Learning mappings onto regularized latent spaces for biometric authentication

11/20/2019
by   Matteo Testa, et al.
0

We propose a novel architecture for generic biometric authentication based on deep neural networks: RegNet. Differently from other methods, RegNet learns a mapping of the input biometric traits onto a target distribution in a well-behaved space in which users can be separated by means of simple and tunable boundaries. More specifically, authorized and unauthorized users are mapped onto two different and well behaved Gaussian distributions. The novel approach of learning the mapping instead of the boundaries further avoids the problem encountered in typical classifiers for which the learnt boundaries may be complex and difficult to analyze. RegNet achieves high performance in terms of security metrics such as Equal Error Rate (EER), False Acceptance Rate (FAR) and Genuine Acceptance Rate (GAR). The experiments we conducted on publicly available datasets of face and fingerprint confirm the effectiveness of the proposed system.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/18/2022

Accuracy Enhancement for Ear Acoustic Authentication Using Between-class Features

In existing biometric authentication methods, the user must perform an a...
research
11/11/2016

HoneyFaces: Increasing the Security and Privacy of Authentication Using Synthetic Facial Images

One of the main challenges faced by Biometric-based authentication syste...
research
05/15/2018

Runtime Optimization of Identification Event in ECG Based Biometric Authentication

Biometric Authentication has become a very popular method for different ...
research
09/26/2017

UBSegNet: Unified Biometric Region of Interest Segmentation Network

Digital human identity management, can now be seen as a social necessity...
research
03/18/2020

Neural Fuzzy Extractors: A Secure Way to Use Artificial Neural Networks for Biometric User Authentication

Powered by new advances in sensor development and artificial intelligenc...
research
08/13/2020

BioMetricNet: deep unconstrained face verification through learning of metrics regularized onto Gaussian distributions

We present BioMetricNet: a novel framework for deep unconstrained face v...
research
01/12/2010

A New Method to Extract Dorsal Hand Vein Pattern using Quadratic Inference Function

Among all biometric, dorsal hand vein pattern is attracting the attentio...

Please sign up or login with your details

Forgot password? Click here to reset