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Detail publikace
STANČÍKOVÁ, I. HOMOLIAK, I.
Originální název
SBvote: Scalable Self-Tallying Blockchain-Based Voting
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Decentralized electronic voting solutions represent a promising advancement in electronic voting. One of the e-voting paradigms, the self-tallying scheme, offers strong protection of the voters' privacy while making the whole voting process verifable. Decentralized smart contract platforms became interesting practical instantiation of the immutable bulletin board that this scheme requires to preserve its properties. Existing smart contract-based approaches employing the self-tallying scheme (such as OVN or BBB-Voting) are only suitable for a boardroom voting scenario due to their scalability limitation. The goal of our work is to build on existing solutions to achieve scalability without losing privacy guarantees and veriability. We present SBvote, a blockchain-based self-tallying voting protocol that is scalable in the number of voters, and therefore suitable for large-scale elections. The evaluation of our proof-of-concept implementation shows that the protocol's scalability is limited only by the underlying blockchain platform. We evaluated the scalability of SBvote on two public smart contract platforms -- Gnosis and Harmony. Despite the limitations imposed by the throughput of blockchain platform, SBvote can accommodate elections with millions of voters.
Klíčová slova
e-voting, scalability, privacy, blockchain, smart contracts
Autoři
STANČÍKOVÁ, I.; HOMOLIAK, I.
Vydáno
7. 6. 2023
Nakladatel
Association for Computing Machinery
Místo
Tallin
ISBN
978-1-4503-9517-5
Kniha
SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
Strany od
203
Strany do
2011
Strany počet
1809
BibTex
@inproceedings{BUT185118, author="Ivana {Stančíková} and Ivan {Homoliak}", title="SBvote: Scalable Self-Tallying Blockchain-Based Voting", booktitle="SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing", year="2023", pages="203--2011", publisher="Association for Computing Machinery", address="Tallin", isbn="978-1-4503-9517-5" }