A Secure Data Regulation Framework for Blockchain Ecosystem
Jing Lei, Qingqi Pei, Xuefeng Liu · 2025
The global blockchain ecosystem is expanding, but with it come increasing security risks and regulatory challenges. Current blockchain systems enable entity anonymity by keeping a user’s digital identity separate from their physical identity. A malicious user may avoid regulations by independently utilizing numerous accounts (or addresses), multiple batches of transactions, or even different chains to conduct illicit transactions. Therefore, based on the existing blockchain architecture, we propose ATC, a framework for regulation dealing with multiple Accounts (or addresses), Transactions, and Cross-chain activities. By building a digital identity-associative relationship database (or an entity-associative relationship database), ATC is dedicated to providing fine-grained transaction risk detection and identification. As a special case, for the permissioned blockchain, an endogenous secure regulation system can be integrated into its architecture design because its participants need to be authorized to join the network and its data is more privacy-sensitive. In this paper, we combine cryptography to design IDC, a permissioned blockchain’s regulation system associated with Identity, Data, and Cross-chain transaction graphs in a private setting, while making the associative relationship visible only to the regulator. Moreover, it also provides data governance after the identity and data are revealed. In short, we provide a high-level draft for blockchain ecosystem regulation for community discussion.