LivDet 2017 - Fingerprint Systems Liveness Detection Competition

Yambay, David; Schuckers, Stephanie; Denning, Samantha K.; Sandmann, Constantin; Bachurinski, Andrey; Hogan, Josh

doi:10.1109/btas.2018.8698578

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…The number of submitted systems remained low for the LivDet Systems competition until the 2017 competition which saw a drastic rise in the amount of competitors (Table 5). Starting from the two presented in LivDet 2011, in 2017, there were a total of 14 submitted system to the two sub-competition: nine systems submitted (with a 10th unofficial submission) for the PAD only competition and five for the integrated PAD and matcher systems competition [27].…”

Section: Livdet Systems Resultsmentioning

confidence: 99%

“…Each submission includes a fully packaged fingerprint system with software installation. The systems were equipped with only a liveness module until the 2017 edition [27], in which we also accepted integrated systems, with enrollment, matching and liveness modules. A system outputs a score between 0-100 representing liveness or 0-100 for match scores.…”

Section: Livdet Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Review of the Fingerprint Liveness Detection (LivDet) competition series: from 2009 to 2021

Micheletto¹,

Orrù²,

Casula³

et al. 2022

Preprint

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Fingerprint authentication systems are highly vulnerable to fingerprint artificial reproductions, called fingerprint presentation attacks. Detecting presentation attacks is not trivial because attackers refine their replication techniques from year to year. The International Fingerprint liveness Detection Competition (LivDet), an open and well-acknowledged meeting point of academies and private companies that deal with the problem of presentation attack detection, has the goal to assess the performance of fingerprint presentation attack detection (FPAD) algorithms by using standard experimental protocols and data sets. Each LivDet edition, held biannually since 2009, is characterized by a different set of challenges to which the competitors must provide solutions The continuous increase of competitors and the noticeable decrease in error rates across competitions demonstrate a growing interest in the topic. This paper reviews the LivDet editions from 2009 to 2021 and points out their evolution over the years.

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Section: Livdet Systems Resultsmentioning

confidence: 99%

Section: Livdet Systemsmentioning

confidence: 99%

Review of the Fingerprint Liveness Detection (LivDet) competition series: from 2009 to 2021

Micheletto¹,

Orrù²,

Casula³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…From 2009, the Fingerprint Liveness Detection Competition (LivDet) aims at assessing the performance of the state-of-the-art algorithms according to a rigorous experimental protocol. The 2017 results show a steady increase in spoof detection performance (up to 95% accuracy) [ 126 , 127 ]. The accuracy measured during the LivDet test of 2021 reached 99%.…”

Section: Friction Ridge Skin and Its Individualization Processmentioning

confidence: 99%

Interpol review of fingermarks and other body impressions (2019 – 2022)

Bécue

Champod

2023

Forensic Science International: Synergy

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“…3 To this end, we considered different acquisition sensors and matchers, and several presentation attacks fabricated with different techniques. We used five state-of-theart fake fabrication techniques for fingerprints, as listed in Table 2, taken from the first two editions of the Fingerprint Liveness Detection Competition (LivDet) [24], [25]. They include fake traits fabricated with five different materials, in a worst-case setting commonly accepted for security evaluation of fingerprint recognition systems, i.e., with the cooperation of the targeted client (consensual method).…”

Section: Where We Stand Todaymentioning

confidence: 99%

Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems

Biggio

Fumera

Marcialis

et al. 2017

IEEE Trans. Pattern Anal. Mach. Intell.

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Abstract-Prior work has shown that multibiometric systems are vulnerable to presentation attacks, assuming that their matching score distribution is identical to that of genuine users, without fabricating any fake trait. We have recently shown that this assumption is not representative of current fingerprint and face presentation attacks, leading one to overestimate the vulnerability of multibiometric systems, and to design less effective fusion rules. In this paper, we overcome these limitations by proposing a statistical meta-model of face and fingerprint presentation attacks that characterizes a wider family of fake score distributions, including distributions of known and, potentially, unknown attacks. This allows us to perform a thorough security evaluation of multibiometric systems against presentation attacks, quantifying how their vulnerability may vary also under attacks that are different from those considered during design, through an uncertainty analysis. We empirically show that our approach can reliably predict the performance of multibiometric systems even under never-before-seen face and fingerprint presentation attacks, and that the secure fusion rules designed using our approach can exhibit an improved trade-off between the performance in the absence and in the presence of attack. We finally argue that our method can be extended to other biometrics besides faces and fingerprints.

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LivDet 2017 - Fingerprint Systems Liveness Detection Competition

Cited by 11 publications

References 5 publications

Review of the Fingerprint Liveness Detection (LivDet) competition series: from 2009 to 2021

Review of the Fingerprint Liveness Detection (LivDet) competition series: from 2009 to 2021

Interpol review of fingermarks and other body impressions (2019 – 2022)

Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems

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