ACB-Vote: Efficient, flexible and privacy-preserving blockchain-based score voting with anonymously convertible ballots
Publication Type
Journal Article
Publication Date
6-2023
Abstract
Blockchain has emerged as a decentralized platform for e-voting. Among various blockchain-based voting systems, score voting provides flexible choices and better reflects public opinions. However, existing blockchain-based score voting systems suffer from heavy range proof overheads, and are much inefficient compared with other blockchain-based voting systems. Besides, voter anonymity in these systems is not rigorously addressed. In this paper, we propose an efficient, flexible and privacy-preserving score voting system, named ACB-Vote, from anonymously convertible ballots. ACB-Vote achieves voting anonymity with BBS+ signature and signature of knowledge. Driven by convertibly linkable signatures (CLS), ACB-Vote allows cast ballots to be converted, where the conversion mechanism prevents anonymous voters from multiple voting. Besides, the proposed system avoids heavy range proofs, enables batch ballot verification and facilitates flexible tallying methods. We formally define a security model for ACB-Vote and provide rigorous security proofs. Experiments show that the efficiency of ACB-Vote is competitive compared with the previous score voting systems and is affordable in blockchain environments.
Keywords
Score voting, blockchain, anonymous authentication, convertible linkable signatures, signature of knowledge
Discipline
Databases and Information Systems | Information Security
Research Areas
Data Science and Engineering
Publication
IEEE Transactions on Information Forensics and Security
Volume
18
First Page
3720
Last Page
3734
ISSN
1556-6013
Identifier
10.1109/TIFS.2023.3287394
Publisher
Institute of Electrical and Electronics Engineers
Citation
XUE, Wenyi; LI, Yingjiu; PANG, Hwee Hwa; PANG, Hwee Hwa; and DENG, Robert H..
ACB-Vote: Efficient, flexible and privacy-preserving blockchain-based score voting with anonymously convertible ballots. (2023). IEEE Transactions on Information Forensics and Security. 18, 3720-3734.
Available at: https://ink.library.smu.edu.sg/sis_research/8110
Additional URL
https://doi.org/10.1109/TIFS.2023.3287394