Projects per year
Abstract
We introduce a zero-knowledge cryptocurrency mixer framework that allows groups of users to set up a mixing pool with configurable governance conditions, configurable deposit delays, and the ability to refund or confiscate deposits if it is suspected that funds originate from crime. Using a consensus process, group participants can monitor inputs to the mixer and determine whether the inputs satisfy the mixer conditions. If a deposit is accepted by the group, it will enter the mixer and become untraceable. If it is not accepted, the verifiers can freeze the deposit and collectively vote to either refund the deposit back to the user, or confiscate the deposit and send it to a different user. This behaviour can be used to examine deposits, determine if they originate from a legitimate source, and if not, return deposits to victims of crime.
Original language | English |
---|---|
Title of host publication | 7th IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS 2025) |
Publisher | IEEE Computer Society |
Publication status | Accepted/In press - 17 May 2025 |
Event | The 7th IEEE International Conference on Decentralized Applications and Infrastructures - University of Arizona, Tuscon, United States Duration: 21 Jul 2025 → 24 Jul 2025 Conference number: 7 https://conf.researchr.org/track/cisose-2025/dapps-2025 |
Conference
Conference | The 7th IEEE International Conference on Decentralized Applications and Infrastructures |
---|---|
Abbreviated title | DAPPS 2025 |
Country/Territory | United States |
City | Tuscon |
Period | 21/07/25 → 24/07/25 |
Internet address |
Research Groups and Themes
- Intelligent Systems Laboratory (FinTech)
- Financial Engineering Lab
- FEL
- Intelligent Systems Laboratory
- ISL
Keywords
- cryptocurrency mixer
- zero-knowledge
- proof-of-innocence
- cryptocurrencies
- blockchain technology
- privacy
Fingerprint
Dive into the research topics of 'zkMixer: A Configurable Zero-Knowledge Mixer with Proof of Innocence and Anti-Money Laundering Consensus Protocols'. Together they form a unique fingerprint.Projects
- 1 Active
-
8463 EPSRC EP/Y028392/1 AI For Collective Intelligence SEMT
Cartlidge, J. (Principal Investigator)
1/02/24 → 31/01/29
Project: Research