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  Published Paper Details:

  Paper Title

Electronic -Voting System Using Machine Learning and Cryptography

  Authors

  Vidyavathi D P,  Pushpa G,  Anusuya D

  Keywords

Electronic -Voting System Using Machine Learning and Cryptography

  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, machine learning and cryptography. We use block chain for immutable vote recording, machine learning model to detect intrusion in voting data centers and e-voting stations, and cryptography for secure voter authentication and data protection. The proposed a blockchain-based e-voting system designed exclusively for physically disabled citizens who are unable to visit polling stations. The system facilitates secure, transparent, and tamper-proof voting by allowing Election Commission (EC) officials to conduct supervised voting at the voter's home using a blockchain-integrated mobile voting device.The system ensures vote integrity, voter privacy, and auditability while addressing accessibility concerns for this marginalized demographic.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2207730

  Paper ID - 290226

  Page Number(s) - f481-f491

  Pubished in - Volume 10 | Issue 7 | July 2022

  DOI (Digital Object Identifier) -    https://doi.org/10.56975/ijcrt.v10i7.290226

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Vidyavathi D P,  Pushpa G,  Anusuya D,   "Electronic -Voting System Using Machine Learning and Cryptography", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 7, pp.f481-f491, July 2022, Available at :http://www.ijcrt.org/papers/IJCRT2207730.pdf

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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
ISSN
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