Attacking Iris Recognition: An Efficient Hill-Climbing Technique

Rathgeb, Christian; Uhl, Andreas

doi:10.1109/icpr.2010.303

Cited by 27 publications

(12 citation statements)

References 5 publications

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“…Consequently, the efficiency of classical stochastic gradient descent methods would be at least unclear. Although previous work in [45] partially supports the assumption of smoothness/continuity, this could not be easily substantiated in our case. Therefore, by simultaneously searching for multiple solutions in the solution space, genetic algorithms are more likely to avoid potential minima or even plateaus in the search space (much like simulated annealing schemes).…”

Section: Is a Multiple Of R And W Is A Multiple Of C)contrasting

confidence: 92%

Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms

Galbally

Ross

Gomez‐Barrero

et al. 2013

Computer Vision and Image Understanding

124

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El acceso a la versión del editor puede requerir la suscripción del recurso Access to the published version may require subscription AbstractA binary iriscode is a very compact representation of an iris image. For a long time it was assumed that the iriscode did not contain enough information to allow for the reconstruction of the original iris. The present work proposes a novel probabilistic approach based on genetic algorithms to reconstruct iris images from binary templates and analyzes the similarity between the reconstructed synthetic iris image and the original one. The performance of the reconstruction technique is assessed by empirically estimating the probability of successfully matching the synthesized iris image against its true counterpart using a commercial matcher. The experimental results indicate that the reconstructed images look reasonably realistic. While a human expert may not be easily deceived by them, they can successfully deceive a commercial matcher. Furthermore, since the proposed methodology is able to synthesize multiple iris images from a single iriscode, it has other potential applications including privacy enhancement of iris-based systems.

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Section: Is a Multiple Of R And W Is A Multiple Of C)contrasting

confidence: 92%

Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms

Galbally

Ross

Gomez‐Barrero

et al. 2013

Computer Vision and Image Understanding

124

View full text Add to dashboard Cite

show abstract

“…There are several ways to spoof a biometric system [2], [3]. Indeed, previous studies show at least eight different points of attack [4], [5] that can be divided into two main groups: direct and indirect attacks.…”

Section: Introductionmentioning

confidence: 99%

Deep Representations for Iris, Face, and Fingerprint Spoofing Detection

Menotti

Chiachia

Pinto

et al. 2015

IEEE Trans.Inform.Forensic Secur.

489

248

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Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or "spoofed") and, despite the recent advances in spoofing detection, current solutions often rely on domain knowledge, specific biometric reading systems, and attack types. We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face, and fingerprint modalities based on two deep learning approaches. The first approach consists of learning suitable convolutional network architectures for each domain, while the second approach focuses on learning the weights of the network via back-propagation. We consider nine biometric spoofing benchmarks --- each one containing real and fake samples of a given biometric modality and attack type --- and learn deep representations for each benchmark by combining and contrasting the two learning approaches. This strategy not only provides better comprehension of how these approaches interplay, but also creates systems that exceed the best known results in eight out of the nine benchmarks. The results strongly indicate that spoofing detection systems based on convolutional networks can be robust to attacks already known and possibly adapted, with little effort, to image-based attacks that are yet to come.Comment: Pre-print of article that will appear in the IEEE Transactions on Information Forenseics and Security (T.IFS), Special Issue on Biometric Spoofing and Countermeasures, vol 10, n. 4, April 201

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“…Anti-spoofing systems thus are required in order to reject the spoofing attacks [2]. Biometric systems without an anti-spoofing system pose a greater threat to the security of users' data [3,4]. In previous studies, eight different points have been highlighted regarding spoofing attacks [5,6], and they are categorized into two major groups such as direct attacks and indirect attacks.…”

Section: Introductionmentioning

confidence: 99%

Auditory Perception Based Anti-Spoofing System for Human Age Verification

et al. 2019

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Biometric systems are considered an efficient component for identification in the developing modern technologies. The aim of biometric systems is to verify or determine the identity of a user through his/her biological and behavioral characteristics. The threat of spoof attacks is always an important issue in biometric verification and authentication, which requires an updated and stronger protection system. In this article, we propose an anti-spoofing system based on auditory perception responses. To the best of our knowledge, this is the first time that an auditory perception based anti-spoofing system has been presented for age verification. The proposed auditory perception based anti-spoofing system was evaluated with 770 trials conducted by many subjects of each gender and age range (12–65 years of age). The results achieved are encouraging, as the auditory perception based system showed the lowest Equal Error Rate (EER) value of 5.5%.

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Attacking Iris Recognition: An Efficient Hill-Climbing Technique

Cited by 27 publications

References 5 publications

Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms

Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms

Deep Representations for Iris, Face, and Fingerprint Spoofing Detection

Auditory Perception Based Anti-Spoofing System for Human Age Verification

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