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Introduction to Presentation Attack Detection in Fingerprint Biometrics

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Handbook of Biometric Anti-Spoofing

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

This chapter provides an introduction to Presentation Attack Detection (PAD) in fingerprint biometrics, also coined as anti-spoofing, describes early developments in this field, and briefly summarizes recent trends and open issues.

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Notes

  1. 1.

    Figures do not lie, but liars do figure.

  2. 2.

    https://www.iarpa.gov/index.php/research-programs/odin/.

  3. 3.

    https://www.iarpa.gov/index.php/research-programs/odin/.

  4. 4.

    http://livdet.diee.unica.it.

  5. 5.

    http://people.clarkson.edu/projects/biosal/fingerprint/index.php.

  6. 6.

    http://biometrics.eps.uam.es/.

References

  1. van der Putte T, Keuning J (2000) Biometrical fingerprint recognition: don’t get your fingers burned. In: Proceedings IFIP conference on smart card research and advanced applications, pp 289–303

    Google Scholar 

  2. Matsumoto T, Matsumoto H, Yamada K, Hoshino S (2002) Impact of artificial gummy fingers on fingerprint systems. In: Proceedings of SPIE optical security and counterfeit deterrence techniques IV, vol 4677, pp 275–289

    Google Scholar 

  3. Thalheim L, Krissler J (2002) Body check: biometric access protection devices and their programs put to the test. ct magazine, pp 114–121

    Google Scholar 

  4. Sousedik C, Busch C (2014) Presentation attack detection methods for fingerprint recognition systems: a survey. IET Biom 3:219–233(14). http://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2013.0020

  5. Derakhshani R, Schuckers S, Hornak L, O’Gorman L (2003) Determination of vitality from non-invasive biomedical measurement for use in fingerprint scanners. Pattern Recognit 36:383–396

    Article  Google Scholar 

  6. Antonelli A, Capelli R, Maio D, Maltoni D (2006) Fake finger detection by skin distortion analysis. IEEE Trans. Inf Forensics Secur 1:360–373

    Google Scholar 

  7. Galbally J, Alonso-Fernandez F, Fierrez J, Ortega-Garcia J (2012) A high performance fingerprint liveness detection method based on quality related features. Futur Gener Comput Syst 28:311–321

    Article  Google Scholar 

  8. Franco A, Maltoni D (2008) Fingerprint synthesis and spoof detection. In: Ratha NK, Govindaraju V (eds) Advances in biometrics: sensors, algorithms and systems. Springer, pp 385–406

    Google Scholar 

  9. Li SZ (ed) (2009) Encyclopedia of biometrics. Springer

    Google Scholar 

  10. Coli P (2008) Vitality detection in personal authentication systems using fingerprints. PhD thesis, Universita di Cagliari

    Google Scholar 

  11. Sandstrom M (2004) Liveness detection in fingerprint recognition systems. Master’s thesis, Linkoping University

    Google Scholar 

  12. Lane M, Lordan L (2005) Practical techniques for defeating biometric devices. Master’s thesis, Dublin City University

    Google Scholar 

  13. Blomme J (2003) Evaluation of biometric security systems against artificial fingers. Master’s thesis, Linkoping University

    Google Scholar 

  14. Lapsley P, Less J, Pare D, Hoffman N (1998) Anti-fraud biometric sensor that accurately detects blood flow 5(737):439

    Google Scholar 

  15. Setlak DR (1999) Fingerprint sensor having spoof reduction features and related methods 5(953):441

    Google Scholar 

  16. Kallo I, Kiss A, Podmaniczky JT (2001) Detector for recognizing the living character of a finger in a fingerprint recognizing apparatus 6(175):64

    Google Scholar 

  17. Diaz-Santana E, Parziale G (2008) Liveness detection method. EP1872719

    Google Scholar 

  18. Kim, J., Choi, H., Lee, W.: Spoof detection method for touchless fingerprint acquisition apparatus (2011). 1054314

    Google Scholar 

  19. Centro Criptologico Nacional (CCN) (2011) Characterizing attacks to fingerprint verification mechanisms CAFVM v3.0. Common Criteria Portal

    Google Scholar 

  20. Bundesamt fur Sicherheit in der Informationstechnik (BSI) (2008) Fingerprint spoof detection protection profile FSDPP v1.8. Common Criteria Portal

    Google Scholar 

  21. Ghiani L, Yambay DA, Mura V, GLM, Roli F, Schuckers S (2017) Review of the fingerprint liveness detection (livdet) competition series: 2009 to 2015. Image Vis Comput 58:110–128. https://doi.org/10.1016/j.imavis.2016.07.002

  22. Casula R, Micheletto M, Orrù G, Delussu R, Concas S, Panzino A, Marcialis G (2021) Livdet 2021 fingerprint liveness detection competition – into the unknown. In: Proceedings of international joint conference on biometrics (IJCB 2021). https://doi.org/10.1109/IJCB52358.2021.9484399

  23. Orrù G, Tuveri P, Casula R, Bazzoni C, Dessalvi G, Micheletto M, Ghiani L, Marcialis G (2019) Livdet 2019 – fingerprint liveness detection competition in action 2019. In: Proceedings of IEEE/IAPR international conference on biometrics (ICB 2019). https://doi.org/10.1109/ICB45273.2019.8987281

  24. Galbally J, Fierrez J, Alonso-Fernandez F, Martinez-Diaz M (2011) Evaluation of direct attacks to fingerprint verification systems. J Telecommun Syst, Special Issue of Biom Syst Appl 47:243–254

    Article  Google Scholar 

  25. Abhyankar A, Schuckers S (2009) Integrating a wavelet based perspiration liveness check with fingerprint recognition. Pattern Recognit 42:452–464

    Article  MATH  Google Scholar 

  26. Spinoulas L, Mirzaalian H, Hussein ME, AbdAlmageed W (2021) Multi-modal fingerprint presentation attack detection: evaluation on a new dataset. IEEE Trans Biom Behav Identity Sci 3:347–364. https://doi.org/10.1109/TBIOM.2021.3072325

    Article  Google Scholar 

  27. Biometrics Institute (2011) Biometric Vulnerability Assessment Expert Group. http://www.biometricsinstitute.org/pages/biometric-vulnerability-assessment-expert-group-bvaeg.html

  28. NPL (2010) National Physical Laboratory: Biometrics. http://www.npl.co.uk/biometrics

  29. CESG (2001) Communications-Electronics Security Group - Biometric Working Group (BWG). https://www.cesg.gov.uk/policyguidance/biometrics/Pages/index.aspx

  30. BEAT (2012) BEAT: Biometrices evaluation and testing. http://www.beat-eu.org/

  31. Tabula Rasa (2010) Trusted biometrics under spoofing attacks (tabula rasa). http://www.tabularasa-euproject.org/

  32. Maltoni D, Maio D, Jain A, Prabhakar S (2009) Handbook of fingerprint recognition. Springer

    Google Scholar 

  33. Cappelli R, Maio D, Lumini A, Maltoni D (2007) Fingerprint image reconstruction from standard templates. IEEE Trans Pattern Anal Mach Intell 29:1489–1503

    Google Scholar 

  34. Cappelli R (2009) Synthetic fingerprint generation. In: Handbook of fingerprint recognition. Springer, pp 270–302

    Google Scholar 

  35. Galbally J, Marcel S, Fierrez J (2014) Image quality assessment for fake biometric detection: application to iris, fingerprint and face recognition. IEEE Trans. Image Process 23(2):710–724. https://doi.org/10.1109/TIP.2013.2292332

    Article  MathSciNet  MATH  Google Scholar 

  36. Hadid A, Evans N, Marcel S, Fierrez J (2015) Biometrics systems under spoofing attack: an evaluation methodology and lessons learned. IEEE Signal Process Mag 32(5):20–30. https://doi.org/10.1109/MSP.2015.2437652

    Article  Google Scholar 

  37. Marasco E, Ross A (2014) A survey on antispoofing schemes for fingerprint recognition systems. ACM Comput Surv 47(2). https://doi.org/10.1145/2617756

  38. Sousedik C, Busch C (2014) Presentation attack detection methods for fingerprint recognition systems: a survey. IET Biom 3(4):219–233. https://doi.org/10.1049/iet-bmt.2013.0020

  39. Karampidis K, Rousouliotis M, Linardos E, Kavallieratou E (2021) A comprehensive survey of fingerprint presentation attack detection. J Surveill Secur Saf 2:117–61

    Google Scholar 

  40. Singh JM, Madhun A, Li G, Ramachandra R (2021) A survey on unknown presentation attack detection for fingerprint. In: Yildirim Yayilgan S, Bajwa IS, Sanfilippo F (eds) Intelligent technologies and applications. Springer International Publishing, Cham, pp 189–202

    Google Scholar 

  41. Wehde A, Beffel JN (1924) Fingerprints can be forged. Tremonia Publish Co

    Google Scholar 

  42. de Water MV (1936) Can fingerprints be forged? Sci News-Lett 29:90–92

    Article  Google Scholar 

  43. Sengottuvelan P, Wahi A (2007) Analysis of living and dead finger impressions identification for biometric applications. In: Proceedings of international conference on computational intelligence and multimedia applications

    Google Scholar 

  44. Yoon S, Feng J, Jain AK (2012) Altered fingerprints: analysis and detection. IEEE Trans Pattern Anal Mach Intell 34:451–464

    Google Scholar 

  45. Willis D, Lee M (1998) Biometrics under our thumb. Netw Comput (1998). http://www.networkcomputing.com/

  46. Sten A, Kaseva A, Virtanen T (2003) Fooling fingerprint scanners - biometric vulnerabilities of the precise biometrics 100 SC scanner. In: Proceedings of Australian information warfare and IT security conference

    Google Scholar 

  47. Wiehe A, Sondrol T, Olsen K, Skarderud F (2004) Attacking fingerprint sensors. NISlab, Gjovik University College, Technical report

    Google Scholar 

  48. Galbally J, Cappelli R, Lumini A, de Rivera GG, Maltoni D, Fierrez J, Ortega-Garcia J, Maio D (2010) An evaluation of direct and indirect attacks using fake fingers generated from ISO templates. Pattern Recognit Lett 31:725–732

    Article  Google Scholar 

  49. Barral C, Tria A (2009) Fake fingers in fingerprint recognition: glycerin supersedes gelatin. In: Formal to practical security, LNCS 5458, pp 57–69

    Google Scholar 

  50. Parthasaradhi S, Derakhshani R, Hornak L, Schuckers S (2005) Time-series detection of perspiration as a liveness test in fingerprint devices. IEEE Trans Syst Man Cybernect - Part C: Appl Rev 35:335–343

    Google Scholar 

  51. Schuckers S, Abhyankar A (2004) A wavelet based approach to detecting liveness in fingerprint scanners. In: Proceedings of biometric authentication workshop (BioAW), LNCS-5404. Springer, pp 278–386

    Google Scholar 

  52. Tan B, Schuckers S (2006) Comparison of ridge- and intensity-based perspiration liveness detection methods in fingerprint scanners. In: Proceedings of SPIE biometric technology for human identification III (BTHI III), vol 6202, p 62020A

    Google Scholar 

  53. Tan B, Schuckers S (2008) A new approach for liveness detection in fingerprint scanners based on valley noise analysis. J Electron Imaging 17:011,009

    Google Scholar 

  54. DeCann B, Tan B, Schuckers S (2009) A novel region based liveness detection approach for fingerprint scanners. In: Proceedings of IAPR/IEEE international conference on biometrics, LNCS-5558. Springer, pp 627–636

    Google Scholar 

  55. NexIDBiometrics (2012). http://nexidbiometrics.com/

  56. Abhyankar A, Schuckers S (2006) Fingerprint liveness detection using local ridge frequencies and multiresolution texture analysis techniques. In: Proceedings of IEEE international conference on image processing (ICIP)

    Google Scholar 

  57. Marasco E, Sansone C (2010) An anti-spoofing technique using multiple textural features in fingerprint scanners. In: Proceedings of IEEE workshop on biometric measurements and systems for security and medical applications (BIOMS), pp 8–14

    Google Scholar 

  58. Marasco E, Sansone C (2012) Combining perspiration- and morphology-based static features for fingerprint liveness detection. Pattern Recognit Lett 33:1148–1156

    Article  Google Scholar 

  59. Cappelli R, Maio D, Maltoni D (2001) Modelling plastic distortion in fingerprint images. In: Proceedings of international conference on advances in pattern recognition (ICAPR), LNCS-2013. Springer, pp 369–376

    Google Scholar 

  60. Bazen AM, Gerez SH (2003) Fingerprint matching by thin-plate spline modelling of elastic deformations. Pattern Recognit 36:1859–1867

    Article  Google Scholar 

  61. Chen Y, Dass S, Ross A, Jain AK (2005) Fingerprint deformation models using minutiae locations and orientations. In: Proceedings of IEEE workshop on applications of computer vision (WACV), pp 150–156

    Google Scholar 

  62. Chen Y, Jain AK (2005) Fingerprint deformation for spoof detection. In: Proceedings of IEEE biometric symposium (BSym), pp 19–21

    Google Scholar 

  63. Zhang Y, Tian J, Chen X, Yang X, Shi P (2007) Fake finger detection based on thin-plate spline distortion model. In: Proceedings of IAPR international conference on biometrics, LNCS-4642. Springer, pp 742–749

    Google Scholar 

  64. Yau WY, Tran HT, Teoh EK, Wang JG (2007) Fake finger detection by finger color change analysis. In: Proceedings of international conference on biometrics (ICB), LNCS 4642. Springer, pp 888–896D

    Google Scholar 

  65. Jia J, Cai L (2007) Fake finger detection based on time-series fingerprint image analysis. In: Proceedings of IEEE international conference on intelligent computing (ICIC), LNCS-4681. Springer, pp 1140–1150

    Google Scholar 

  66. Uchida K (2004) Image-based approach to fingerprint acceptability assessment. In: Proceedings of international conference on biometric authentication, LNCS 3072. Springer, pp 194–300

    Google Scholar 

  67. Marcialis GL, Roli F, Tidu A (2010) Analysis of fingerprint pores for vitality detection. In: Proceedings of IEEE international conference on pattern recognition (ICPR), pp 1289–1292

    Google Scholar 

  68. Memon S, Manivannan N, Balachandran W (2011) Active pore detection for liveness in fingerprint identification system. In: Proceedings of IEEE telecommunications forum (TelFor), pp 619–622

    Google Scholar 

  69. Martinsen OG, Clausen S, Nysather JB, Grimmes S (2007) Utilizing characteristic electrical properties of the epidermal skin layers to detect fake fingers in biometric fingerprint systems-a pilot study. IEEE Trans Biomed Eng 54:891–894

    Article  Google Scholar 

  70. Moon YS, Chen JS, Chan KC, So K, Woo KC (2005) Wavelet based fingerprint liveness detection. Electron Lett 41

    Google Scholar 

  71. Nikam SB, Agarwal S (2009) Feature fusion using Gabor filters and cooccrrence probabilities for fingerprint antispoofing. Int J Intell Syst Technol Appl 7:296–315

    Google Scholar 

  72. Nikam SB, Argawal S (2009) Ridgelet-based fake fingerprint detection. Neurocomputing 72:2491–2506

    Article  Google Scholar 

  73. Nikam S, Argawal S (2010) Curvelet-based fingerprint anti-spoofing. SIViP 4:75–87

    Article  Google Scholar 

  74. Coli P, Marcialis GL, Roli F (2007) Power spectrum-based fingerprint vitality detection. In: Proceedings of IEEE workshop on automatic identification advanced technologies (AutoID), pp 169–173

    Google Scholar 

  75. Jin C, Kim H, Elliott S (2007) Liveness detection of fingerprint based on band-selective Fourier spectrum. In: Proceedings of international conference on information security and cryptology (ICISC), LNCS-4817. Springer, pp 168–179

    Google Scholar 

  76. Jin S, Bae Y, Maeng H, Lee H (2010) Fake fingerprint detection based on image analysis. In: Proceedings of SPIE 7536, sensors, cameras, and systems for industrial/scientific applications XI, p 75360C

    Google Scholar 

  77. Lee H, Maeng H, Bae Y (2009) Fake finger detection using the fractional Fourier transform. In: Proceedings of biometric ID management and multimodal communication (BioID), LNCS 5707. Springer, pp 318–324

    Google Scholar 

  78. Marcialis GL, Coli P, Roli F (2012) Fingerprint liveness detection based on fake finger characteristics. Int J Digit Crime Forensics 4:1–19

    Google Scholar 

  79. Coli P, Marcialis GL, Roli F (2007) Vitality detection from fingerprint images: a critical survey. In: Proceedings of international conference on biometrics (ICB), LNCS 4642. Springer, pp 722–731

    Google Scholar 

  80. Coli P, Marcialis GL, Roli F (2008) Fingerprint silicon replicas: static and dynamic features for vitality detection using an optical capture device. Int. J Image Graph 495–512

    Google Scholar 

  81. Choi H, Kang R, Choi K, Jin ATB, Kim J (2009) Fake-fingerprint detection using multiple static features. Opt Eng 48:047,202

    Google Scholar 

  82. Marcialis GL, Lewicke A, Tan B, Coli P, Grimberg D, Congiu A, Tidu A, Roli F, Schuckers S (2009) First international fingerprint liveness detection competition – livdet 2009. In: Proceedings of IAPR international conference on image analysis and processing (ICIAP), LNCS-5716, pp 12–23

    Google Scholar 

  83. Yambay D, Ghiani L, Denti P, Marcialis GL, Roli F, Schuckers S (2011) LivDet 2011 - fingerprint liveness detection competition 2011. In: Proceedings of international joint conference on biometrics (IJCB)

    Google Scholar 

  84. Nixon KA, Rowe RK (2005) Multispectral fingerprint imaging for spoof detection. In: Proceedings of SPIE 5779, biometric technology for human identification II (BTHI), pp 214–225

    Google Scholar 

  85. Rowe RK, Nixon KA, Butler PW (2008) Multispectral fingerprint image acquisition. In: Ratha N, Govindaraju V (eds) Advances in biometrics: sensors, algorithms and systems. Springer, pp 3–23

    Google Scholar 

  86. Yau WY, Tran HL, Teoh EK (2008) Fake finger detection using an electrotactile display system. In: Proceedings of international conference on control, automation, robotics and vision (ICARCV), pp 17–20

    Google Scholar 

  87. Reddy PV, Kumar A, Rahman SM, Mundra TS (2008) A new antispoofing approach for biometric devices. IEEE Trans Biomed Circuits Syst 2:328–337

    Google Scholar 

  88. Baldiserra D, Franco A, Maio D, Maltoni D (2006) Fake fingerprint detection by odor analysis. In: Proceedings of IAPR international conference on biometrics (ICB), LNCS-3832. Springer, pp 265–272

    Google Scholar 

  89. Cheng Y, Larin KV (2006) Artificial fingerprint recognition using optical coherence tomography with autocorrelation analysis. Appl Opt 45:9238–9245

    Article  Google Scholar 

  90. Manapuram RK, Ghosn M, Larin KV (2006) Identification of artificial fingerprints using optical coherence tomography technique. Asian J Phys 15:15–27

    Google Scholar 

  91. Cheng Y, Larin KV (2007) In vivo two- and three-dimensional imaging of artificial and real fingerprints with optical coherence tomography. IEEE Photon Technol Lett 19:1634–1636

    Article  Google Scholar 

  92. Larin KV, Cheng Y (2008) Three-dimensional imaging of artificial fingerprint by optical coherence tomography. In: Proceedings of SPIE biometric technology for human identification (BTHI), vol 6944, p 69440M

    Google Scholar 

  93. Chang S, Larin KV, Mao Y, Almuhtadi W, Flueraru C (2011) Fingerprint spoof detection using near infrared optical analysis. In: Wang J (ed.) State of the art in biometrics. Intechopen, pp 57–84

    Google Scholar 

  94. Nasiri-Avanaki MR, Meadway A, Bradu A, Khoshki RM, Hojjatoleslami A, Podoleanu AG (2011) Anti-spoof reliable biometry of fingerprints using en-face optical coherence tomography. Opt Photon J 1:91–96

    Article  Google Scholar 

  95. Rattani A, Poh N, Ross A (2012) Analysis of user-specific score characteristics for spoof biometric attacks. In: Proceedings of of IEEE computer society workshop on biometrics at the international conference on computer vision and pattern recognition (CVPR), pp 124–129

    Google Scholar 

  96. Marasco E, Ding Y, Ross A (2012) Combining match scores with liveness values in a fingerprint verification system. In: Proceedings of IEEE international conference on biometrics: theory, applications and systems (BTAS), pp 418–425

    Google Scholar 

  97. Hariri M, Shokouhi SB (2011) Possibility of spoof attack against robustness of multibiometric authentication systems. SPIE J Opt Eng 50:079,001

    Google Scholar 

  98. Akhtar Z, Fumera G, Marcialis GL, Roli F (2011) Robustness analysis of likelihood ratio score fusion rule for multi-modal biometric systems under spoof attacks. In: Proceedings of IEEE international carnahan conference on security technology (ICSST), pp 237–244

    Google Scholar 

  99. Akhtar Z, Fumera G, Marcialis GL, Roli F (2012) Evaluation of serial and parallel multibiometric systems under spoofing attacks. In: Proceedings of international conference on biometrics: theory, applications and systems (BTAS)

    Google Scholar 

  100. Ultra-Scan (2012). http://www.ultra-scan.com/

  101. Optel (2012). http://www.optel.pl/

  102. PosID (2012). http://www.posid.co.uk/

  103. VirdiTech (2012). http://www.virditech.com/

  104. Kang H, Lee B, Kim H, Shin D, Kim J (2003) A study on performance evaluation of the liveness detection for various fingerprint sensor modules. In: Proceedings of international conference on knowledge-based intelligent information and engineering systems (KES), LNAI-2774. Springer, pp 1245–1253

    Google Scholar 

  105. Wang L, El-Maksoud RA, Sasian JM, William Kuhn P, Gee K, VSV (2009) A novel contactless aliveness-testing fingerprint sensor. In: Proceedings of SPIE novel optical systems design and optimization XII, vol 7429, p 742915

    Google Scholar 

  106. Chugh T, Cao K, Jain AK (2018) Fingerprint spoof buster: use of minutiae-centered patches. IEEE Trans Inf Forensics Secur 13:2190–2202. https://doi.org/10.1109/TIFS.2018.2812193

    Article  Google Scholar 

  107. Park E, Cui X, Nguyen THB, Kim H (2019) Presentation attack detection using a tiny fully convolutional network. IEEE Trans Inf Forensics Secur 14:3016–3025. https://doi.org/10.1109/TIFS.2019.2907184

    Article  Google Scholar 

  108. Xia Z, Yuan C, Lv R, Sun X, Xiong NN, Shi Y (2020) A novel weber local binary descriptor for fingerprint liveness detection. IEEE Trans Syst Man Cybernet: Syst 50:1526–1536. https://doi.org/10.1109/TSMC.2018.2874281

    Article  Google Scholar 

  109. Agarwal S, Rattani A, Chowdary CR (2021) A comparative study on handcrafted features v/s deep features for open-set fingerprint liveness detection. Pattern Recognit Lett 147:34–40. https://doi.org/10.1016/j.patrec.2021.03.032

    Article  Google Scholar 

  110. Jain AK, Deb D, Engelsma JJ (2021) Biometrics: trust, but verify

    Google Scholar 

  111. Chugh T, Jain AK (2021) Fingerprint spoof detector generalization. IEEE Trans Inf Forensics Secur 16:42–55. https://doi.org/10.1109/TIFS.2020.2990789

    Article  Google Scholar 

  112. Micheletto M, Marcialis GL, Orrù G, Roli F (2021) Fingerprint recognition with embedded presentation attacks detection: are we ready? IEEE Trans Inf Forensics Secur 16:5338–5351. https://doi.org/10.1109/TIFS.2021.3121201

    Article  Google Scholar 

  113. Nixon KA, Aimale V, Rowe RK (2008) Spoof detection schemes. In: Jain AK, Flynn P, Ross A (eds) Handbook of biometrics. Springer, pp 403–423

    Google Scholar 

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Acknowledgements

This work was mostly done (2nd Edition of the book) in the context of TABULA RASA: Trusted Biometrics under Spoofing Attacks, and BEAT: Biometrics Evaluation and Testing projects funded under the 7th Framework Programme of EU. The 3rd Edition update has been made in the context of EU H2020 projects PRIMA and TRESPASS-ETN. This work was also partially supported by the Spanish project BIBECA (RTI2018-101248-B-I00 MINECO/FEDER).

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Authors and Affiliations

  1. European Commission, Joint Research Centre, Ispra, Italy

    Javier Galbally

  2. Biometrics and Data Pattern Analytics-BiDA Lab, Universidad Autonoma de Madrid, Madrid, Spain

    Julian Fierrez

  3. Università di Bologna, Cesena, Italy

    Raffaele Cappelli

  4. Università di Cagliari, Cagliari, Italy

    Gian Luca Marcialis

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  1. Javier Galbally
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  4. Gian Luca Marcialis
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Correspondence to Gian Luca Marcialis .

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  1. Idiap Research Institute, Martigny, Switzerland

    Sébastien Marcel

  2. Universidad Autonoma de Madrid, Madrid, Spain

    Julian Fierrez

  3. EURECOM, Biot Sophia Antipolis, France

    Nicholas Evans

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Galbally, J., Fierrez, J., Cappelli, R., Marcialis, G.L. (2023). Introduction to Presentation Attack Detection in Fingerprint Biometrics. In: Marcel, S., Fierrez, J., Evans, N. (eds) Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. Springer, Singapore. https://doi.org/10.1007/978-981-19-5288-3_1

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