Paper 2026/511

Human-Extractable ZK Proofs of Knowledge: A Solution to Dark DAOs

Zeyuan Yin, The State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security
Leiyuan Tian, The State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security
Bingsheng Zhang, The State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security
Kui Ren, The State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security
Abstract

A Decentralized Autonomous Organization (DAO) is a pioneering evolution to realize a decentralized democratic governance over a blockchain. In a DAO, stakeholders usually make collective decisions through secure on-chain voting. Recently, Dark DAO (Austgen et al., arXiv:2311.03530) was proposed as a decentralized cartel that enables automated vote-buying. It attacks the inalienable authentication of a remote e-voting system by leveraging key encumbrance via MPC or TEEs, enabling a voter to pass the authentication without knowing the actual key. To defend against this new type of attack, the notions of individual knowledge (Dziembowski et al., CRYPTO '23) and complete knowledge (Kelkar et al., CCS '24) were proposed, ensuring that the prover has unencumbered knowledge of a secret. However, their solutions rely on TEEs or ASICs, which are difficult to deploy on blockchain. Inspired by the human-extractable CAPTCHA puzzles proposed by Kumarasubramanian et al. (PKC '13), we propose a new primitive called human-extractable zero-knowledge proofs of knowledge (HE-ZKPoK) as an alternative solution to Dark DAOs. Our HE-ZKPoK protocol forces the prover to solve human-extractable CAPTCHA puzzles along with completing a standard zero-knowledge proof of knowledge, avoiding the need for specialized hardware. As a result, any human entity can extract the witness merely by looking at the prover's CAPTCHA queries and the associated puzzles. With this property, we conclude that if a voter sells his vote, his secret key will be fully exposed, thus deterring voters from engaging in vote-buying.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Published elsewhere. 28th International Conference on Information and Communications Security (ICICS 2026)
Keywords
Human-extractable CAPTCHADark DAOsInalienable authenticationHuman-extractable ZK proofs of knowledge
Contact author(s)
zeyuanyin @ zju edu cn
lytian cs @ zju edu cn
bingsheng @ zju edu cn
kuiren @ zju edu cn
History
2026-05-08: revised
2026-03-13: received
See all versions
Short URL
https://ia.cr/2026/511
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2026/511,
      author = {Zeyuan Yin and Leiyuan Tian and Bingsheng Zhang and Kui Ren},
      title = {Human-Extractable {ZK} Proofs of Knowledge: A Solution to Dark {DAOs}},
      howpublished = {Cryptology {ePrint} Archive, Paper 2026/511},
      year = {2026},
      url = {https://eprint.iacr.org/2026/511}
}
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.