Presentation attack detection system for fake Iris: a review

2021 ◽  
Author(s):  
Rohit Agarwal ◽  
Anand Singh Jalal
Keyword(s):  
Detection System ◽  
Attack Detection ◽  
Presentation Attack Detection

A review on presentation attack detection system for fake fingerprint

2020 ◽  
Vol 34 (05) ◽  
pp. 2030001 ◽  
Author(s):  
Rohit Agarwal ◽  
A. S. Jalal ◽  
K. V. Arya
Keyword(s):  
Detection System ◽  
Attack Detection ◽  
Fingerprint Recognition ◽  
The Past ◽  
Liveness Detection ◽  
Comprehensive Survey ◽  
Open Issue ◽  
Recognition Systems ◽  
Effectiveness And Efficiency ◽  
Presentation Attack Detection

Fingerprint recognition systems are susceptible to artificial spoof fingerprint attacks, like molds manufactured from polymer, gelatin or Play-Doh. Presentation attack is an open issue for fingerprint recognition systems. In a presentation attack, synthetic fingerprint which is reproduced from a real user is submitted for authentication. Different sensors are used to capture the live and fake fingerprint images. A liveness detection system has been designed to defeat different classes of spoof attacks by differentiating the features of live and fake fingerprint images. In the past few years, many hardware- and software-based approaches are suggested by researchers. However, the issues still remain challenging in terms of robustness, effectiveness and efficiency. In this paper, we explore all kinds of software-based solution to differentiate between real and fake fingerprints and present a comprehensive survey of efforts in the past to address this problem.

scholarly journals Directed Gaze Trajectories for Biometric Presentation Attack Detection

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1394
Author(s):  
Asad Ali ◽  
Sanaul Hoque ◽  
Farzin Deravi
Keyword(s):  
Eye Movements ◽  
Visual Stimuli ◽  
Attack Detection ◽  
Movement Data ◽  
Biometric Systems ◽  
Planar Geometries ◽  
Presentation Attack Detection

Presentation attack artefacts can be used to subvert the operation of biometric systems by being presented to the sensors of such systems. In this work, we propose the use of visual stimuli with randomised trajectories to stimulate eye movements for the detection of such spoofing attacks. The presentation of a moving visual challenge is used to ensure that some pupillary motion is stimulated and then captured with a camera. Various types of challenge trajectories are explored on different planar geometries representing prospective devices where the challenge could be presented to users. To evaluate the system, photo, 2D mask and 3D mask attack artefacts were used and pupillary movement data were captured from 80 volunteers performing genuine and spoofing attempts. The results support the potential of the proposed features for the detection of biometric presentation attacks.

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