Building Blockchain-Driven Dynamic Tax Base Dark Matter Monitoring and Governance Model: Cryptocurrency, International Tax System Reconstruction, and Global Governance

Abstract

Cryptocurrency taxation poses a fundamental dilemma: how to ensure compliance while protecting privacy and enabling real-time cross-border coordination. This paper introduces a blockchain-driven framework to address these challenges. First, a permissioned consortium chain with a multi-channel architecture links OECD tax authorities, compliant exchanges and international organizations, safeguarding data sovereignty. Second, a dynamic account-transaction graph with rule-guided subgraph templates detects hidden ‘tax-base dark matter’ behaviours, including mixing services, cross-chain transfers and NFT profit masking. Third, a zero-knowledge proof protocol (zero-knowledge-TaxProof) encodes tax rules into verifiable arithmetic circuits, allowing taxpayers to prove taxable conditions without exposing details. Fourth, a dynamic-weight PBFT mechanism ties node voting power to data integrity, accuracy and responsiveness, enabling multinational collaboration. Fifth, off-chain identity anchoring with on-chain KYC decoupling preserves privacy while permitting traceability strictly under judicial authorization. Finally, a real-time dashboard and adaptive early-warning system monitors global tax-base changes with sub-minute responsiveness. Experiments on a Hyperledger Fabric testbed show the model achieves 87.8% identification accuracy, an average dark-matter capture rate of 88.9%, leakage entropy of 2.3 bits and event confirmation within 53 s. These results demonstrate a feasible, sustainable paradigm for reconstructing global digital tax governance that balances privacy, compliance and efficiency.