A Digital Currency System with Transaction Amount Privacy Protection

Abstract

Blockchain has the characteristics of decentralization, tamper proof, and untraceability and has been used in various areas. Nowadays, users are increasingly concerned about their privacy. However, anonymity poses a huge challenge on anti-crime, such as anti-money laundering, counter-terrorism financing and tax evasion. In order to achieve a broader use of blockchain, a trade-off between privacy and regulation must be achieved. We study the contradiction between privacy-preserving payment mechanisms including controllable anonymity, and penetrating regulation on digital currency. We then propose a solution based on homomorphic encryption and federated learning. Finally, a digital currency prototype is implemented with corda framework to verify our strategies.