t-EER: Parameter-Free Tandem Evaluation of Countermeasures and Biometric Comparators

Tomi H. Kinnunen, Kong Aik Lee, Hemlata Tak, Nicholas Evans, Andreas Nautsch

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Presentation attack (spoofing) detection (PAD) typically operates alongside biometric verification to improve reliablity in the face of spoofing attacks. Even though the two sub-systems operate in tandem to solve the single task of reliable biometric verification, they address different detection tasks and are hence typically evaluated separately. Evidence shows that this approach is suboptimal. We introduce a new metric for the joint evaluation of PAD solutions operating in situ with biometric verification. In contrast to the tandem detection cost function proposed recently, the new tandem equal error rate (t-EER) is parameter free. The combination of two classifiers nonetheless leads to a set of operating points at which false alarm and miss rates are equal and also dependent upon the prevalence of attacks. We therefore introduce the concurrent t-EER, a unique operating point which is invariable to the prevalence of attacks. Using both modality (and even application) agnostic simulated scores, as well as real scores for a voice biometrics application, we demonstrate application of the t-EER to a wide range of biometric system evaluations under attack. The proposed approach is a strong candidate metric for the tandem evaluation of PAD systems and biometric comparator.

Original languageEnglish
Article number10246406
Pages (from-to)2622 - 2637
Number of pages16
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume46
Issue number5
DOIs
Publication statusPublished - 1 May 2024

Keywords

  • Automatic speaker verification
  • biometrics
  • equal error rate
  • presentation attack detection
  • tandem evaluation

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Applied Mathematics
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics

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