Evaluation of multimodal biometric score fusion rules under spoof attacks

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How researchers see this paper

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Robust multimodal face and fingerprint fusion in the presence of spoofing attacks (2016, background): “Multibiometrics using face and fingerprint biometrics comes with many benefits including expected increased accuracy, higher universality (absence of single characteristics), efficiency (fast indexing), but its robustness to spoofing attempts has been shown to be compromised [8,9].”
Towards anomaly detection for increased security in multibiometric systems: Spoofing-resistant 1-median fusion eliminating outliers (2014, background): “Table 1 lists results for (1) the reference fusion rules sum and - augmenting evaluations [6, 3, 1] - median rule, (2) the proposed median filtering using scores only, and (3) 1median filtering of score and liveness values with logistic regression classification.”
Security evaluation of biometric authentication systems under real spoofing attacks (2012, background): “This is part of the authors’ ongoing work [3, 2].”