Machine Learning with Blockchain for Secure E-voting System

Muhammad Asaad Cheema, Nouman Ashraf, Asad Aftab, Hassaan Khaliq Qureshi, Muhammad Kazim, Ahmad Taher Azar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Voting is a central component of a country's political life cycle. Privacy, authentication and integrity of citizens' votes and their data are considered to be essential to any e-voting program. In order to resolve these concerns, we propose a stable e-voting system based on the principles of blockchain and machine learning. We use blockchain to ensure the integrity and security of votes, machine learning model to detect intrusion in voting data centers and e-voting stations. In the proposed model, we use the concepts of personal and public blockchain. The personal blockchain is used for the purposes of voter registration and voting. The public blockchain is used to maintain the integrity of the personal data of the voters by storing the root hash derived from the Merkle hash tree and revealing the results of the voting stations as soon as the voting process is completed. The proposed blockchain-based e-voting system offers transparency, treasury, confidence and prevents intrusion into the information exchange network.

Original languageEnglish
Title of host publicationProceedings - 2020 1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020
EditorsAnis Koubaa, Ahmad Taher Azar, Basit Qureshi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages177-182
Number of pages6
ISBN (Electronic)9781728174075
DOIs
Publication statusPublished - Nov 2020
Event1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020 - Riyadh, Saudi Arabia
Duration: 03 Nov 202005 Nov 2020

Publication series

NameProceedings - 2020 1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020

Conference

Conference1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020
Country/TerritorySaudi Arabia
CityRiyadh
Period03/11/202005/11/2020

Keywords

  • Blockchain
  • E-Voting
  • Machine Learning
  • Merkle Tree

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