In order to address the issues of sensitive data exposure due to shared ledgers among nodes in a blockchain network, alongside the inability to audit and trace encrypted privacy data, a blockchain privacy protection model based on directed graphs and zeroknowledge proofs has been proposed. This model extends the open-source Hyperledger Fabric framework and effectively inherits the features of Fabric. By encrypting on-chain transaction information and utilizing Pedersen commitments and Schnorr-type zero-knowledge proofs, it generates proofs of balance, traceability, asset ownership, and consistency to provide fast and verifiable privacy data audits. The model utilizes a directed graph structure to construct a transaction graph, thus achieving traceability of transaction information on the blockchain. Moreover, it generates proofs to validate the correctness of forward tracing transactions. Experimental results demonstrate that the proposed model achieves complete audit and traceability on Fabric at a cost of less than 10% throughput, outperforming existing related models.
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