Blockchain Electoral Vote Counting Solutions: A Comparative Analysis of Methods, Constraints, and Approaches

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Big Data Pub Date : 2023-08-03 DOI:10.1109/icABCD59051.2023.10220467

Patrick Mwansa, Boniface Kabaso

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Abstract

Blockchain technology in electronic voting has emerged as an alternative to other electronic and paper-based voting systems to minimize inconsistencies and redundancies. However, past experiences indicate limited success due to scalability, speed, and privacy issues. This systematic literature review examines the methods, constraints, and approaches in the existing literature on blockchain-based electoral vote-counting solutions. A thorough search of pertinent databases was performed, and selected studies were assessed based on predefined inclusion and exclusion criteria. The review's findings reveal that most existing solutions employ smart contracts and various cryptographic algorithms to create secure and transparent voting systems. However, the study also pinpoints areas that require improvement, such as scalability, privacy, and accessibility. The review recommends exploring different combinations of blockchain platforms, cryptographic algorithms, and programming languages to develop secure and transparent voting systems. Additionally, future research could investigate the potential benefits and challenges of incorporating Internet of Things (IoT) devices, consensus mechanisms, and other technologies into the voting process. The review concludes that more research is needed to enhance the security and transparency of blockchain-based voting systems.

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区块链选举计票解决方案:方法、约束和途径的比较分析

电子投票中的区块链技术已经成为其他电子和纸质投票系统的替代品，以最大限度地减少不一致和冗余。然而，过去的经验表明，由于可伸缩性、速度和隐私问题，成功有限。这篇系统的文献综述研究了基于区块链的选举计票解决方案的现有文献中的方法、约束和方法。对相关数据库进行了彻底的搜索，并根据预定义的纳入和排除标准对选定的研究进行了评估。审查的结果显示，大多数现有的解决方案都采用智能合约和各种加密算法来创建安全透明的投票系统。然而，该研究也指出了需要改进的领域，如可扩展性、隐私性和可访问性。该审查建议探索区块链平台、加密算法和编程语言的不同组合，以开发安全透明的投票系统。此外，未来的研究可以调查将物联网(IoT)设备、共识机制和其他技术纳入投票过程的潜在好处和挑战。该审查的结论是，需要更多的研究来提高基于区块链的投票系统的安全性和透明度。

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.