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논문 기본 정보

자료유형
학술저널
저자정보
Adyan Marendra Ramadhani (Dong-A University) Soon-Goo Hong (Dong-A University) Na-rang Kim (Dong-A University) Seung-Eui Ryu (Dong-A University)
저널정보
한국인터넷전자상거래학회 인터넷전자상거래연구 인터넷전자상거래연구 제19권 제2호
발행연도
2019.4
수록면
99 - 111 (13page)
DOI
10.37272/JIECR.2019.04.19.2.99

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초록· 키워드

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Voting is an activity that involves choosing a preferred candidate in an election. There are several potential problems in the voting process, including cheating and security failures. The development of a secure electronic voting system that offers the fairness and privacy of existing voting schemes while simultaneously providing the transparency and flexibility offered by electronic systems has been a challenge for some time. To prevent problems in the voting process, we propose a robust technique that includes blockchain and machine learning. Blockchain employs a technique and concept similar to that used by digital currencies to secure transactions. Blockchain voter data is then used to predict votes based on past votes using a machine learning method. The purpose of this research was to provide a conceptual model for an e-voting system based on blockchain technology and machine learning(support vector machines, Gaussian Naive Bayes, and decision trees) to predict votes and provide vote security. The machine learning techniques used in this study predicted votes based on previous voter data with an average of 98% accuracy, while the blockchain improved and tightened e-voting system security using private networks and structures. This study contributes to the literature on e-voting by proposing improvements to vote security and prediction by combining blockchain technology and machine learning techniques. Its primary limitation is that this method has only been replicated on small-scale networks, such as school networks.

목차

Abstract
Ⅰ. Introduction
Ⅱ. Literature Review
Ⅲ. Research Model and Methodology
Ⅳ. Result
Ⅴ. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2019-323-000681153