A Blockchain-Based Traceable Self-Tallying E-Voting Protocol in AI Era
Huilin Li, Yannan Li, Yong Yu, Baocang Wang, Kefei Chen
Abstract
Artificial intelligence (AI) has demonstrated huge potential in a variety of real-world applications. However, some significant considerations like fairness, transparency and trustworthiness are still challenging when applying AI to trust-oriented applications such as E-voting. E-voting plays a significant role in democratic societies, which requires voters and initiators have strong mutual trust. In this paper, we aim to facilitate the consolidation of AI ecosystems by developing a blockchain-based traceable self-tallying e-voting system. We take advantage of an event-oriented linkable group signature and a homomorphic time-lock puzzle to balance the anonymity and accountability, and the voting scale and efficiency of an e-voting system. The proposed e-voting protocol supports additional functions like multi-choice and self-tallying. We prove that the proposed protocol satisfies anonymity, time-bounded privacy, linkability and full-traceability. We also evaluate the time cost of off-chain operations and the gas cost of on-chain operations, which show the proposed e-voting protocol is practical and can be adopted in real-world applications.