Presentation attack detection methods for fingerprint recognition systems: a survey
- Author(s): Ctirad Sousedik 1 and Christoph Busch 1
-
-
View affiliations
-
Affiliations:
1:
Norwegian Information Security Laboratory (NISlab), Gjøvik University College, Teknologiveien 22, 2815 Gjøvik, Norway
-
Affiliations:
1:
Norwegian Information Security Laboratory (NISlab), Gjøvik University College, Teknologiveien 22, 2815 Gjøvik, Norway
- Source:
Volume 3, Issue 4,
December 2014,
p.
219 – 233
DOI: 10.1049/iet-bmt.2013.0020 , Print ISSN 2047-4938, Online ISSN 2047-4946
(http://creativecommons.org/licenses/by-nc/3.0/)
Nowadays, fingerprint biometrics is widely used in various applications, varying from forensic investigations and migration control to access control as regards security sensitive environments. Any biometric system is potentially vulnerable against a fake biometric characteristic, and spoofing of fingerprint systems is one of the most widely researched areas. The state-of-the-art sensors can often be spoofed by an accurate imitation of the ridge/valley structure of a fingerprint. An individual may also try to avoid identification by altering his own fingerprint pattern. This study is a survey of presentation attack detection methods for fingerprints, both in terms of liveness detection and alteration detection.
Inspec keywords: fingerprint identification
Other keywords: presentation attack detection methods; fingerprint recognition system; state-of-the-art sensors; security sensitive environments; forensic investigations; migration control; access control; fingerprint biometrics
Subjects: Computer vision and image processing techniques; Image recognition
References
-
-
1)
-
47. Antonelli, A., Cappelli, R., Maio, D., Maltoni, D.: ‘Fake finger detection by skin distortion analysis’, IEEE Trans. Inf. Forensics Sec., 2006, 1, (3), pp. 360–373 (doi: 10.1109/TIFS.2006.879289).
-
-
2)
-
27. Sousedik, C., Breithaupt, R., Busch, C.: ‘Volumetric fingerprint data analysis using optical coherence tomography’. Proc. Int. Conf. of the Biometrics Special Interest Group (BIOSIG), 2013, pp. 1–6.
-
-
3)
-
42. Nikam, S., Agarwal, S.: ‘Texture and wavelet-based spoof fingerprint detection for fingerprint biometric systems’. Proc. First Int. Conf. on Emerging Trends in Engineering and Technology (ICETET ‘08), 2008, pp. 675–680.
-
-
4)
-
5. Galbally, J., Fierrez, J., Alonso-Fernandez, F., Martinez-Diaz, M.: ‘Evaluation of direct attacks to fingerprint verification systems’, Telecommun. Syst., 2011, 47, pp. 243–254 (doi: 10.1007/s11235-010-9316-0).
-
-
5)
-
39. Nikam, S.B., Agarwal, S.: ‘Ridgelet-based fake fingerprint detection’, Neurocomputing, 2009, 72, (10–12), pp. 2491–2506 (doi: 10.1016/j.neucom.2008.11.003).
-
-
6)
-
29. Choi, H., Kang, R., CHoi, K., Kim, J.: ‘Aliveness detection of fingerprints using multiple static features’. Proc. World Academy of Science, Engineering and Technology, 2007, vol. 22.
-
-
7)
-
2. Zwiesele, A., Munde, A., Busch, C., Daum, H.: ‘BioIS study. Comparative study of biometric identification systems’. Proc. 34th Annual Int. Carnahan Conf. on Security Technology, 2000, pp. 60–63.
-
-
8)
-
51. Abhyankar, A., Schuckers, S.: ‘Integrating a wavelet based perspiration liveness check with fingerprint recognition’, Pattern Recognit., 2009, 42, (3), pp. 452–464 (doi: 10.1016/j.patcog.2008.06.012).
-
-
9)
-
64. Drahansky, M., Notzel, R., Funk, W.: ‘Liveness detection based on fine movements of the fingertip surface’. Proc. IEEE Information Assurance Workshop, 2006, pp. 42–47.
-
-
10)
- P. Coli , G.L. Marcialis , F. Roli . Fingerprint silicon replicas: static and dynamic features for vitality detection using an optical capture device. Int. J. Image Graph. , 495 - 512
-
11)
-
10. Memon, S., Sepasian, M., Balachandran, W.: ‘Review of finger print sensing technologies’. Proc. IEEE Int. Multitopic Conf. (INMIC), 2008, pp. 226–231.
-
-
12)
-
8. Matsumoto, T., Matsumoto, H., Yamada, K., Hoshino, S.: ‘Impact of artificial ‘gummy’ fingers on fingerprint systems’. Proc. SPIE 4677, Optical Security and Counterfeit Deterrence Techniques IV, 2002, vol. 4677, pp. 275–289.
-
-
13)
-
17. Espinoza, M., Champod, C.: ‘Using the number of pores on fingerprint images to detect spoofing attacks’. Proc. Int. Conf. on Hand-Based Biometrics (ICHB), 2011, pp. 1–5.
-
-
14)
-
23. Yoon, S., Zhao, Q., Jain, A.: ‘On matching altered fingerprints’. Proc. Fifth IAPR Int. Conf. on Biometrics (ICB), 2012, pp. 222–229.
-
-
15)
-
58. Yau, W.Y., Tran, H.L., Teoh, E.K.: ‘Fake finger detection using an electrotactile display system’. Proc. Tenth Int. Conf. on Control, Automation, Robotics and Vision (ICARCV 2008), 2008, pp. 962–966.
-
-
16)
-
16. Biggio, B., Akhtar, Z., Fumera, G., Marcialis, G., Roli, F.: ‘Security evaluation of biometric authentication systems under real spoofing attacks’, IET Biometrics, 2012, 1, (1), pp. 11–24 (doi: 10.1049/iet-bmt.2011.0012).
-
-
17)
-
71. Bossen, A., Lehmann, R., Meier, C.: ‘Internal fingerprint identification with optical coherence tomography’, IEEE Photonics Technol. Lett., 2010, 22, (7), pp. 507–509 (doi: 10.1109/LPT.2010.2041347).
-
-
18)
-
26. Marasco, E., Sansone, C.: ‘Combining perspiration- and morphology-based static features for fingerprint liveness detection’, Pattern Recognit. Lett., 2012, 33, (9), pp. 1148–1156 (doi: 10.1016/j.patrec.2012.01.009).
-
-
19)
-
22. Tiribuzi, M., Pastorelli, M., Valigi, P., Ricci, E.: ‘A multiple kernel learning framework for detecting altered fingerprints’. Proc. 21st Int. Conf. on Pattern Recognition (ICPR), 2012, pp. 3402–3405.
-
-
20)
-
24. Petrovici, A., Lazar, C.: ‘Identifying fingerprint alteration using the reliability map of the orientation field’, Ann. Univ. Craiova, Series Autom. Comput. Electron. Mechatronics, 2010, 7, (34), pp. 45–52.
-
-
21)
-
54. Nikam, S.B., Agarwal, S.: ‘Wavelet-based multiresolution analysis of ridges for fingerprint liveness detection’, Int. J. Inf. Comput. Sec., 2009, 3, (1), pp. 1–46.
-
-
22)
-
65. Martinsen, O., Clausen, S., Nysaether, J., Grimnes, S.: ‘Utilizing characteristic electrical properties of the epidermal skin layers to detect fake fingers in biometric fingerprint systems – a pilot study’, IEEE Trans. Biomed. Eng., 2007, 54, (5), pp. 891–894 (doi: 10.1109/TBME.2007.893472).
-
-
23)
-
43. Pereira, L., Pinheiro, H., Silva, J., et al: ‘A fingerprint spoof detection based on MLP and SVM’. Proc. Int. Joint Conf. on Neural Networks (IJCNN), 2012, pp. 1–7.
-
-
24)
-
53. Decann, B., Tan, B., Schuckers, S.: ‘A novel region based liveness detection approach for fingerprint scanners’. Proc. Third Int. Conf. on Advances in Biometrics (ICB ‘09), 2009, pp. 627–636.
-
-
25)
-
14. Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: ‘Handbook of fingerprint recognition’ (Springer London, 2009, 2nd edn.), Ch. 9.5, pp. 386–391.
-
-
26)
- R. Derakhshani , S.A.C. Schuckers , L.A. Hornak , L.O. Gorman . Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners. Pattern Recognit. , 2 , 383 - 396
-
27)
-
6. Kang, H., Lee, B., Kim, H., Shin, D., Kim, J.: ‘A study on performance evaluation of the liveness detection for various fingerprint sensor modules’. Knowledge-Based Intelligent Information and Engineering Systems, 2003(LNCS, 2774), pp. 1245–1253.
-
-
28)
-
81. Trusted Biometrics under Spoofing Attacks (Tabula Rasa): ‘http://www.tabularasa-euproject.org/’.
-
-
29)
-
80. Biometrics Evaluation and Testing (BEAT): ‘http://www.beat-eu.org/’.
-
-
30)
-
37. Nikam, S., Agarwal, S.: ‘Wavelet energy signature and GLCM features-based fingerprint anti-spoofing’. Proc. Int. Conf. on Wavelet Analysis and Pattern Recognition (ICWAPR ‘08), 2008, vol. 2, pp. 717–723.
-
-
31)
-
50. Parthasaradhi, S., Derakhshani, R., Hornak, L., Schuckers, S.: ‘Time-series detection of perspiration as a liveness test in fingerprint devices’, IEEE Trans. Syst. Man Cybern. C, Appl. Rev., 2005, 35, (3), pp. 335–343 (doi: 10.1109/TSMCC.2005.848192).
-
-
32)
-
55. Marcialis, G., Roli, F., Tidu, A.: ‘Analysis of fingerprint pores for vitality detection’. Proc. 20th Int. Conf. on Pattern Recognition (ICPR), 2010, pp. 1289–1292.
-
-
33)
-
59. Baldisserra, D., Franco, A., Maio, D., Maltoni, D.: ‘Fake fingerprint detection by odor analysis’. Advances in Biometrics, 2005(LNCS, 3832), pp. 265–272.
-
-
34)
-
44. Coli, P., Marcialis, G., Roli, F.: ‘Power spectrum-based fingerprint vitality detection’. Proc. IEEE Workshop on Automatic Identification Advanced Technologies, 2007, pp. 169–173.
-
-
35)
-
31. Jin, C., Li, S., Kim, H., Park, E.: ‘Fingerprint liveness detection based on multiple image quality features’. Information Security Applications, 2011(LNCS, 6513), pp. 281–291.
-
-
36)
-
9. Wiehe, A., Søndrol, T., Olsen, O., Skarderud, F.: ‘Attacking fingerprint sensors’. Technical report, NISlab/Gjovik Univ. College, 2004.
-
-
37)
-
68. Cheng, Y., Larin, K.: ‘In vivo two- and three-dimensional imaging of artificial and real fingerprints with optical coherence tomography’, IEEE Photonics Technol. Lett., 2007, 19, (20), pp. 1634–1636 (doi: 10.1109/LPT.2007.904932).
-
-
38)
-
20. Feng, J., Jain, A., Ross, A.: ‘Detecting altered fingerprints’. Proc. 20th Int. Conf. on Pattern Recognition (ICPR), 2010, pp. 1622–1625.
-
-
39)
-
56. Memon, S., Manivannan, N., Balachandran, W.: ‘Active pore detection for liveness in fingerprint identification system’. Proc. Telecommunications Forum (TELFOR), 2011 19th, 2011, pp. 619–622.
-
-
40)
-
12. Rowe, R.K., Nixon, K.A., Butler, P.W.: ‘Multispectral fingerprint image acquisition’, in Ratha, N., Govindaraju, V. (Eds.): ‘Advances in Biometrics’ (Springer, London, 2008), pp. 3–23.
-
-
41)
-
11. Sato, N., Machida, K., Morimura, H., et al: ‘MEMS fingerprint sensor immune to various finger surface conditions’, IEEE Trans. Electron Devices, 2003, 50, (4), pp. 1109–1116 (doi: 10.1109/TED.2003.812490).
-
-
42)
-
30. Tan, B., Schuckers, S.: ‘New approach for liveness detection in fingerprint scanners based on valley noise analysis’, J. Electron. Imaging, 2008, 17, (1), pp. 011009–011009-9 (doi: 10.1117/1.2885133).
-
-
43)
-
15. Yambay, D., Ghiani, L., Denti, P., Marcialis, G., Roli, F., Schuckers, S.: ‘LivDet 2011 – Fingerprint liveness detection competition 2011’. Proc. Fifth IAPR Int. Conf. on Biometrics (ICB), 2012, pp. 208–215.
-
-
44)
- Y.S. Moon , J.S. Chen , K.C. Chan , K.C. Woo . Wavelet based fingerprint liveness detection. Electron. Lett. , 1112 - 1113
-
45)
-
21. Yoon, S., Feng, J., Jain, A.: ‘Altered fingerprints: analysis and detection’, IEEE Trans. Pattern Anal. Mach. Intell., 2012, 34, (3), pp. 451–464 (doi: 10.1109/TPAMI.2011.161).
-
-
46)
-
3. Espinoza, M., Champod, C., Margot, P.: ‘Vulnerabilities of fingerprint reader to fake fingerprints attacks’, Forensic Sci Int., 2011, 204, (1–3), pp. 41–49 (doi: 10.1016/j.forsciint.2010.05.002).
-
-
47)
-
45. Galbally, J., Alonso-Fernandez, F., Fierrez, J., Ortega-Garcia, J.: ‘A high performance fingerprint liveness detection method based on quality related features’, Future Gener. Comput. Syst., 2012, 28, (1), pp. 311–321 (doi: 10.1016/j.future.2010.11.024).
-
-
48)
-
72. Menrath, M.: ‘Fingerprint with OCT’. Master's thesis, Fern-Universität Hagen in Cooperation with Bundesamt für Sicherheit in der Informationstechnik (BSI), 2011.
-
-
49)
-
13. Lee, C., Lee, S., Kim, J.: ‘A study of touchless fingerprint recognition system’. Structural, Syntactic, and Statistical Pattern Recognition, 2006(LNCS, 4109), pp. 358–365.
-
-
50)
-
61. Hengfoss, C., Kulcke, A., Mull, G., Edler, C., Püschel, K., Jopp, E.: ‘Dynamic liveness and forgeries detection of the finger surface on the basis of spectroscopy in the 400–1650 nm region’, Forensic Sci. Int., 2011, 212, (1–3), pp. 61–68 (doi: 10.1016/j.forsciint.2011.05.014).
-
-
51)
-
19. Coli, P., Marcialis, G.L., Roli, F.: ‘Vitality detection from fingerprint images: a critical survey’. Proc. of the Int. Conf. on Advances in Biometrics (ICB ‘07), 2007, pp. 722–731.
-
-
52)
-
77. Ghiani, L., Yambay, D., Mura, V., et al: ‘LivDet 2013 fingerprint liveness detection competition 2013’. Proc. Sixth IAPR Int. Conference on Biometrics (ICB), 2013.
-
-
53)
-
57. Abhyankar, A., Schuckers, S.: ‘Modular decomposition of fingerprint time series captures for the liveness check’, Int. J. Comput. Electr. Eng., 2010, 2, pp. 426–431 (doi: 10.7763/IJCEE.2010.V2.172).
-
-
54)
-
52. Jia, J., Cai, L.: ‘Fake finger detection based on time-series fingerprint image analysis’. Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues, 2007(LNCS, 4681), pp. 1140–1150.
-
-
55)
-
78. Sepasian, M., Mares, C., Balachandran, W.: ‘Vitality detection in fingerprint identification’, WSEAS Trans. Info. Sci. and App., 2010, 7, (4), pp. 498–507.
-
-
56)
-
67. Cheng, Y., Larin, K.V.: ‘Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis’, Appl. Opt., 2006, 45, (36), pp. 9238–9245 (doi: 10.1364/AO.45.009238).
-
-
57)
-
69. Peterson, L.E., Larin, K.V.: ‘Image classification of artificial fingerprints using Gabor wavelet filters, self-organising maps and Hermite/Laguerre neural networks’, Int. J. Knowl. Eng. Soft Data Paradigms, 2009, 1, (3), pp. 239–256 (doi: 10.1504/IJKESDP.2009.028817).
-
-
58)
-
25. Petrovici, A.: ‘Simulating alteration on fingerprint images’. Proc. IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS), 2012, pp. 1–5.
-
-
59)
-
4. Espinoza, M., Champod, C.: ‘Risk evaluation for spoofing against a sensor supplied with liveness detection’, Forensic Sci. Int., 2011, 204, (1–3), pp. 162–168 (doi: 10.1016/j.forsciint.2010.05.025).
-
-
60)
-
1. Han, Y., Ryu, C., Moon, J., Kim, H., Choi, H.: ‘A study on evaluating the uniqueness of fingerprints using statistical analysis’. Information Security and Cryptology – ICISC 2004, 2005(LNCS, 3506), pp. 467–477.
-
-
61)
-
40. Nikam, S., Agarwal, S.: ‘Gabor filter-based fingerprint anti-spoofing’. Advanced Concepts for Intelligent Vision Systems, 2008(LNCS, 5259), pp. 1103–1114.
-
-
62)
-
28. Manivanan, N., Memon, S., Balachandran, W.: ‘Automatic detection of active sweat pores of fingerprint using highpass and correlation filtering’, Electron. Lett., 2010, 46, (18), pp. 1268–1269 (doi: 10.1049/el.2010.1549).
-
-
63)
-
18. International Organization for Standardization, ISO/IEC 5th WD 30107: ‘Information Technology – Biometrics – Presentation attack detection’, 2013.
-
-
64)
-
34. Tan, B., Schuckers, S.: ‘Spoofing protection for fingerprint scanner by fusing ridge signal and valley noise’, Pattern Recognit., 2010, 43, (8), pp. 2845–2857 (doi: 10.1016/j.patcog.2010.01.023).
-
-
65)
-
60. Reddy, P., Kumar, A., Rahman, S., Mundra, T.: ‘A new antispoofing approach for biometric devices’, IEEE Trans. Biomed. Circuits Syst., 2008, 2, (4), pp. 328–337 (doi: 10.1109/TBCAS.2008.2003432).
-
-
66)
-
70. Nasiri-Avanaki, M.R., Meadway, A., Bradu, A., Khoshki, R.M., Hojjatoleslami, A., Podoleanu, A.G.: ‘Anti-spoof reliable biometry of fingerprints using en-face optical coherence tomography’, Opt. Photonics J., 2011, 1, (3), pp. 91–96 (doi: 10.4236/opj.2011.13015).
-
-
67)
-
75. Marcialis, G., Ghiani, L., Vetter, K., Morgeneier, D., Roli, F.: ‘Large scale experiments on fingerprint liveness detection’. Structural, Syntactic, and Statistical Pattern Recognition, 2012(LNCS, 7626), pp. 501–509.
-
-
68)
-
33. Tan, B., Schuckers, S.: ‘Liveness detection for fingerprint scanners based on the statistics of wavelet signal processing’. Proc. Computer Vision and Pattern Recognition Workshop (CVPRW ‘06), 2006, pp. 26.
-
-
69)
-
48. Zhang, Y., Tian, J., Chen, X., Yang, X., Shi, P.: ‘Fake finger detection based on thin-plate spline distortion model’. Advances in Biometrics, 2007(LNCS, 4642), pp. 742–749.
-
-
70)
-
36. Pereira, L., Pinheiro, H., Cavalcanti, G., Ren, T.I.: ‘Spatial surface coarseness analysis: technique for fingerprint spoof detection’, Electron. Lett., 2013, 49, (4), pp. 260–261 (doi: 10.1049/el.2012.4173).
-
-
71)
-
74. Ghiani, L., Denti, P., Marcialis, G.: ‘Experimental results on fingerprint liveness detection’. Articulated Motion and Deformable Objects, 2012(LNCS, 7378), pp. 210–218.
-
-
72)
-
79. Meissner, S., Breithaupt, R., Koch, E.: ‘Fingerprint fake detection by optical coherence tomography’. Proc. SPIE 8571, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVII, 2013, vol. 8571.
-
-
73)
-
63. Chang, S., Larin, K., Mao, Y., Almuhtadi, W., Flueraru, C.: ‘Fingerprint spoof detection by NIR optical analysis’, in Yang, J. (Ed.): ‘State of the art in Biometrics’ (InTech, 2011).
-
-
74)
-
66. Shimamura, T., Morimura, H., Shimoyama, N., et al: ‘Impedance-sensing circuit techniques for integration of a fraud detection function into a capacitive fingerprint sensor’, IEEE Sens. J., 2012, 12, (5), pp. 1393–1401 (doi: 10.1109/JSEN.2011.2172413).
-
-
75)
-
46. Jia, J., Cai, L., Zhang, K., Chen, D.: ‘A new approach to fake finger detection based on skin elasticity analysis’. Proc. ICB, 2007, pp. 309–318.
-
-
76)
-
32. Marasco, E., Sansone, C.: ‘An anti-spoofing technique using multiple textural features in fingerprint scanners’. Proc. IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS), 2010, pp. 8–14.
-
-
77)
-
7. van der Putte, T., Keuning, J.: ‘Biometrical fingerprint recognition: don't get your fingers burned’. Proc. IFIP TC8/WG8.8, 4thWorking Conf. on Smart Card Research and Advanced Applications, 2000, pp. 289–303.
-
-
78)
-
73. Marcialis, G., Lewicke, A., Tan, B., et al: ‘First international fingerprint liveness detection competition – LivDet 2009’. Image Analysis and Processing – ICIAP 2009, 2009(LNCS, 5716), pp. 12–23.
-
-
79)
-
62. LUMIDIGM: ‘http://www.lumidigm.com/technology/’.
-
-
80)
-
41. Nikam, S., Agarwal, S.: ‘Fingerprint liveness detection using curvelet energy and co-occurrence signatures’. Proc. Fifth Int. Conf. on Computer Graphics, Imaging and Visualisation (CGIV ‘08), 2008, pp. 217–222.
-
-
81)
- E.J. Candès , D.L. Donoho . Ridgelets: a key to higher dimensional intermittency. R. Soc. Publ. Source: Phil. Trans.: Math. Phys. Eng. Sci. , 1760 , 2495 - 2509
-
1)