DemocracyGuard: Blockchain‐based secure voting framework for digital democracy

IF 3 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Expert Systems Pub Date : 2024-08-14 DOI:10.1111/exsy.13694

Mritunjay Shall Peelam, Gaurav Kumar, Kunjan Shah, Vinay Chamola

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引用次数: 0

Abstract

Online voting is gaining traction in contemporary society to reduce costs and boost voter turnout, allowing individuals to cast their ballots from anywhere with an internet connection. This innovation is cautiously met due to the inherent security risks, where a single vulnerability can lead to widespread vote manipulation. Blockchain technology has emerged as a promising solution to address these concerns and create a trustworthy electoral process. Blockchain offers a decentralized network of nodes that enhances transparency, security, and verifiability. Its distributed ledger and non‐repudiation features make it a compelling alternative to traditional electronic voting systems, ensuring the integrity of elections. To further bolster the security of online voting, we propose DemocracyGuard platform on the Ethereum blockchain, which incorporates facial recognition technology to authenticate voters. By leveraging these advancements, DemocracyGuard aims to provide a secure and resilient platform for online voting, paving the way for its broader adoption and revolutionizing the electoral landscape.

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民主卫士基于区块链的数字民主安全投票框架

为了降低成本和提高投票率，网络投票在当代社会越来越受到重视，它允许个人在任何有互联网连接的地方进行投票。由于存在固有的安全风险，一个漏洞就可能导致大范围的投票操纵，人们对这一创新持谨慎态度。区块链技术已成为解决这些问题和创建可信选举程序的一种有前途的解决方案。区块链提供了一个去中心化的节点网络，提高了透明度、安全性和可验证性。区块链的分布式账本和不可抵赖性使其成为传统电子投票系统的有力替代品，确保了选举的公正性。为了进一步加强在线投票的安全性，我们在以太坊区块链上提出了 DemocracyGuard 平台，该平台结合了面部识别技术来验证选民身份。通过利用这些先进技术，DemocracyGuard 旨在为在线投票提供一个安全、灵活的平台，为其更广泛的应用铺平道路，并彻底改变选举格局。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Expert Systems 工程技术-计算机：理论方法

CiteScore

7.40

自引率

6.10%

发文量

266

审稿时长

24 months

期刊介绍： Expert Systems: The Journal of Knowledge Engineering publishes papers dealing with all aspects of knowledge engineering, including individual methods and techniques in knowledge acquisition and representation, and their application in the construction of systems – including expert systems – based thereon. Detailed scientific evaluation is an essential part of any paper. As well as traditional application areas, such as Software and Requirements Engineering, Human-Computer Interaction, and Artificial Intelligence, we are aiming at the new and growing markets for these technologies, such as Business, Economy, Market Research, and Medical and Health Care. The shift towards this new focus will be marked by a series of special issues covering hot and emergent topics.