Capture Biases in Fingerprint Systems

Abdarahmane Wone (1, 2) , Joël Di Manno (2) , Christophe Rosenberger (1) , Christophe Charrier (1)

1 Equipe SAFE - Laboratoire GREYC - UMR6072
2 FIME EMEA

Fingerprint recognition is a common solution for user authentication in Cybersecurity. This paper deals with the context of the certification of fingerprint biometric systems. The increasing use of biometric systems makes their certification a mandatory step in their development to assess their behavior in a real situation use. It has been shown that certain parameters such as environmental conditions can have a significant impact on the performance of biometric systems. However, there are also non-controlled parameters that depend on the user's state such as the quality of his biometric samples. In this paper, we propose a study that explores the performance of fingerprint systems across these parameters.

Mots clés: Certification of fingerprint systems; Biometrics; fingerprints; biases

Domaines: Informatique [cs]

Abdarahmane Wone, Joël Di Manno, Christophe Rosenberger, Christophe Charrier. Capture Biases in Fingerprint Systems. 2023 International Conference on Cyberworlds (CW), Oct 2023, Sousse (Tunisie), France. ⟨hal-04176199⟩