Securing E-Voting Authentication: A Framework Integrating AI-Based Facial Recognition

Xhesika Pasha, Hamid Jahankhani*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Electoral elections are the basis of democratic governance, with an unparalleled importance that shapes the trajectory of a nation. Current paper-based systems continue to be a significant challenge in many countries, bringing problems related to trust, transparency and security. To avoid this many countries have seen electronic voting as a more attractive and efficient alternative. These electronic systems implemented in some countries, where the advantages of their use have been obvious, have also encountered their own set of challenges. Massive manipulations in voting results can happen even from a very small vulnerability. New technologies that are under development such as biometrics, blockchain and machine learning have been implemented to revolutionize the paradigm of electronic voting. Facial recognition is a modality used by us to authenticate voters, while we use algorithms such as Haar Classifier algorithm for the most accurate recognition of identity to guarantee transparent, safe and avoidable voting. We propose an architecture of the face recognition system, database management and machine learning process. A simulated case study is developed to illustrate the functionality and effectiveness of the system based on the 2020 elections in the United States. The system proposed allows users to automate the identity verification process by ensuring a good database management and a secure network that increases efficiency and transparency. Future research is envisioned to drive improvement of this system by implementing real-world scenarios.

Original languageEnglish
Title of host publicationNavigating the Intersection of Artificial Intelligence, Security, and Ethical Governance
Subtitle of host publicationSentinels of Cyberspace
EditorsReza Montasari, Hamid Jahankhani, Anthony J. Masys
Place of PublicationCham, Switzerland
PublisherSpringer
Pages19-46
Number of pages28
Edition1st
ISBN (Electronic)9783031728211
ISBN (Print)9783031728204, 9783031728235
DOIs
Publication statusPublished - 27 Nov 2024
Externally publishedYes

Publication series

NameAdvanced Sciences and Technologies for Security Applications
VolumePart F3735
ISSN (Print)1613-5113
ISSN (Electronic)2363-9466

Keywords

  • AI
  • Blockchain
  • E-voting
  • Facial recognition
  • Haar classifier algorithm
  • Quantum computing
  • SSI

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