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Introduction

  • Nesli ErdoğmuşEmail author
  • Sébastien Marcel
Chapter
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

In a well-designed system, biometric security ensures that only authorized persons can access to the protected facility or information, because it assesses a person’s most unique physical and behavioural features that can be practically sensed by devices and interpreted by computers. It is also convenient as the users need to carry or remember identification data is eliminated. Mainly driven by the biometrics passports that are currently in use in many countries, more and more biometric-enabled applications are used in daily life. However, despite a stimulating and rapidly growing market, a crucial security issue is still to be considered by concerning parties: vulnerability to attacks, in other words, attempts to subvert and circumvent the system.

It has been shown recently that conventional biometric techniques, such as fingerprint or face recognition are prone to one of the most potent and damaging threats involving personal Data-Identity fraud, mostly known as spoofing.

Spoofing,...

Keywords

Speaker Recognition Biometric System False Acceptance Rate Face Recognition System Biometric Trait 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to thank the TABULA RASA (http://www.tabularasa-euproject.org) and BEAT projects (http://www.beat-eu.org) funded under the 7th Framework Programme of the European Union (EU) (grant agreement numbers 257289 and 284989) and the Swiss Center for Biometrics Research and Testing (http://www.biometrics-center.ch) for their support.

References

  1. 1.
    Lyons M (1994) Napoleon Bonaparte and the legacy of the French Revolution. Macmillan, LondonGoogle Scholar
  2. 2.
    UNFPA (2011) State of world population 2011–people and possibilities in a world of 7 billion. UN Report. http://www.unfpa.org/public/home/publications/pid/8726
  3. 3.
    UNWTO (2014) International tourism exceeds expectations with arrivals up by 52 million in 2013. Press Release 14004. http://media.unwto.org/press-release/2014-01-20/international-tourism-exceeds-expectations-arrivals-52-million-2013
  4. 4.
    Paullin CO, Wright JK (1932) Atlas of the historical geography of the united states. Carnegie Institution of Washington, WashingtonGoogle Scholar
  5. 5.
    Herley C (2009) So long, and no thanks for the externalities: the rational rejection of security advice by users. In: Workshop on new security paradigms workshop, ACM pp 133–144Google Scholar
  6. 6.
    Information security survey (2003). In: Infosecurity EuropeGoogle Scholar
  7. 7.
    Ratha NK, Connell JH, Bolle RM (2001) An analysis of minutiae matching strength. Audio-and video-based biometric person authentication. Springer, BerlinGoogle Scholar
  8. 8.
    Jain AK, Ross AA (2011) Security of biometric systems. Introduction to biometrics. Springer, Berlin, pp 259–306Google Scholar
  9. 9.
    Matsumoto T, Matsumoto H, Yamada K, Hoshino S (2002) Impact of artificial gummy fingers on fingerprint systems. In: Electronic imaging 2002, international society for optics and photonics, pp 275–289Google Scholar
  10. 10.
    Duc NM, Minh BQ (2009) Your face is not your password face authentication bypassing lenovo-asus-toshiba. Black Hat BriefingsGoogle Scholar
  11. 11.
    Doctor ’used silicone fingers’ to sign in for colleagues. www.bbc.com/news/world-latin-america-21756709. Accessed 09 Apr 2014
  12. 12.
    Yen portraits fool age-verification cameras. http://pinktentacle.com/2008/07/yen-portraits-fool-age-verification-cameras/. Accessed 09 Apr 2014
  13. 13.
    Woman fools japan’s airport security fingerprint system. www.smh.com.au/travel/woman-fools-japans-airport-security-fingerprint-system-20090102-78rv.html. Accessed 09 Apr 2014
  14. 14.
    V-series sensors. www.lumidigm.com. Accessed 17 Apr 2014
  15. 15.
    Huang X, Ti C, zhen Hou Q, Tokuta A, Yang R (2013) An experimental study of pupil constriction for liveness detection. In: IEEE workshop on applications of computer vision (WACV), pp 252–258. doi: 10.1109/WACV.2013.6475026
  16. 16.
    Rattani A, Poh N, Ross A (2013) A bayesian approach for modeling sensor influence on quality, liveness and match score values in fingerprint verification. In: International workshop on information forensics and security (WIFS), IEEE. pp 37–42Google Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Idiap Research InstituteMartignySwitzerland

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