Securing Biometric Systems Against Fingerprint Spoofing with Imaging Solutions

EasyChair Preprint 13625

Abstract

The widespread adoption of biometric systems for authentication has revolutionized security protocols across various domains, offering a seamless and reliable means of identity verification. However, the increasing prevalence of fingerprint spoofing attacks has exposed significant vulnerabilities in these systems, necessitating the development of robust countermeasures. This paper presents an in-depth investigation into the utilization of advanced imaging solutions to enhance the security of biometric systems against fingerprint spoofing. We propose a novel framework that integrates high-resolution photographic techniques with sophisticated machine learning algorithms to effectively differentiate between authentic and spoofed fingerprints.
Our research methodology encompasses the development of a multi-layered imaging system capable of capturing minute details of fingerprint ridges and textures, which are then analyzed using deep learning models trained on extensive datasets of both genuine and counterfeit fingerprints. The experimental evaluation of our system demonstrates a substantial improvement in detection accuracy, with a notable reduction in the false acceptance rate (FAR) and false rejection rate (FRR). The proposed imaging solution not only enhances the precision of fingerprint authentication but also offers real-time processing capabilities, making it suitable for deployment in various high-security environments.

Keyphrases: Fingerprint, Securing Biometric, fingerprint spoofing

@booklet{EasyChair:13625,
  author    = {Thomas Micheal and Godwin Michael},
  title     = {Securing Biometric Systems Against Fingerprint Spoofing with Imaging Solutions},
  howpublished = {EasyChair Preprint 13625},
  year      = {EasyChair, 2024}}