A review on presentation attack detection system for fake fingerprint

Author:

Agarwal Rohit1,Jalal A. S.1,Arya K. V.2

Affiliation:

1. Computer Engineering & Applications, GLA University, Mathura, U. P. 281406, India

2. Department of Computer Science, ABV-IIITM Gwalior, M. P. 474015, India

Abstract

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.

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

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1. Single heartbeat ECG authentication: a 1D-CNN framework for robust and efficient human identification;Frontiers in Bioengineering and Biotechnology;2024-07-04

2. Enhancing Fingerprint Authentication: A Systematic Review of Liveness Detection Methods Against Presentation Attacks;Journal of The Institution of Engineers (India): Series B;2024-05-12

3. Deep learning techniques for biometric security: A systematic review of presentation attack detection systems;Engineering Applications of Artificial Intelligence;2024-03

4. Quantized Generative Models for Solving Inverse Problems;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

5. CLNet: a contactless fingerprint spoof detection using deep neural networks with a transfer learning approach;Multimedia Tools and Applications;2023-08-24

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