Machine Learning with Blockchain for Secure E-voting System

Cheema, Muhammad Asaad and Ashraf, Nouman and Aftab, Asad and Qureshi, Hassaan Khaliq and Kazim, Muhammad and Azar, Ahmad Taher (2020) Machine Learning with Blockchain for Secure E-voting System. In: Proceedings - 2020 1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020 :. Proceedings - 2020 1st International Conference of Smart Systems and Emerging Technologies, SMART-TECH 2020 . Institute of Electrical and Electronics Engineers Inc., SAU, pp. 177-182. ISBN 9781728174075

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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.

Item Type:	Book Section
Additional Information:	Publisher Copyright: © 2020 IEEE.
Uncontrolled Keywords:	/dk/atira/pure/subjectarea/asjc/2200/2208
Departments or Groups:
Depositing User:	Admin SSL
Date Deposited:	19 Oct 2022 23:17
Last Modified:	11 Aug 2023 01:35
URI:	http://repository-testing.wit.ie/id/eprint/5109

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