NDLI: Robustness analysis of likelihood ratio score fusion rule for multimodal biometric systems under spoof attacks

Content Provider	IEEE Xplore Digital Library
Author	Akhtar, Z. Fumera, G. Marcialis, G.L. Roli, F.
Copyright Year	2011
Description	Author affiliation: Dept. of Electrical and Electronic Engineering, University of Cagliari, Piazza d'Armi, 09123 Cagliari, Italy (Akhtar, Z.; Fumera, G.; Marcialis, G.L.; Roli, F.)
Abstract	Recent works have shown that, contrary to a common belief, multi-modal biometric systems may be “forced” by an impostor by submitting a spoofed biometric replica of a genuine user to only one of the matchers. Although those results were obtained under a worst-case scenario when the attacker is able to replicate the exact appearance of the true biometric, this raises the issue of investigating more thoroughly the robustness of multi-modal systems against spoof attacks and devising new methods to design robust systems against them. To this aim, in this paper we propose a robustness evaluation method which takes into account also scenarios more realistic than the worst-case one. Our method is based on an analytical model of the score distribution of fake traits, which is assumed to lie between the one of genuine and impostor scores, and is parametrised by a measure of the relative distance to the distribution of impostor scores, we name “fake strength”. Varying the value of such parameter allows one to simulate the different factors which can affect the distribution of fake scores, like the ability of the attacker to replicate a certain biometric. Preliminary experimental results on real bi-modal biometric data sets made up of faces and fingerprints show that the widely used LLR rule can be highly vulnerable to spoof attacks against one only matcher, even when the attack has a low fake strength.
Starting Page	1
Ending Page	8
File Size	831859
Page Count	8
File Format	PDF
ISBN	9781457709029
ISSN	21530742
e-ISBN	9781457709036
DOI	10.1109/CCST.2011.6095935
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-18
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Biometrics Biological system modeling Testing System performance Data models Training data
Content Type	Text
Resource Type	Article

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