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Presentation Attacks in Signature Biometrics: Types and Introduction to Attack Detection

  • Ruben TolosanaEmail author
  • Ruben Vera-Rodriguez
  • Julian Fierrez
  • Javier Ortega-Garcia
Chapter
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Abstract

Authentication applications based on the use of biometric methods have received a lot of interest during the last years due to the breathtaking results obtained using personal traits such as face or fingerprint. However, it is important not to forget that these biometric systems have to withstand different types of possible attacks. This work carries out an analysis of different Presentation Attack (PA) scenarios for on-line handwritten signature verification. The main contributions of the present work are: (1) short overview of representative methods for Presentation Attack Detection (PAD) in signature biometrics; (2) to describe the different levels of PAs existing in on-line signature verification regarding the amount of information available to the attacker, as well as the training, effort and ability to perform the forgeries; and (3) to report an evaluation of the system performance in signature biometrics under different PAs and writing tools considering freely available signature databases. Results obtained for both BiosecurID and e-BioSign databases show the high impact on the system performance regarding not only the level of information that the attacker has but also the training and effort performing the signature. This work is in line with recent efforts in the Common Criteria standardization community towards security evaluation of biometric systems, where attacks are rated depending on, among other factors, time spent, effort and expertise of the attacker, as well as the information available and used from the target being attacked.

Notes

Acknowledgements

This work has been supported by projects: Bio-Guard (Ayudas Fundación BBVA a Equipos de Investigación Científica 2017), UAM-CecaBank, and by TEC2015-70627-R (MINECO/FEDER). Ruben Tolosana is supported by a FPU Fellowship from the Spanish MECD.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ruben Tolosana
    • 1
    Email author
  • Ruben Vera-Rodriguez
    • 1
  • Julian Fierrez
    • 2
  • Javier Ortega-Garcia
    • 1
  1. 1.Biometrics and Data Pattern Analytics - BiDA LabEscuela Politecnica Superior, Universidad Autonoma de MadridMadridSpain
  2. 2.Universidad Autonoma de MadridMadridSpain

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