SeDe: Balancing Blockchain Privacy and Regulatory Compliance by Selective De-Anonymization

Privacy is one of the essential pillars for the widespread adoption of blockchains, but public blockchains are transparent by nature. Modern analytics techniques can easily subdue the pseudonymity feature of a blockchain user. Some applications have been able to provide practical privacy protections using privacy-preserving cryptography techniques. However, malicious actors have abused them illicitly, discouraging honest actors from using privacy-preserving applications as "mixing" user interactions and funds with anonymous bad actors, causing compliance and regulatory concerns. In this paper, we propose a framework that balances privacy-preserving features by establishing a regulatory and compliant framework called Selective De-Anonymization (SeDe). The adoption of this framework allows privacy-preserving applications on blockchains to de-anonymize illicit transactions by recursive traversal of subgraphs of linked transactions. Our technique achieves this without leaving de-anonymization decisions or control in the hands of a single entity but distributing it among multiple entities while holding them accountable for their respective actions. To instantiate, our framework uses threshold encryption schemes and Zero-Knowledge Proofs (ZKPs).