End-to-End Verifiability Degree Metric in e-Voting System

Suharsono, Teguh Nurhadi; Sukmana, Rini Nuraini; Gunawan, .

doi:10.1109/tssa52866.2021.9768251

Cited by 1 publication

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Suharsono et al [6] proposed an indicator for improving the verifiability of E-voting systems, knowing that verifiability is one of the most important features in E-voting systems and is the most important factor in improving public acceptance of the results of E-voting. Suharsono et al [7] proposed an end-to-end verifiability metric to measure the degree of end-to-end verifiability (including end-to-end verifiability metrics) before an election, end-to-end verifiability at the time of an election, end-to-end verifiability after an election, and end-to-end verifiability after the counting of votes. They also determined the location of the degree of verifiability, and determined the range of the degree of verifiability.…”

Section: Related Workmentioning

confidence: 99%

A Publicly Verifiable E-Voting System Based on Biometrics

Liu,

Han,

Tan

et al. 2023

Cryptography

View full text Add to dashboard Cite

Voters use traditional paper ballots, a method limited by the factors of time and space, to ensure their voting rights are exercised; this method requires a lot of manpower and resources. Duplicate voting problems may also occur, meaning the transparency and reliability of the voting results cannot be guaranteed. With the rapid developments in science and technology, E-voting system technology is being adopted more frequently in election activities. However, E-voting systems still cannot address the verifiability of the election process; the results of a given election and the credibility of the host organization will be questioned if the election’s verifiability cannot be ensured. Elections may also pose a series of problems related to privacy, security, and so on. To address these issues, this paper presents a public, and verifiable E-voting system with hidden statistics; this system is based on commitment, zk-SNARKs, and machine learning. The system can deal with a large number of candidates, complex voting methods, and result functions in counting both hidden and public votes and can satisfy the requirements of verifiability, privacy, security, and intelligence. Our security analysis shows that our scheme achieves privacy, hidden vote counting and verifiability. Our performance evaluation demonstrates that our system has reasonable applications in real scenarios.

show abstract

Section: Related Workmentioning

confidence: 99%