Skip to main content
SpringerLink
Log in

Presentation attack detection system for fake Iris: a review

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

The real-time solicitations of biometric systems have been extensively used for several things with the growing necessities of higher security level. There are numerous biometric traits used for person identification. In recent years, iris biometric trait become very popular and efficient in many security applications. However, biometric systems are prone to presentation attack. This attack is carried out by using spoofing of any biometric modality and present as a real trait. The objective of this paper is to present a broad and well thought-out overview of the effort that has been conceded out over the preceding years in the field of iris anti-spoofing. Spoofing of an iris image can be done by paper print and contact lens etc. So, it is essential to discover fake iris up to its core level. In this survey, we have discussed various research work done in the past on the topic of different classes of presentation attack and summarized the state-of-the-art methods in a structural way. We have also discussed the future direction in the field of iris liveness detection.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Agarwal R, Jalal AS, Arya KV (2020) A review on presentation attack detection system for fake fingerprint. Modern Physics Letters B 34(05):2030001

    Article  Google Scholar 

  2. Agarwal R, Jalal AS, Arya KV (2020) Local binary hexagonal extrema pattern (LBHXEP): a new feature descriptor for fake iris detection. Vis Comput. https://doi.org/10.1007/s00371-020-01870-0

  3. Agarwal R, Jalal AS, Arya KV (2020) Enhanced Binary Hexagonal Extrema Pattern (EBH X EP) Descriptor for Iris Liveness Detection. Wireless personal communications 115(3):2627–2643

  4. Agrawal R, Jalal AS, Arya KV (2019) Fake fingerprint liveness detection based on micro and macro features. Int J Biometrics 11(2):177–206

    Article  Google Scholar 

  5. Anjos A, El Shafey L, Marcel S (2017). Beat: An open-science web platform. In Thirty-fourth International Conference on Machine Learning (No. CONF)

  6. Anjos A, El Shafey L, Marcel S (2017) BEAT: an open-science web platform. In Thirty-fourth International Conference on Machine Learning

  7. Bhogal APS, Söllinger D, Trung P, Uhl A (2017) Non-reference image quality assessment for biometric presentation attack detection. In 2017 5th international workshop on biometrics and forensics (IWBF):1-6

  8. Bodade RM, Talbar SN (2009) Dynamic iris localisation: A novel approach suitable for fake iris detection. ICUMT, pp 1–5. https://doi.org/10.1049/ic.2009.0123

  9. Bodade R, Talbar S (2011) Fake iris detection: a holistic approach. Int J Comput Appl 19(2):1–7

    Google Scholar 

  10. Chatterjee P, Yalchin A, Shelton J, Roy K, Yuan X, Edoh KD (2019) Presentation Attack Detection Using Wavelet Transform and Deep Residual Neural Net. In: Wang G, Feng J, Bhuiyan M, Lu R (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2019 Lecture Notes in Computer Science, vol 11637. Springer, Cham. https://doi.org/10.1007/978-3-030-24900-7_7

  11. Chen C, Ross A (2018) A multi-task convolutional neural network for joint iris detection and presentation attack detection. In 2018 IEEE winter applications of Computer vision workshops (WACVW):44-51

  12. Chen J, Shan S, He C, Zhao G, Pietikainen M, Chen X, Gao W (2009) WLD: A Robust Local Image Descriptor. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(9):1705–1720. https://doi.org/10.1109/TPAMI.2009.155

  13. Chen R, Lin X, Ding T (2012) Liveness detection for iris recognition using multispectral images. Pattern Recogn Lett 33(12):1513–1519

    Article  Google Scholar 

  14. Chingovska I, Mohammadi A, Anjos A, Marcel S (2019) Evaluation methodologies for biometric presentation attack detection. In handbook of biometric anti-spoofing:457-480

  15. Choudhary M, Tiwari V, Venkanna U (2019) An approach for iris contact lens detection and classification using ensemble of customized DenseNet and SVM. Future Generation Computer Systems 101:1259–1270. https://doi.org/10.1016/j.future.2019.07.003

  16. Connell J, Ratha N, Gentile J, Bolle R (2013) "Fake iris detection using structured light," 2013 IEEE International Conference on Acoustics. Speech and Signal Processing, Vancouver, BC, pp 8692–8696. https://doi.org/10.1109/ICASSP.2013.6639363

  17. Czajka A (2015) Pupil dynamics for iris liveness detection. IEEE Trans Inform Forensics Secur 10(4):726–735

    Article  Google Scholar 

  18. Das A, Pal U, Ferrer MA, Blumenstein M (2016) A framework for liveness detection for direct attacks in the visible spectrum for multimodal ocular biometrics. Pattern Recogn Lett 82:232–241

    Article  Google Scholar 

  19. Das P, McGrath J, Fang Z, Boyd A, Jang G, Mohammadi A, . . . Trokielewicz M (2020) Iris Liveness Detection Competition (LivDet-Iris)--The 2020 Edition. arXiv preprint arXiv:2009.00749

  20. Doyle JS, Bowyer KW (2015) Robust Detection of Textured Contact Lenses in Iris Recognition Using BSIF. In IEEE Access, vol. 3, pp 1672-1683. https://doi.org/10.1109/ACCESS.2015.2477470

  21. Doyle JS, Bowyer KW, Flynn PJ (2013) Variation in accuracy of textured contact lens detection based on sensor and lens pattern. In 2013 IEEE sixth international conference on biometrics: theory, applications and systems (BTAS): 1-7

  22. Fathy WSA, Ali HS (2018) Entropy with local binary patterns for efficient iris liveness detection. Wirel Pers Commun 102(3):2331–2344

    Article  Google Scholar 

  23. Galbally J, Gomez-Barrero M (2016). A review of iris anti-spoofing. In 2016 4th international conference on biometrics and forensics (IWBF):1-6

  24. Galbally J, Ortiz-Lopez J, Fierrez J, Ortega-Garcia J (2012) Iris liveness detection based on quality related features. In: 2012 5th IAPR International Conference on Biometrics (ICB), New Delhi, pp 271–276. https://doi.org/10.1109/ICB.2012.6199819

  25. Galbally J, Marcel S, Fierrez J (2013) Image quality assessment for fake biometric detection: application to iris, fingerprint, and face recognition. IEEE Trans Image Process 23(2):710–724

    Article  MathSciNet  Google Scholar 

  26. Galbally J, Savvides M, Venugopalan S, Ross AA (2016) Iris image reconstruction from binary templates. In Handbook of Iris Recognition:469–496

  27. Gragnaniello D, Poggi G, Sansone C, Verdoliva L (2014) Contact Lens Detection and Classification in Iris Images through Scale Invariant Descriptor. In: Tenth International Conference on Signal-Image Technology and Internet-Based Systems, Marrakech, pp 560–565. https://doi.org/10.1109/SITIS.2014.35

  28. Gragnaniello D, Poggi G, Sansone C, Verdoliva L (2015) An investigation of local descriptors for biometric spoofing detection. IEEE Trans Inform Forensics Secur 10(4):849–863

    Article  Google Scholar 

  29. Gragnaniello D, Sansone C, Verdoliva L (2015) Iris liveness detection for mobile devices based on local descriptors. Pattern Recognition Letters 57:81–87. https://doi.org/10.1016/j.patrec.2014.10.018

  30. Gupta P, Behera S, Vatsa M, Singh R (2014) On iris spoofing using print attack. In 2014 22nd international conference on pattern recognition :1681-1686

  31. He X, Lu Y, Shi P (2008) A Fake Iris Detection Method Based on FFT and Quality Assessment. Paper presented at the 2008 Chinese Conference on Pattern Recognition

  32. He X, Lu Y, Shi P (2009) A New Fake Iris Detection Method. In: Tistarelli M, Nixon MS (eds) Advances in Biometrics. ICB 2009. Lecture Notes in Computer Science, vol 5558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01793-3_114

  33. He X, Lu Y, Shi P (2009) A New Fake Iris Detection Method. In: Tistarelli M, Nixon MS (eds) Advances in Biometrics. ICB 2009. Lecture Notes in Computer Science, vol 5558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01793-3_114

  34. He Y, Hou Y, Li Y, Wang Y (2010) Liveness iris detection method based on the eye's optical features (Vol. 7838): SPIE

  35. He L, Li H, Liu F, Liu N, Sun Z, He Z (2016) Multi-patch convolution neural network for iris liveness detection. Paper presented at the 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)

  36. Hoffman S, Sharma R, Ross A (2018) Convolutional neural networks for iris presentation attack detection: Toward cross-dataset and cross-sensor generalization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops:1620–1628

  37. Hsieh SH, Li YH, Wang W, Tien CH (2018) A novel anti-spoofing solution for iris recognition toward cosmetic contact lens attack using spectral ICA analysis. Sensors 18(3):795

    Article  Google Scholar 

  38. Hu Y, Sirlantzis K, Howells G (2016) Iris liveness detection using regional features. Pattern Recognition Letters 82:242–250. https://doi.org/10.1016/j.patrec.2015.10.010

  39. Huang X, Ti C, Hou Q, Tokuta A, Yang R "An experimental study of pupil constriction for liveness detection," 2013 IEEE Workshop on Applications of Computer Vision (WACV), Tampa, FL, 2013, pp 252-258. https://doi.org/10.1109/WACV.2013.6475026

  40. Hughes K, Bowyer KW (2013) "Detection of Contact-Lens-Based Iris Biometric Spoofs Using Stereo Imaging," 2013 46th Hawaii International Conference on System Sciences, Wailea, Maui, HI, 1763-1772. https://doi.org/10.1109/HICSS.2013.172

  41. Kannala J, Rahtu E (2012) "BSIF: Binarized statistical image features," Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), Tsukuba, 1363-1366

  42. Karunya R, Kumaresan S (2015) "A study of liveness detection in fingerprint and iris recognition systems using image quality assessment," 2015 International Conference on Advanced Computing and Communication Systems, Coimbatore, 1-5. https://doi.org/10.1109/ICACCS.2015.7324134

  43. Kaur B (2020) Iris spoofing detection using discrete orthogonal moments. Multimedia Tools and Applications 79(9):6623–6647. https://doi.org/10.1007/s11042-019-08281-x

  44. Kaur B, Singh S, Kumar J (2019) Cross-sensor iris spoofing detection using orthogonal features. Computers & Electrical Engineering 73:279–288. https://doi.org/10.1016/j.compeleceng.2018.12.002

  45. Kohli N, Yadav D, Vatsa M, Singh R (2013) Revisiting iris recognition with color cosmetic contact lenses. 2013 International Conference on Biometrics (ICB), Madrid, 2013, pp. 1-7. https://doi.org/10.1109/ICB.2013.6613021

  46. Kohli N, Yadav D, Vatsa M, Singh R, Noore A (2016) "Detecting medley of iris spoofing attacks using DESIST," 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), Niagara Falls, NY, 1-6. https://doi.org/10.1109/BTAS.2016.7791168

  47. Komogortsev OV, Karpov A (2013) Liveness detection via oculomotor plant characteristics: attack of mechanical replicas. In 2013 international conference on biometrics (ICB): 1-8

  48. Krupinski R, Mazurek P (2012) Estimation of Electrooculography and Blinking Signals Based on Filter Banks. In: Bolc L, Tadeusiewicz R, Chmielewski LJ, Wojciechowski K (eds) Computer Vision and Graphics. ICCVG 2012. Lecture Notes in Computer Science, vol 7594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33564-8_19

  49. Lee EC, Park KR (2010) Fake iris detection based on 3D structure of iris pattern. International Journal of Imaging Systems and Technology 20(2):162–166

  50. Lee EC, Park KR, Kim J (2006) Fake iris detection by using purkinje image. In international conference on biometrics. Springer, Berlin, pp 397–403

    Google Scholar 

  51. Lee SJ, Park K, Lee YJ, Bae K, Kim JH (2007) Multifeature-based fake iris detection method. Optical Engineering 46(12):127204

  52. Lee E, Ko Y, Park K (2008) Fake iris detection method using Purkinje images based on gaze position. Optical Engineering 47(6):067204

  53. Liu M, Zhou Z, Shang P, Xu D (2019) Fuzzified image enhancement for deep learning in iris recognition. IEEE Trans Fuzzy Syst 28(1):92–99

    Article  Google Scholar 

  54. Long M, Zeng Y (2019) Detecting iris liveness with batch normalized convolutional neural network. Comput Mater Continua 58(2):493–504

    Article  Google Scholar 

  55. Manjani I, Tariyal S, Vatsa M, Singh R, Majumdar A (2017) Detecting silicone mask-based presentation attack via deep dictionary learning. IEEE Trans Information Forensics Secur 12(7):1713–1723

    Article  Google Scholar 

  56. Menotti D, Chiachia G, Pinto A, Schwartz WR, Pedrini H, Falcao AX, Rocha A (2015) Deep representations for iris, face, and fingerprint spoofing detection. IEEE Trans Inform Forensics Secur 10(4):864–879

    Article  Google Scholar 

  57. Nguyen DT, Pham TD, Lee YW, Park KR (2018) Deep learning-based enhanced presentation attack detection for iris recognition by combining features from local and global regions based on NIR camera sensor. Sensors 18(8):2601

    Article  Google Scholar 

  58. Nosaka R, Ohkawa Y, Fukui K (2011) Feature extraction based on co-occurrence of adjacent local binary patterns. In Pacific-Rim Symposium on Image and Video Technology:82-91

  59. Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on pattern analysis and machine intelligence 24(7):971–987

  60. Ojansivu V, Rahtu E, Heikkila J (2008) Rotation invariant local phase quantization for blur insensitive texture analysis. In 2008 19th international conference on pattern recognition :1-4

  61. Pala F, Bhanu B (2017) Iris liveness detection by relative distance comparisons. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops:162–169

  62. Park, JH, Kang MG (2005) Iris recognition against counterfeit attack using gradient based fusion of multi-spectral images. Paper presented at the International Workshop on Biometric Person Authentication

  63. Pinto A, Pedrini H, Krumdick M, Becker B, Czajka A, Bowyer KW, Rocha A (2018) Counteracting presentation attacks in face, fingerprint, and iris recognition. Deep Learning in Biometrics, 245

  64. Puhan NB, Sudha N, Hegde S (2011) A new iris liveness detection method against contact lens spoofing. In 2011 IEEE 15th International Symposium on Consumer Electronics (ISCE) :71–74

  65. Raghavendra R, Busch C (2014) Presentation attack detection on visible spectrum iris recognition by exploring inherent characteristics of light field camera. In IEEE International Joint Conference on Biometrics:1-8

  66. Raghavendra R, Busch C (2014) Presentation attack detection algorithm for face and iris biometrics. In 2014 22nd European signal processing conference (EUSIPCO) (pp. 1387-1391). IEEE

  67. Raghavendra R, Busch C (2015) Robust scheme for iris presentation attack detection using multiscale binarized statistical image features. IEEE Transactions on Information Forensics and Security 10(4):703–715

  68. Raghavendra R, Raja KB, Busch C (2014) Ensemble of statistically independent filters for robust contact lens detection in iris images. In Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing (pp. 1-7)

  69. Raja KB, Raghavendra R, Busch C (2015) Video presentation attack detection in visible spectrum iris recognition using magnified phase information. IEEE Transactions on Information Forensics and Security 10(10):2048–2056

  70. Raja KB, Raghavendra R, Busch C (2015) "Presentation attack detection using Laplacian decomposed frequency response for visible spectrum and Near-Infra-Red iris systems," 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS), Arlington, VA, 1-8. https://doi.org/10.1109/BTAS.2015.7358790

  71. Rigas I, Komogortsev OV (2014) "Gaze estimation as a framework for iris liveness detection," IEEE International Joint Conference on Biometrics, Clearwater, FL, 1-8. https://doi.org/10.1109/BTAS.2014.6996282

  72. Rigas I, Komogortsev OV (2015) Eye movement-driven defense against iris print-attacks. Pattern Recognition Letters 68:316–326. https://doi.org/10.1016/j.patrec.2015.06.011

  73. Ruiz-Albacete V, Tome-Gonzalez P, Alonso-Fernandez F, Galbally J, Fierrez J, Ortega-Garcia J (2008) Direct Attacks Using Fake Images in Iris Verification. In: Schouten B, Juul NC, Drygajlo A, Tistarelli M (eds) Biometrics and Identity Management. BioID 2008. Lecture Notes in Computer Science, vol 5372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89991-4_19

  74. Sequeira AF, Oliveira HP, Monteiro JC, Monteiro JP, Cardoso JS (2014) "MobILive 2014 - Mobile Iris Liveness Detection Competition," IEEE International Joint Conference on Biometrics, Clearwater, FL, pp. 1-6. https://doi.org/10.1109/BTAS.2014.6996290

  75. Sequeira AF, Thavalengal S, Ferryman J, Corcoran P, Cardoso JS (2016) A realistic evaluation of iris presentation attack detection. In 2016 39th international conference on telecommunications and signal processing (TSP): 660-664

  76. Silva P, Luz E, Baeta R, Pedrini H, Falcao AX, Menotti D (2015) "An Approach to Iris Contact Lens Detection Based on Deep Image Representations," 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images, Salvador, 157-164. https://doi.org/10.1109/SIBGRAPI.2015.16

  77. Singh YN, Singh SK (2011) Vitality detection from biometrics: state-of-the-art. In 2011 World Congress on Information and Communication Technologies:106-111

  78. Tola E, Lepetit V, Fua P (2010) DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(5):815–830. https://doi.org/10.1109/TPAMI.2009.77

  79. Wei Z, Qiu X, Sun Z, Tan T (2008) "Counterfeit iris detection based on texture analysis," 2008 19th International Conference on Pattern Recognition, Tampa, FL, pp 1-4. https://doi.org/10.1109/ICPR.2008.4761673

  80. Yadav D, Kohli N, Doyle JS, Singh R, Vatsa M, Bowyer KW (2014) Unraveling the effect of textured contact lenses on iris recognition. IEEE Trans Inform Forensics Secur 9(5):851–862

    Article  Google Scholar 

  81. Yambay D, Walczak B, Schuckers S, Czajka A (2017) LivDet-Iris 2015 – Iris Liveness Detection. In IEEE International Conference on Identity, Security and Behavior Analysis, 1–6

  82. Yambay D, Becker B, Kohli N, Yadav D, Czajka A, Bowyer KW, . . . Tan T (2017) LivDet iris 2017 — Iris liveness detection competition 2017. Paper presented at the 2017 IEEE International Joint Conference on Biometrics (IJCB)

  83. Yambay D, Becker B, Kohli N, Yadav D, Czajka A, Bowyer KW, ..., Gragnaniello D (2017) LivDet iris 2017—Iris liveness detection competition 2017. In 2017 IEEE International Joint Conference on Biometrics (IJCB):733–741

  84. Zhang H, Sun Z, Tan T (2010) "Contact Lens Detection Based on Weighted LBP," 2010 20th International Conference on Pattern Recognition, Istanbul, 4279-4282. https://doi.org/10.1109/ICPR.2010.1040

  85. Zhang H, Sun Z, Tan T, Wang J (2011) Learning hierarchical visual codebook for iris liveness detection. In International Joint Conference on Biometrics (Vol. 1)

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering & Applications, GLA University, Mathura, 281406, India

    Rohit Agarwal & Anand Singh Jalal

Authors
  1. Rohit Agarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anand Singh Jalal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anand Singh Jalal.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agarwal, R., Jalal, A.S. Presentation attack detection system for fake Iris: a review. Multimed Tools Appl 80, 15193–15214 (2021). https://doi.org/10.1007/s11042-020-10378-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-020-10378-7

Keywords

Search

Navigation