Introduction to Iris Presentation Attack Detection

Morales, Aythami; Fiérrez, Julián; Galbally, Javier; Gomez‐Barrero, Marta

doi:10.1007/978-3-319-92627-8_6

Cited by 15 publications

(5 citation statements)

References 41 publications

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“…Biometry can similarly be attacked by replaying recorded or artificially generated data during enrollment. For instance, wearing cosmetic contact lenses during enrollment with an iris scanner can cause the scanner to accept other individuals who wear the same contact lens as false positives [37].…”

Section: Discussionmentioning

confidence: 99%

Deep Eyedentification: Biometric Identification using Micro-Movements of the Eye

Jäger,

Makowski,

Prasse

et al. 2019

Preprint

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We study involuntary micro-movements of the eye for biometric identification. While prior studies extract lower-frequency macromovements from the output of video-based eye-tracking systems and engineer explicit features of these macro-movements, we develop a deep convolutional architecture that processes the raw eye-tracking signal. Compared to prior work, the network attains a lower error rate by one order of magnitude and is faster by two orders of magnitude: it identifies users accurately within seconds.

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Section: Discussionmentioning

confidence: 99%

Deep Eyedentification: Biometric Identification using Micro-Movements of the Eye

Jäger,

Makowski,

Prasse

et al. 2019

Preprint

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“…Subsequently, this acquired data is utilized to generate a replica image, either in two-dimensional or three-dimensional form. Such a replica can then be transformed into a mask or overlay, enabling an imposter to assume the identity of the victim [9]…”

Section: Different Types Of Attacks In Fvrsmentioning

confidence: 99%

A Review on Vascular Biometrics for Finger Vein Authentication System

Hemanth,

Thomas

2024

Frontiers in Artificial Intelligence and Applications

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In the area of biometric authentication, vascular biometrics has been highlighted off late due to its much-appreciated list of advantages which promotes more efficient person identification and authentication. Finger Vein Recognition Systems (FVRS) is an emerging biometric technology gaining much attention throughout the world especially in the banking sector, cashless/cardless money transfer, ATM systems and soon. Finger vein authentication systems have the threat of spoof attacks or presentation attacks (PA) which affects the security measures in a serious manner. Since vascular biometrics is receiving more attention in the field of financial transfer, being aware of the possible security attacks is a necessity. This paper presents a review of selected literature on presentation attacks in finger vein authentication systems. Also listing the pros and cons of the presentation attack detection methods and certain ways to prevent PA. The pros and challenges of dealing with FVRS have also been listed here.

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“…Fingerprint designs are exclusive to everyone, and the likelihood that two individuals will have identical ngerprints is an exceptional case of approximately one in sixty-four thousand million from birth to death [16]. One of the most often used biometric recognition methods in biometric technology is the iris [17]. Since the earliest Dougman publication proposed the iris as a biological feature [18].…”

Section: Biometrics Informationmentioning

confidence: 99%

A robust hybrid algorithm for medical image cryptography using patient biometrics based on DNA and RNA computing

Soltani,

Shakeri,

Houshmand

2023

Preprint

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In the new age, most medical digital imaging and media objects (DICOMs) contain images and related medical and demographic information about the patients, which must be kept secret. One of the techniques used to secure medical images is encryption. This study suggests a robust hybrid cryptography algorithm to ensure DICOM privacy. The proposed algorithm uses DNA and RNA encryption algorithms. In the suggested algorithm, in the DNA phase, the DICOM image is encrypted using DNA rules, the XOR operator, and the chaotic map function, and the first cipher image is created. The cipher image is then sent into the RNA phase, where the truth table for RNA and the secret key are used to further encrypt the image. In addition to increasing security for each of the encrypted DICOMs, all keys depend on the patient’s biometric information, such as the patient’s iris or fingerprint. Some of the encryption features such as statistical, differential, and key analysis findings show that the proposed system is resilient and resistant to a variety of attacks.

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Introduction to Iris Presentation Attack Detection

Cited by 15 publications

References 41 publications

Deep Eyedentification: Biometric Identification using Micro-Movements of the Eye

Deep Eyedentification: Biometric Identification using Micro-Movements of the Eye

A Review on Vascular Biometrics for Finger Vein Authentication System

A robust hybrid algorithm for medical image cryptography using patient biometrics based on DNA and RNA computing

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