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 [BibTeX] [Marc21]
Anti-spoofing in action: joint operation with a verification system
Type of publication: Conference paper
Publication status: Accepted
Booktitle: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Workshop on Biometrics
Year: 2013
Month: June
Location: Portland, Oregon
Crossref: Chingovska_Idiap-RR-19-2013:
Abstract: Besides the recognition task, today's biometric systems need to cope with additional problem: spoofing attacks. Up to date, academic research considers spoofing as a binary classification problem: systems are trained to discriminate between real accesses and attacks. However, spoofing counter-measures are not designated to operate stand-alone, but as a part of a recognition system they will protect. In this paper, we study techniques for decision-level and score-level fusion to integrate a recognition and anti-spoofing systems, using an open-source framework that handles the ternary classification problem (clients, impostors and attacks) transparently. By doing so, we are able to report the impact of different spoofing counter-measures, fusion techniques and thresholding on the overall performance of the final recognition system. For a specific use-case covering face verification, experiments show to what extent simple fusion improves the trustworthiness of the system when exposed to spoofing attacks.
Keywords: biometric recognition, Counter-Measures, Fusion, Spoofing, trustworthy, vulnerability
Projects Idiap
Authors Chingovska, Ivana
Anjos, André
Marcel, Sébastien
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Total mark: 0