Paper Title

User Authentication for Online Voting System by using Machine Learning Techniques

Article Identifiers

Registration ID: IJNRD_181443

Published ID: IJNRD2205091

DOI: Click Here to Get

Authors

Sakshi Ahlawat , Pulkit Aggarwal , Saurabh Rai , Rajveer Singh , Ashwini Kumar Verma

Keywords

Keywords— Online voting system, Firebase, ML, Face detection, Biometrics.

Abstract

User Authentication for Online voting system is an Android application used to securely conducting votes and elections. As a digital platform, they eliminate the need to cast your votes using paper or having to gather in person. It also helps to protect the integrity of vote by preventing voters from being able to vote many times. This application make the use of Firebase as backend, for login, registration and for storage purpose which make our system highly secured and reliable. It also uses Firebase, ML for face detection which allows us to vote, one person at a time. This application helps in the verification of biometrics through finger print sensor. Keywords— Online voting system, Firebase, ML, Face detection, Biometrics.

How To Cite (APA)

Sakshi Ahlawat, Pulkit Aggarwal, Saurabh Rai, Rajveer Singh, & Ashwini Kumar Verma (May-2022). User Authentication for Online Voting System by using Machine Learning Techniques. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(5), 812-815. https://ijnrd.org/papers/IJNRD2205091.pdf

Issue

Volume 7 Issue 5, May-2022

Pages : 812-815

Other Publication Details

Paper Reg. ID: IJNRD_181443

Published Paper Id: IJNRD2205091

Downloads: 000121993

Research Area: Computer Engineering 

Country: Gautam Buddha Nagar, Uttar Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2205091.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2205091

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

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