Evaluation of biometric spoofing in a multimodal system

By Ricardo Nagel Rodrigues, Niranjan Kamat, Venugopal Govindaraju. 2010

64 citations recorded by the source corpus.

Subfields: Genetics, Information Systems, Signal Processing

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Citations in the corpus

Robust multimodal face and fingerprint fusion in the presence of spoofing attacks (2016, background): “[8, 17] first addressed this security issue of spoofing attacks against a multimodal biometric system.”
Combining match scores with liveness values in a fingerprint verification system (2012, background): “While previous research has considered the problem of designing spoof-resilient fusion schemes for multibiometric systems [20], [19], [7], [10], the specific problem of combining liveness values with match scores has not been investigated.”
Biometric Antispoofing Methods: A Survey in Face Recognition (2014, background): “, circumventing a multibiometric system implies breaking all unimodal modules) has already been shown to be untrue as, in many cases, bypassing just one of the unimodal subsystems is enough to gain access to the complete application [75], [85]–[88].”
Robustness of multi-modal biometric verification systems under realistic spoofing attacks (2011, methodology): “In [15] it was argued that the worst-case assumption is reasonable for 2D face systems, as it is easy to show a picture of a genuine user in front of a camera.”
Evaluation of serial and parallel multibiometric systems under spoofing attacks (2012, methodology): “However, some recent works [13, 12, 10, 3, 5, 7] have questioned the validity of this belief, and have empirically shown that spoofing only one trait is sufficient to evade a parallel multi-modal system.”
Security evaluation of biometric authentication systems under real spoofing attacks (2012, methodology): “In fact, this hypothesis is only supported by a very limited experimental evidence reported in [28], where the distributions of some real spoofing attacks were shown to be similar to those of the “live” traits of genuine users.”
Biometrics Evaluation Under Spoofing Attacks (2014, background): “Significant publications covering this problem include [12], [13], [14].”
Increase the Security of Multibiometric Systems by Incorporating a Spoofing Detection Algorithm in the Fusion Mechanism (2011, background): “Recently, researchers demonstrated that the existing multimodal systems can be deceived also when only a subset of the fused modalities is spoofed [6].”
Anti-spoofing in Action: Joint Operation with a Verification System (2013, background): “Most notable are [21] which explores fuzzy logic, and [20] which extends the LLR scheme by introducing hidden variables denoting the probability of a spoofing attack.”
Towards anomaly detection for increased security in multibiometric systems: Spoofing-resistant 1-median fusion eliminating outliers (2014, background): “Several previous research projects have indicated the vulnerability of multimodal biometric systems against single or multiple biometric spoofing attacks [15, 14, 3, 1].”
Multi-Factor Authentication: A Survey (2018, background): “Unfortunately, a biometric spoofing attack is fairly simple to execute [179].”
Evaluation of multimodal biometric score fusion rules under spoof attacks (2012, background): “If the fused score s is below a given acceptance threshold T , the user is classified as an impostor, otherwise it is classified as a genuine user.”
A Survey on Anti-Spooﬁng Schemes for Fingerprint Recognition Systems (2014, background): “Recent investigations demonstrated that, multimodal systems can be deceived when only a subset of the fused modalities is spoofed [Rodrigues et al. 2010] [Rodrigues et al. 2009] [Akhtar et al. 2011a] [Marasco and Sansone 2011b] [Marasco 2010].”