2013’, 2013. Available at http://www.people.clarkson.edu/projects/biosal/iris/.
    15. 15)
      • 15. The Guardian: ‘iPhone 5S fingerprint sensor hacked by Germany's chaos computer club’, 2013, Available at http://www.theguardian.com/technology/2013/sep/22/apple-iphone-fingerprint-scanner-hacked.
    16. 16)
      • 16. Sky News: ‘Fake fingers fool hospital clock-in scanner’, 2013, Available at http://www.news.sky.com/story/1063956/fake-fingers-fool-hospital-clock-in-scanner.
    17. 17)
      • 17. The CNN: ‘Man in disguise boards international flight’, 2010, Available at http://www.edition.cnn.com/2010/WORLD/americas/11/04/canada-disguised-passenger/.
    18. 18)
      • 18. Kollreider, K., Fronthaler, H., Bigun, J.: ‘Evaluating liveness by face images and the structure tensor’. Proc. IEEE Workshop on Automatic Identification Advanced Technologies (AutoID), 2005, pp. 7580.
    19. 19)
    20. 20)
      • 20. Kose, N., Dugelay, J.-L.: ‘On the vulnerability of face recognition systems to spoofing mask attacks’. Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2013.
    21. 21)
      • 21. Tan, X., Li, Y., Liu, J., Jiang, L.: ‘Face liveness detection from a single image with sparse low rank bilinear discriminative model’. Proc. European Conf. on Computer Vision (ECCV), ser. LNCS 6316, 2010, pp. 504517.
    22. 22)
      • 22. Zhiwei, Z., Yan, J., Liu, S., Lei, Z., Yi, D., Li, S.Z.: ‘A face antispoofing database with diverse attacks’. Proc. IAPR Int. Conf. on Biometrics (ICB), 2012, pp. 2631.
    23. 23)
      • 23. Anjos, A., Marcel, S.: ‘Counter-measures to photo attacks in face recognition: a public database and a baseline’. Proc. IEEE Int. Joint Conf. on Biometrics (IJCB), 2011.
    24. 24)
      • 24. Arora, S.S., Cao, K., Jain, A.K., Paulter, N.G.: ‘3D fingerprint phantoms’. Proc. IEEE Int. Conf. on Pattern Recognition (ICPR), 2014.
    25. 25)
      • 25. Aggarwal, G., Biswas, S., Flynn, P.J., Bowyer, K.W.: ‘A sparse representation approach to face matching across plastic surgery’. Proc. Workshop on the Applications of Computer Vision (WACV), 2012, pp. 113119.
    26. 26)
    27. 27)
      • 27. Sun, Y., Tistarelli, M., Maltoni, D.: ‘Structural similarity based image quality map for face recognition across plastic surgery’. Proc. IEEE Conf. on Biometrics: Theory, Applications and Systems (BTAS), 2013.
    28. 28)
    29. 29)
      • 29. Dantcheva, A., Chen, C., Ross, A.: ‘Can facial cosmetics affect the matching accuracy of face recognition systems?’. Proc. IEEE Int. Conf. on Biometrics: Theory, Applications and Systems (BTAS), 2013, pp. 391398.
    30. 30)
      • 30. Tabula Rasa: ‘Tabula rasa spoofing challenge’, 2013. Available at http://www.tabularasa-euproject.org/evaluations/tabula-rasa-spoofing-challenge-2013.
    31. 31)
      • 31. Li, Y., Xu, K., Yan, Q., Li, Y., Deng, R.: ‘Understanding OSN-based facial disclosure against face authentication systems’. Proc. ACM Asia Symp. on Information, Computer and Communications Security (ASIACCS), 2014, pp. 413424.
    32. 32)
      • 32. Duc, N.M., Minh, B.Q.: ‘Your face is not your password: face authentication bypassing lenovo-asus-toshiba’. Black Hat USA, 2009.
    33. 33)
      • 33. Chingovska, I., Anjos, A., Marcel, S.: ‘On the effectiveness of local binary patterns in face anti-spoofing’. Proc. IEEE Int. Conf. of the Biometrics Special Interest Group (BIOSIG), 2012, pp. 17.
    34. 34)
    35. 35)
      • 35. Erdogmus, N., Marcel, S.: ‘Spoofing in 2D face recognition with 3D masks and anti-spoofing with Kinect’. Proc. IEEE Biometrics: Theory, Applications and Systems (BTAS), 2013.
    36. 36)
      • 36. Erdogmus, N., Marcel, S.: ‘Spoofing 2D face recognition systems with 3D masks’. Proc. Int. Conf. of the Biometrics Special Interest Group (BIOSIG), 2013.
    37. 37)
      • 37. Peixoto, B., Michelassi, C., Rocha, A.: ‘Face liveness detection under bad illumination conditions’. Proc. IEEE Int. Conf. on Image Processing (ICIP), 2011, pp. 35573560.
    38. 38)
      • 38. Vijayan, V., Bowyer, K.W., Flynn, P.J., et al: ‘Twins 3D face recognition challenge’. Proc. IEEE Int. Joint Conf. on Biometrics (IJCB), 2011.
    39. 39)
      • 39. Phillips, P.J., Flynn, P.J., Bowyer, K.W., et al: ‘Distinguishing identical twins by face recognition’. Proc. IEEE Int. Conf. on Automatic Face and Gesture Recognition and Workshops (FG), 2011, pp. 185192.
    40. 40)
      • 40. Klare, B., Paulino, A.A., Jain, A.K.: ‘Analysis of facial features in identical twins’. Proc. IEEE Int. Joint Conf. on Biometrics (IJCB), 2011.
    41. 41)
      • 41. Sun, Z., Paulino, A.A., Feng, J., Chai, Z., Tan, T., Jain, A.K.: ‘A study of multibiometric traits of identical twins’. Proc. SPIE Biometric Technology for Human Identification (BTHI), 2010.
    42. 42)
      • 42. BEAT: ‘BEAT: biometrics evaluation and testing’, 2012. Available at http://www.beat-eu.org/.
    43. 43)
      • 43. Barnsley, M.F.: ‘Fractals everywhere’. Morgan Kaufmann, 1993, ch. Metric spaces; Equivalent spaces; Classification of subsets; and the space of fractals, pp. 541.
    44. 44)
      • 44. Henrikson, J.: ‘Completeness and total boundedness of the Hausdorff metric’, MIT Undergrad. J. Math., 1999, pp. 6980.
    45. 45)
      • 45. Huttenlocher, D., Rucklidge, W.: ‘A multiresolution technique for comparing images using the Hausdorff distance’. Technical Report, Technical Report 1321, Cornell University, Department of Computer Science, 1992.
    46. 46)
    47. 47)
      • 47. Achermann, B., Bunke, H.: ‘Classifying range images of human faces with Hausdorff distance’. Proc. of Int. Conf. on Pattern Recognition (ICPR), 2000, pp. 809813.
    48. 48)
      • 48. Pan, G., Wu, Z., Pan, Y.: ‘Automatic 3D face verification from range data’. Proc. Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2003, pp. 193196.
    49. 49)
      • 49. Russ, T., Koch, K., Little, C.: ‘3D facial recognition: a quantitative analysis’. Annual Meeting of the Institute of Nuclear Materials Management (INMM), 2004.
    50. 50)
    51. 51)
      • 51. Phillips, P.J., Flynn, P.J., Scruggs, T., et al: ‘Overview of the face recognition grand challenge’. Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2005, pp. 947954.
    52. 52)
      • 52. Russ, T., Koch, M., Little, C.: ‘A 2D range Hausdorff approach for 3D face recognition’. Proc. IEEE Workshop on Face Recognition Grand Challenge Experiments, 2005.
    53. 53)
      • 53. ArtecID. (2014) ArtecID – Artec 3D Face LogOn: Data sheet. http://www.artecid.com/resources.html. ArtecID. Available at http://www.artecid.com/resources.html.
    54. 54)
      • 54. Marasco, E., Johnson, P., Sansone, C., Schuckers, S.: ‘Increase the security of multibiometric systems by incorporating a spoofing detection algorithm in the fusion mechanism’. Proc. Int. Workshop on Multiple Classifier Systems (MCS), ser. Springer, 2011 (LNCS, 6713), pp. 309318.
    55. 55)
      • 55. Johnson, P., Lazarick, R., Marasco, E., Newton, E., Ross, A., Schuckers, S.: ‘Biometric liveness detection: framework and metrics’. Proc. NIST Int. Biometric Performance Conf. (IBPC), 2012.
    56. 56)
      • 56. Chingovska, I., Anjos, A., Marcel, S.: ‘Anti-spoofing in action: joint operation with a verification system’. Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition Workshops (CVPR-W), 2013, pp. 98104.
    57. 57)
      • 57. Pan, G., Sun, L., Wu, Z., Lao, S.: ‘Eyeblink-based anti-spoofing in face recognition from a generic webcamera’. Proc. IEEE Int. Conf. on Computer Vision (ICCV), 2007, pp. 1420.
    58. 58)
    59. 59)
    60. 60)
      • 60. de Freitas Pereira, T., Komulainen, J., Anjos, A., et al: ‘Face liveness detection using dynamic texture’, EURASIP J. Image Video Process., 2014, 2, doi:10.1186/1687-5281-2014-2.
    61. 61)
    62. 62)
      • 62. Kose, N., Dugelay, J.-L.: ‘Reflectance analysis based countermeasure technique to detect face mask attacks’. Proc. IEEE Int. Conf. on Digital Signal Processing (DSP), 2013.
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