A novel multimodal biometric authentication system using machine learning and blockchain

Richard Brown, Gueltoum Bendiab, Stavros Shiaeles*, Bogdan Ghita

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Secure user authentication has become an important issue in modern society as in many consumer applications, especially financial transactions, it is extremely important to prove the identity of the user. In this context, biometric authentication methods that rely on physical and behavioural characteristics have been proposed as an alternative for convolutional systems that rely on simple passwords, Personal Identification Number or tokens. However, in real-world applications, authentication systems that involve a single biometric faced many issues, especially lack accuracy and noisy data, which boost the research community to create multibiometric systems that involve a variety of biometrics. Those systems provide better performance and higher accuracy compared to other authentication methods. However, most of them are inconvenient and requires complex interactions from the user. Thus, in this paper, we present a multimodal authentication system that relies on machine learning and blockchain, intending to provide a more reliable, transparent, and convenient authentication mechanism. The proposed system combines tow important biometrics: fingerprint and face with age, and gender features. The supervised learning algorithm Decision Tree has been used to combine the results of the biometrics verification process and produce a confidence level related to the user. The initial experimental results show the efficiency and robustness of the proposed systems.

Original languageEnglish
Title of host publicationSelected Papers from the 12th International Networking Conference - INC 2020
EditorsBogdan Ghita, Stavros Shiaeles
PublisherSpringer
Pages31-46
Number of pages16
ISBN (Electronic)9783030647582
ISBN (Print)9783030647575
DOIs
Publication statusPublished - 5 Jan 2021
Event12th International Network Conference - Online
Duration: 21 Sep 202021 Sep 2020

Publication series

NameLecture Notes in Networks and Systems
Volume180
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference12th International Network Conference
Abbreviated titleINC 2020
Period21/09/2021/09/20

Keywords

  • Authentication
  • Blockchain
  • Machine learning
  • Multimodal
  • Security

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