Work

Detection of Printed False Attacks Using Neural Networks

Year: 2025

Type: article

Abstract: This article discusses a method for detecting false positives against a biometric facial recognition system based on deep convolutional neural networks. The proposed method is designed to detect printed false positives and is tested on open databases of real and fake faces, and the results are analyzed. The types of false positive attacks launched against a biometric system based on existing faces are analyzed.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17258687

Author: Bakhtiyor Abdukadirov

Institution: Ferghana State University

Language: English

Topic: Biometric Identification and Security

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7084604510

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