Secure Online Voting with Enhanced Biometric Verification Using Cryptography Approach

Electronic voting systems, increasingly used in modern elections, offer several enhancements over traditional methods, including better accuracy, convenience, flexibility, privacy, verifiability, and mobility. However, these systems are not without their shortcomings. They can be time-consuming to manage and still require significant amounts of paperwork. High-level officials often have no direct involvement in their operation. Additionally, the machines are prone to damage if not properly maintained, and their software typically does not support the simultaneous updating and editing of multiple items, which can hinder their efficiency. Here proposes a novel approach that integrates encrypted face recognition and score voting. The system leverages Haar Cascade Classification for face detection, extracting and encrypting facial features during user registration, and subsequently comparing encrypted features during the authentication process. The encrypted feature storage ensures user privacy and protects sensitive biometric information. Due to identification and authentication users are permitted to cast votes in the system using a score voting system that introduces more flexibility to the procedure. Score voting or also called range voting is the type of voting where voters have the liberty to assign different scores to the given candidates or options. With reference to other methods of voting that enable the voters to vote for only one candidate, the score-based methods are much better at providing a gradation of the views of the voters. This feature allows for the verification of every process of the voting exercise. However, this ID is well hidden and even the system administrators cannot track this ID thus ensuring that no anyone can identify any of the voters.

Authors

Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/aece62803.2024.10911295
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Secure Online Voting with Enhanced Biometric Verification Using Cryptography Approach

S. Gunasekaran, B. Gowtham, M. Dhinesh, M Ebinesh et al.
Advanced Steganography and Watermarking Techniques
article

Secure Online Voting with Enhanced Biometric Verification Using Cryptography Approach

S. Gunasekaran, B. Gowtham, M. Dhinesh, M Ebinesh, C R Guruprasath
article en

Abstract

Electronic voting systems, increasingly used in modern elections, offer several enhancements over traditional methods, including better accuracy, convenience, flexibility, privacy, verifiability, and mobility. However, these systems are not without their shortcomings. They can be time-consuming to manage and still require significant amounts of paperwork. High-level officials often have no direct involvement in their operation. Additionally, the machines are prone to damage if not properly maintained, and their software typically does not support the simultaneous updating and editing of multiple items, which can hinder their efficiency. Here proposes a novel approach that integrates encrypted face recognition and score voting. The system leverages Haar Cascade Classification for face detection, extracting and encrypting facial features during user registration, and subsequently comparing encrypted features during the authentication process. The encrypted feature storage ensures user privacy and protects sensitive biometric information. Due to identification and authentication users are permitted to cast votes in the system using a score voting system that introduces more flexibility to the procedure. Score voting or also called range voting is the type of voting where voters have the liberty to assign different scores to the given candidates or options. With reference to other methods of voting that enable the voters to vote for only one candidate, the score-based methods are much better at providing a gradation of the views of the voters. This feature allows for the verification of every process of the voting exercise. However, this ID is well hidden and even the system administrators cannot track this ID thus ensuring that no anyone can identify any of the voters.

Openalex Percentile: Top 72%
Advanced Steganography and Watermarking Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Secure Online Voting with Enhanced Biometric Verification Using Cryptography Approach — S. Gunasekaran, B. Gowtham, et al. · (2024) | TGRS Research Map | TGRS