http://iet.metastore.ingenta.com
1887

On application of bloom filters to iris biometrics

On application of bloom filters to iris biometrics

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Biometrics — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In this study, the application of adaptive Bloom filters to binary iris biometric feature vectors, that is, iris-codes, is proposed. Bloom filters, which have been established as a powerful tool in various fields of computer science, are applied in order to transform iris-codes to a rotation-invariant feature representation. Properties of the proposed Bloom filter-based transform concurrently enable (i) biometric template protection, (ii) compression of biometric data and (iii) acceleration of biometric identification, whereas at the same time no significant degradation of biometric performance is observed. According to these fields of application, detailed investigations are presented. Experiments are conducted on the CASIA-v3 iris database for different feature extraction algorithms. Confirming the soundness of the proposed approach, the application of adaptive Bloom filters achieves rotation-invariant cancellable templates maintaining biometric performance, a compression of templates down to 20–40% of original size and a reduction of bit-comparisons to less than 5% leading to a substantial speed-up of the biometric system in identification mode.

References

    1. 1)
      • 1. Daugman, J.: ‘High confidence visual recognition of persons by a test of statistical independence’, IEEE Trans. Pattern Anal. Mach. Intell., 1993, 15, (11), pp. 11481161 (doi: 10.1109/34.244676).
    2. 2)
      • 2. Bowyer, K., Hollingsworth, K., Flynn, P.: ‘Image understanding for iris biometrics: a survey’, Comput. Vis. Image Underst., 2007, 110, (2), pp. 281307 (doi: 10.1016/j.cviu.2007.08.005).
    3. 3)
      • 3. Rathgeb, C., Uhl, A., Wild, P.: ‘Iris biometrics: from segmentation to template securityNumber 59 in Advances in Information Security. (Springer, 2012).
    4. 4)
      • 4. Daugman, J.: ‘Iris recognition at airports and border-crossings’. In: Li, S.Z. (ed):‘Encyclopedia of biometrics’ (Springer, 2009).
    5. 5)
      • 5. Ross, A.: ‘Iris recognition: the path forward’, Computer, 2001, 43, pp. 3035 (doi: 10.1109/MC.2010.44).
    6. 6)
      • 6. Daugman, J.: ‘How iris recognition works’, IEEE Trans. Circuits Syst. Video Technol., 2004, 14, (1), pp. 2130 (doi: 10.1109/TCSVT.2003.818350).
    7. 7)
      • 7. Unique Identification Authority of India. Aadhaar: http://www.uidai.gov.in/. retrieved March, 2013.
    8. 8)
      • 8. Cimato, S., Gamassi, M., Piuri, V., Sassi, R., Scotti, F.: ‘Privacy in biometrics’ ‘Biometrics: fundamentals, theory, and systems’ (Wiley, 2009).
    9. 9)
      • 9. Venugopalan, S., Savvides, M.: ‘How to generate spoofed irises from an iris code template’, IEEE Trans. Inf. Forensics Sec., 2011, 6, (2), pp. 385395 (doi: 10.1109/TIFS.2011.2108288).
    10. 10)
      • 10. ISO/IEC JTC1 SC27 Security Techniques. ISO/IEC 24745:2011. Information Technology – Security Techniques – Biometric Information Protection. International Organization for Standardization, 2011.
    11. 11)
      • 11. Jain, A.K., Nandakumar, K., Nagar, A.: ‘Biometric template security’, EURASIP J. Adv. Signal Process., 2008, 2008, pp. 117 (doi: 10.1155/2008/657081).
    12. 12)
      • 12. Rathgeb, C., Uhl, A.: ‘A survey on biometric cryptosystems and cancelable biometrics’, EURASIP J. Inf. Sec., 2011, 2011, (3), pp. 125.
    13. 13)
      • 13. Ratha, N., Connell, J., Bolle, R.: ‘Enhancing security and privacy in biometrics-based authentication systems’, IBM Syst. J., 2001, 40, (3), pp. 614634 (doi: 10.1147/sj.403.0614).
    14. 14)
      • 14. Daugman, J.: ‘The importance of being random: statistical principles of iris recognition’, Pattern Recognition, 2003, 36, (2), pp. 279291 (doi: 10.1016/S0031-3203(02)00030-4).
    15. 15)
      • 15. Hollingsworth, K.P., Bowyer, K.W., Flynn, P.J.: ‘The best bits in an iris code’, IEEE Trans. Pattern Anal. Mach. Intell., 2009, 31, (6), pp. 964973 (doi: 10.1109/TPAMI.2008.185).
    16. 16)
      • 16. Gentile, J.E., Ratha, N., Connell, J.: ‘SLIC: short-length iris codes’. Proc. IEEE Third Int. Conf. on Biometrics: Theory, Applications, and Systems, 2009, pp. 15.
    17. 17)
      • 17. Gentile, J.E., Ratha, N., Connell, J.: ‘An efficient, two-stage iris recognition system’. Proc. IEEE Third Int. Conf. on Biometrics: Theory, Applications, and Systems, 2009, pp. 15.
    18. 18)
      • 18. Konrad, M., Stögner, H., Uhl, A., Wild, P.: ‘Computationally efficient serial combination of rotation-invariant and rotation compensating iris recognition algorithms’. Proc. Fifth Int. Conf. on Computer Vision Theory and Applications, 2010, vol. 1, pp. 8590.
    19. 19)
      • 19. Bloom, B.: ‘Space/time tradeoffs in hash coding with allowable errors’, Commun. ACM, 1970, 13, (7), pp. 422426 (doi: 10.1145/362686.362692).
    20. 20)
      • 20. Mullin, J.: ‘Optimal semijoins for distributed database systems’, IEEE Trans. Softw. Eng., 1990, 16, (5), pp. 558560 (doi: 10.1109/32.52778).
    21. 21)
      • 21. Broder, A., Mitzenmacher, M.: ‘Network applications of bloom filters: a survey’, Internet Math., 2005, 1, (4), pp. 485509 (doi: 10.1080/15427951.2004.10129096).
    22. 22)
      • 22. Rathgeb, C., Breitinger, F., Busch, C.: ‘Alignment-free cancelable Iris biometric templates based on adaptive bloom filters’. Proc. Sixth IAPR Int. Conf. on Biometrics (ICB'13), 2013, pp. 18.
    23. 23)
      • 23. Juels, A., Wattenberg, M.: ‘A fuzzy commitment scheme’. Proc. Sixth ACM Conf. on Computer and Communications Security, 1999, pp. 2836.
    24. 24)
      • 24. Juels, A., Sudan, M.: ‘A fuzzy vault scheme’. Proc. IEEE Int. Symp. on Information Theory, 2002, p. 408.
    25. 25)
      • 25. Hao, F., Anderson, R., Daugman, J.: ‘Combining cryptography with biometrics effectively’, IEEE Trans. Comput., 2006, 55, (9), pp. 10811088 (doi: 10.1109/TC.2006.138).
    26. 26)
      • 26. Bringer, J., Chabanne, H., Cohen, G., Kindarji, B., Zemor, G.: ‘Theoretical and practical boundaries of binary secure sketches’, IEEE Trans. Inf. Forensics Sec., 2008, 3, pp. 673683 (doi: 10.1109/TIFS.2008.2002937).
    27. 27)
      • 27. Lee, C., Choi, J., Toh, K., Lee, S., Kim, J.: ‘Alignment-free cancelable fingerprint templates based on local minutiae information’, IEEE Trans. Syst. Man Cybern. B, Cybern., 2007, 37, (4), pp. 980992 (doi: 10.1109/TSMCB.2007.896999).
    28. 28)
      • 28. Rathgeb, C., Uhl, A.: ‘Statistical attack against fuzzy commitment scheme’, IET Biometrics, 2012, 1, (2), pp. 94104 (doi: 10.1049/iet-bmt.2011.0001).
    29. 29)
      • 29. Scheirer, W., Boult, T.: ‘Cracking fuzzy vaults and biometric encryption’. Proc. Biometrics Symp., 2007, pp. 16.
    30. 30)
      • 30. Zuo, J., Ratha, N.K., Connel, J.H.: ‘Cancelable iris biometric’. Proc. 19th Int. Conf. on Pattern Recognition, 2008, pp. 14.
    31. 31)
      • 31. Hämmerle-Uhl, J., Pschernig, E., Uhl, A.: ‘Cancelable iris biometrics using block re-mapping and image warping’. in: Samarati, P., Yung, M., Martinelli, F., Ardagna, C., (Eds.), Proc. 12th Int. Information Security Conf., 2009(LNCS, 5735), pp. 135142.
    32. 32)
      • 32. Ouda, O., Tsumura, N., Nakaguchi, T.: ‘Tokenless cancelable biometrics scheme for protecting iris codes’. Proc. 20th Int. Conf. on Pattern Recognition, 2010, pp. 882885.
    33. 33)
      • 33. Kong, A., Cheunga, K.-H., Zhanga, D., Kamelb, M., Youa, J.: ‘An analysis of BioHashing and its variants’, Pattern Recognit., 2006, 39, (7), pp. 13591368 (doi: 10.1016/j.patcog.2005.10.025).
    34. 34)
      • 34. Pillai, J.K., Patel, V.M., Chellappa, R., Ratha, N.K.: ‘Secure and robust iris recognition using random projections and sparse representations’, IEEE Trans. Pattern Anal. Mach. Intell., 2011, 33, (9), pp. 18771893 (doi: 10.1109/TPAMI.2011.34).
    35. 35)
      • 35. Chong, S.C., Jin, A.T.B., Ling, D.N.C.: ‘High security iris verification system based on random secret integration’, Comput. Vis. Image Underst., 2006, 102, (2), pp. 169177 (doi: 10.1016/j.cviu.2006.01.002).
    36. 36)
      • 36. Chong, S.C., Jin, A.T.B., Ling, D.N.C.: ‘Iris authentication using privatized advanced correlation filter’. in: Zhang, D., Jain, A. (Eds.), Proc. First Int. Conf. on Biometrics, 2006,(LNCS, 3832), pp. 382388.
    37. 37)
      • 37. Hao, F., Daugman, J., Zielinski, P.: ‘A fast search algorithm for a large fuzzy database’, IEEE Trans. Inf. Forensics Sec., 2008, 3, (2), pp. 203212 (doi: 10.1109/TIFS.2008.920726).
    38. 38)
      • 38. Mukherjee, R., Ross, A.: ‘Indexing iris images’. Proc. 19th Int. Conf. on Pattern Recognition (ICPR'08), 2008, pp. 14.
    39. 39)
      • 39. Rathgeb, C., Uhl, A.: ‘Iris-biometric hash generation for biometric database indexing’. Proc. 20th Int. Conf. on Pattern Recognition, 2010, pp. 28482851.
    40. 40)
      • 40. Rathgeb, C., Uhl, A., Wild, P.: ‘Incremental iris recognition: a single-algorithm serial fusion strategy to optimize time complexity’. Proc. IEEE Fourth Int. Conf. on Biometrics: Theory, Applications, and Systems, 2010, pp. 16.
    41. 41)
      • 41. Masek, L.: ‘Recognition of human iris patterns for biometric identification’. Master's thesis, University of Western Australia, 2003.
    42. 42)
      • 42. ISO/IEC TC JTC1 SC37 Biometrics. ISO/IEC 19795-1:2006. Information Technology – Biometric Performance Testing and Reporting – Part 1: Principles and Framework. International Organization for Standardization and International Electrotechnical Committee, Mar. 2006.
    43. 43)
      • 43. Uhl, A., Wild, P.: ‘Weighted adaptive hough and ellipsopolar transforms for real-time iris segmentation’. Proc. Fifth Int. Conf. on Biometrics, 2012, pp. 18.
    44. 44)
      • 44. Ma, L., Tan, T., Wang, Y., Zhang, D.: ‘Efficient iris recognition by characterizing key local variations’, IEEE Trans. Image Process., 2004, 13, (6), pp. 739750 (doi: 10.1109/TIP.2004.827237).
    45. 45)
      • 45. Viveros, R., Balasubramanian, K., Balakrishnan, N.: ‘Binomial and negative binomial analogues under correlated Bernoulli trials’, Am. Stat., 1984, 48, (3), pp. 243247.
    46. 46)
      • 46. Maiorana, E.: ‘Biometric cryptosystem using function based on-line signature recognition’, Expert Syst. Appl., 2010, 37, (4), pp. 34543461 (doi: 10.1016/j.eswa.2009.10.043).
    47. 47)
      • 47. Daugman, J.: ‘Probing the uniqueness and randomness of iriscodes: results from 200 billion iris pair comparisons’, Proc. IEEE, 2006, 94, (11), pp. 19271935 (doi: 10.1109/JPROC.2006.884092).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-bmt.2013.0049
Loading

Related content

content/journals/10.1049/iet-bmt.2013.0049
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address