Blockchain-Based Privacy Conservation Framework

S. P. Maniraj; P. Robert; Ravilla Pavithra; J. Omana

doi:10.2991/978-94-6463-529-4_29

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Blockchain-Based Privacy Conservation Framework

Authors

S. P. Maniraj¹^{, *}, P. Robert², Ravilla Pavithra³, J. Omana⁴

¹Department of Computer Science & Engineering, S.R.M. Institute of Science and Technology, Chennai, Tamil Nadu, India

²Department of Artificial Intelligence & Machine Learning, C.M.R. Institute of Technology, Bengaluru, Karnataka, India

³Department of Computer Science & Engineering, R.M.D. Engineering College, Chennai, Tamil Nadu, India

⁴Department of Information Technology, Prathyusha Engineering College, Chennai, Tamil Nadu, India

^*Corresponding author. Email: spmaniraj1986@gmail.com

Corresponding Author

S. P. Maniraj

Available Online 4 October 2024.

DOI: 10.2991/978-94-6463-529-4_29 How to use a DOI?
Keywords: Ethereum; E-Voting; Block Chain; Hyper Ledger; Privacy; Transaction Accuracy
Abstract: As the blockchain architectures and communities grow, blockchain networks frequently face scenarios where the user must vote to make decisions. However, a natively implemented voting system on current blockchain systems is useless. The decision-making process is then either assigned to many network members who make such decisions offline or reliant on online voting services by third parties. The peers depend on reliable parties or centralized networks directly or implicitly. This contradicts the underlying blockchain decentralization theory and opens the option to theft. The work suggests a native blockchain voting protocol for peers to vote on their existing block-chained network without requiring a responsible or third party to enable decentralized and secure decisions. The protocol protects end-to-end anonymity and has attractive properties such as cheating detectability and correctness. A protocol for the legitimacy and functional applicability of protocol on Hyperledger Fabric shall also be enforced.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Signal Processing and Computer Vision (SIPCOV-2023)
Series: Advances in Engineering Research
Publication Date: 4 October 2024
ISBN: 978-94-6463-529-4
ISSN: 2352-5401
DOI: 10.2991/978-94-6463-529-4_29 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - S. P. Maniraj
AU  - P. Robert
AU  - Ravilla Pavithra
AU  - J. Omana
PY  - 2024
DA  - 2024/10/04
TI  - Blockchain-Based Privacy Conservation Framework
BT  - Proceedings of the International Conference on Signal Processing and Computer Vision (SIPCOV-2023)
PB  - Atlantis Press
SP  - 317
EP  - 329
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-529-4_29
DO  - 10.2991/978-94-6463-529-4_29
ID  - Maniraj2024
ER  -

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