Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지
DOI QR코드

DOI QR Code

Multi-modal Authentication Using Score Fusion of ECG and Fingerprints

  • Received : 2020.01.07
  • Accepted : 2020.05.24
  • Published : 2020.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.

Keywords

References

  1. G. Park, "Bio-signal and personal authentication," Korea Internet and Security Agency, Technical Report, Aug. 2014
  2. G. Park, "Analysis of authentication technology using bio-signals and construction of bio-signal database," Korea Internet and Security Agency, Technical Report, Jan. 2016
  3. J. Kim and G. Park, "Personal authentication technology using bio-signals and DB construction," TTA Journal, vol. 165, pp. 41-46, Mar. 2016.
  4. R. Paranjape, J. Mahovsky, L. Benedicenti, and Z. Koles, "The EEG as a biometric," in Proc. IEEE Canadian Conference on Electrical and Computer Engineering, vol. 2, pp. 1363-1366, 2001. DOI: 10.1109/CCECE.2001.933649.
  5. E. Vural, S. Simske, and S Schuckers, "Verification of individuals from accelerometer measures of cardiac chest movements," in 2013 International Conference of the BIOSIG, pp. 1-8, Sept. 2013. INSPEC Accession Number: 13826572.
  6. H. Guo, X. Cao, J. Wu, and J. Tang, "Ballistocardiogram-based person identification using correlation analysis," in IFMBE Proceedings of World Congress on Medical Physics and Biomedical Engineering, vol. 39, pp. 570-573, 2013. DOI: 10.1007/978-3-642-29305-4_149.
  7. S. Wahabi, S. Pouryayevali, S. Hari, and D. Hatzinakos, "On evaluating ECG biometric systems: Session-dependence and body posture," IEEE Transactions on Information Forensics and Security., vol. 9, no. 11, pp. 2002-2013, Nov. 2014. DOI: 10.1109/TIFS.2014.2360430.
  8. Y. N. Singh, S.K. Singh, and P. Gupta, "Fusion of electrocardiogram with unobtrusive biometrics: An efficient individual authentication system," Pattern Recognition Letters, vol. 33, no. 14, pp. 1932-1941, 2012. DOI: 10.1016/J.patrec.2012.03.010.
  9. Y. N. Singh and S.K. Singh, "Evaluation of electrocardiogram for biometric authentication," Journal of Information Security, vol. 3, no. 1, pp. 39-48, 2012. DOI: 10.4236/jis.2012.31005.
  10. R. Palaniappan, "Two-stage biometric authentication method using thought activity brain waves," International Journal of Neural Systems, vol. 18, no. 1, pp. 59-66, Feb. 2008. DOI: 10.1142/S0129065708001373.
  11. I. Traore, M. Alshahrani, M.S. Obaidat, "State of the art and perspectives on traditional and emerging biometrics: A Survey," Security and Privacy, vol. 1, no. 6, 2018. DOI: 10.1002/spy2.44.
  12. Medical Biometric Databases, University of Tronto, Available: https://www.comm.utoronto.ca/-biometrics/databases.html.
  13. M. Komeili, N. Armanfard, D. Hatzinakos, and A.N.V. Venetsanopoulos, "Feature selection from multisession electrocardiogram signals for identity verification," in IEEE 28th Canadian Conference in Electrical and Computer Engineering, (CCECE'2015), Halifax, NS, pp. 603-608, 05-2015. DOI: 10.1109/CCECE.2015.7129343.
  14. W. Louis and D. Hatzinakos, "Enhanced binary patterns for electrocardiogram (ECG) biometrics," in IEEE 29th Canadian Conference on Electrical and Computer Engineering (CCECE'2016), Vancouver, BC, May 2016. DOI: 10.1109/CCECE.2016.7726725.
  15. M. Komeili, W. Louis, N. Armanfard, and D. Hatzinakos, "On evaluating human recognition using electrocardiogram signals: from rest to exercise," in IEEE 29th Canadian Conference on Electrical and Computer Engineering (CCECE'2016), Vancouver, BC, May 2016. DOI: 10.1109/CCECE.2016.7726726.
  16. W. Louis, M. Komeili, and D. S. Hatzinakos, "Continuous authentication using one-dimensional multi-resolution local binary patterns (1DMRLBP) in ECG biometrics," IEEE Transactions on Information Forensics and Security, vol. 11, no. 12, pp. 2818-2832, December 2016. DOI: 10.1109/TIFS.2016.2599270.
  17. J. Kim, S. Lee, B. Kim, and S. Lee, "Standardization trend of nonface-to-face authentication technology based on tele-biometrics," Korea Institute of Information Security & Cryptology, vol. 25, no. 4, pp. 43-50, Aug. 2015.
  18. J. Kim, "Recommendation of X.tif, integrated framework for telebiometric data protection in e-health and worldwide telemedicine," ITU-T SG17 Q9, Aug. 2013.
  19. ISO/IEC 19794-2: 2005 Information technology - Biometric data interchange formats - Part 2: Finger Minutiae Data https://www.iso.org/standard/38746.html.
  20. P. Grother et al., MINEX Performance and Interoperability of the INCITS 378 Fingerprint Template, NISTIR 7296, 2006. https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=150619.
  21. P. Grother et al., Biometric Specification for Personal Identity Verification, NIST Special Publication 800-76-2, July 2013. https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-76-2.pdf.
  22. B. Kohler, C. Hennig, and R. Orglmeister, "The principles of software QRS detection," IEEE Engineering in Medicine and Biology Magazine, vol. 21, no. 1, pp. 42-57, Jan./Feb. 2002. https://doi.org/10.1109/51.993193
  23. J. Arteaga-Falconi, H. Al Osman, and A. El Saddik, "R-peak detection algorithm based on differentiation," Proc. IEEE 9th International Symposium on Intelligent Signal Processing (WISP), May 2015, pp. 1-4.
  24. S. Israel, J. Irvine, A. Cheng, M. Wiederhold, and B.. Wiederhold, "ECG to identify individuals," Pattern Recognition, vol. 38, no. 1, pp. 133-142, Jan. 2005. https://doi.org/10.1016/j.patcog.2004.05.014
  25. R. Tan and M. Perkowski, "Toward improving electrocardiogram (ECG) biometric verification using mobile sensors: A two-stage classifier approach. Sensors, vol. 17, no. 2, p. 410, 2017. Available: http://www.ncbi.nlm.nih.gov/pubmed/28230745. https://doi.org/10.3390/s17020410
  26. Nymi, Always On Authentication,, Available: https://nymi.com/.
  27. P. Shahrzad, S. Wahabi, S. Hari, and D. Hatzinakos, "On establishing evaluation standards for ECG biometrics," 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), p. 3774-3778, 2014. Available: http://ieeexplore.ieee.org/document/6854307/.
  28. K. Plataniotis, D. Hatzinakos, and J. Lee, "ECG Biometric Recognition Without Fiducial Detection," 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, pp. 1-6. Available: http://ieeexplore.ieee.org/document/4341628/.
  29. S. Wahabi, P. Shahrzad, S. Hari, and D. Hatzinakos, "On evaluating ECG biometric systems: Session-dependence and body posture," IEEE Transactions on Information Forensics and Security, vol. 9, no. 11, pp. 2002-2013, 2014. https://doi.org/10.1109/TIFS.2014.2360430
  30. F. Agrafioti, "ECG in biometric recognition: Time Dependency and application challenges," ProQuest Diss. Theses, 2011; NR93098:189. Available: http://ezproxy.net.ucf.edu/login?url=http://search.proquest.com/docview/1330569834?accountid=10003%5Cnhttp://sfx.fcla.edu/ucf?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&genre=dissertations+&+theses&sid=ProQ:ProQuest+Dissertations+&+.
  31. O. Boumbarov, Y. Velchev, K. Tonchev, and I. Paliy, "Face and ECG based multi-modal biometric authentication," in Advanced Biometric Technologies (Book chapter), InTech August 2011. DOI: 10.5772/21842.
  32. C. Watson, G. Fiumara, E. Tabassi, W. Salamon, and P. Flanagan, Fingerprint vendor technology evaluation, NIST, 2014, Available: http://nvlpubs.nist.gov/nistpubs/ir/2014/NIST.IR.8034.pdf.