Bachelor/Master Thesis

Private Voting in DAOs

DAOs are decentralized organizations where decisions are made by token holders through on-chain voting. On most platforms, such as Snapshot or Aragon, these votes are public and permanently recorded. This transparency undermines privacy: it becomes trivial to link a vote to a voter, and participants whose opinion diverges from the majority may be publicly identified and socially ostracized.

This creates strong incentives for strategic voting, vote delegation to trusted parties, or abstention. As a result, honest and independent governance is hindered. In contrast, the literature on electronic voting has proposed several privacy-preserving voting protocols. These aim to satisfy properties such as vote-privacy, coercion-resistance, individual and universal verifiability, and statistical transparency. The techniques rely on cryptographic building blocks such as threshold encryption, homomorphic tallying, mixnets, and zero-knowledge proofs.

This thesis explores the application of these cryptographic protocols in the context of DAO governance. The student should begin by studying the relevant privacy and correctness requirements, including individual verifiability, receipt-freeness, and robustness. A protocol should then be designed that satisfies a meaningful subset of these properties, under the assumption of a smart contract acting as a transparent bulletin board. The student will implement this protocol as a proof-of-concept smart contract, and evaluate its performance in terms of scalability and gas costs.

References

[1] Vote-Independence: A Powerful Privacy Notion for Voting Protocols
Jannik Dreier, Pascal Lafourcade, and Yassine Lakhnech 2011.

[2] A Smart Contract for Boardroom Voting with Maximum Voter Privacy
Patrick McCorry, Siamak F. Shahandashti and Feng Hao 2017.

[3] Cicada: A framework for private non-interactive on-chain auctions and voting
Noemi Glaeser, Istvan Andras Seres, Michael Zhu, and Joseph Bonneau 2024.

Contact François-Xavier Wicht for more information.

Nature of the project: Theory 50%, Systems 50%.