Financial information sharing system and method based on block chain

Abstract

The invention discloses a financial information sharing system and method based on a block chain, and relates to the technical field of block chains, and the method comprises the steps: integrating block chain intercommunication financial information in an enterprise, collecting the financial data of the enterprise, carrying out the preprocessing, structuring and data encryption, obtaining the priority score YX of each business record, and obtaining the priority score YX of each business record; the method comprises the steps of obtaining first priority financial data and second priority financial data in combination with a preset priority score threshold YZ, storing the first priority financial data and the second priority financial data in a block chain and an under-chain auxiliary node respectively, constructing a hash tree model according to the financial data of the block chain, generating a multi-dimensional index for financial data query, and compiling an intelligent contract for abnormal financial transaction recognition. According to the method, data collaborative analysis is carried out on abnormal financial transactions, and abnormal data is repaired according to a data collaborative analysis result, so that the consistency and integrity of on-chain and off-chain data are realized, and the efficiency, transparency and security of financial data sharing are improved.

Description

Technical Field

[0001] The present invention relates to the field of blockchain technology, and in particular to a blockchain-based financial information sharing system and method. Background Art

[0002] In enterprise-level applications, companies need to share specific financial data such as contract information, payment status, and invoice data in scenarios such as supply chain, cross-border transactions, and settlement and payment. Financial information sharing refers to the process of transmitting and sharing financial data and information between different organizations or systems. In modern enterprises and institutions, the purpose of financial information sharing is to improve decision-making efficiency, ensure transparency, reduce risks, and improve management and compliance. Financial information sharing can be achieved through the integration of internal and external systems, shared platforms, or cloud technology. However, traditional financial information sharing models have problems such as low efficiency, insufficient privacy protection, and data inconsistency, which makes it difficult to meet the high requirements of modern enterprises for the digital and collaborative management of financial information.

[0003] A Chinese invention patent, published under application number CN113763172B, discloses a blockchain-based automated information sharing platform for financial data processes. This platform comprises an application layer, an API layer, a service layer, a logic layer, a data layer, a blockchain subsystem, and a subsystem for evidence storage and traceability. Robotic process automation (RPA) technology is used to acquire project data from multiple systems, and blockchain technology is used to enable project data sharing. This improves the security, efficiency, and usability of project transaction processes within core and industrial units. Automatically acquiring system data without human intervention significantly reduces the burden on grassroots employees. All members can access project data on the blockchain through a blockchain browser. By establishing cross-enterprise and cross-departmental information links, transaction documents from different organizations and systems are uniformly managed and shared in real time, providing decision support for core and industrial units.

[0004] The above platforms can share financial data, but in addition to this, in the existing financial information sharing process, financial data is usually directly optimized and shared among multiple departments.

[0005] However, this data sharing method has shortcomings in terms of privacy and data protection. The transparency of the blockchain means that all on-chain data can be browsed. Although the evidence traceability subsystem supports hiding and recycling functions, the hidden evidence still remains on the chain, but it is difficult to display on the browser interface. This cannot fully meet the privacy protection needs of sensitive financial data, and there is no clear mention of optimization solutions for large-scale financial data storage and query, which may cause bottlenecks when facing high-concurrency requests.

[0006] To this end, the present invention provides a financial information sharing system and method based on blockchain. Summary of the Invention

[0007] (1) Technical problems solved

[0008] In response to the shortcomings of the existing technology, the present invention provides a financial information sharing system and method based on blockchain. By integrating blockchain to communicate financial information within the enterprise, collecting the enterprise's financial data, preprocessing, structuring and data encryption, the priority score YX of each business record is obtained, and combined with the preset priority score threshold YZ, the first priority financial data and the second priority financial data are obtained, and stored in the blockchain and the off-chain auxiliary node respectively. Based on the financial data of the blockchain, a hash tree model is constructed, a multidimensional index is generated for financial data query, and a smart contract is written to identify abnormal financial transactions. For abnormal financial transactions, data collaborative analysis is performed, and the abnormal data is repaired according to the results of the data collaborative analysis, thereby achieving consistency and integrity of on-chain and off-chain data, improving the efficiency, transparency and security of financial data sharing, and solving the problems in the above-mentioned background technology.

[0009] (2) Technical solution

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions: a financial information sharing system based on blockchain, including a blockchain integration module, a data acquisition and encryption module, a data storage module, a smart contract execution module, a data collaborative analysis module, and a data repair module;

[0011] The blockchain integration module is used to integrate the blockchain into the financial information system within the enterprise and to transfer information between the blockchain and the financial information system;

[0012] The data collection and encryption module is used to collect financial data based on the financial information system within the enterprise, pre-process the financial data, construct a financial data set D, and perform structured processing on the financial data set D to obtain a structured table of financial data, and encrypt each business record in the structured table to generate a unique identifier;

[0013] The data storage module is used to obtain a priority score YX for each business record based on the financial data set D, preset a priority score threshold YZ, and compare and analyze the priority score YX with the priority score threshold YZ, classify the business records into first-priority financial data and second-priority financial data, and store them in the blockchain and the off-chain auxiliary node respectively. Based on the financial data stored in the blockchain, a hash tree model is constructed for each business record, and a multi-dimensional index is generated to perform financial data queries;

[0014] The smart contract execution module is used to write a smart contract in the blockchain. For the first-priority financial data on the chain, the smart contract is triggered to obtain the transaction score JY of each financial transaction, and a transaction score threshold PF is preset. The transaction score JY is compared and analyzed with the transaction score threshold PF to evaluate the transaction status. If the transaction status evaluation result is abnormal, the early warning mechanism is triggered to perform data collaborative adjustment;

[0015] The data collaborative analysis module is used to collect local financial data of suppliers, customers, and enterprises after the transaction status assessment result is abnormal, perform homomorphic encryption, and transmit the encrypted local financial data to the secure multi-party computing platform SMPC for joint analysis to obtain the cause of the abnormal state, generate joint analysis results, and transmit the joint analysis results to suppliers, customers, and enterprises;

[0016] The data repair module is used to locate abnormal transaction data based on the joint analysis results, repair the abnormal transaction data, update the transaction records on and off the chain based on the repaired transaction data, and generate a data repair report.

[0017] Preferably, the blockchain integration module is used to establish a connection between the enterprise's internal financial information system and the blockchain through the communication interface RESTful API, and use the communication interface RESTful API to perform two-way data transmission on and off the chain, and regularly synchronize the enterprise's financial data to the blockchain.

[0018] Preferably, the data acquisition and encryption module includes a data acquisition unit and a data encryption unit;

[0019] The data collection unit is used to use ETL tools to obtain the company's financial data from the company's internal financial information system, and pre-process the collected financial data, wherein the pre-processing includes field cleaning and data standardization, and construct a financial data set D based on the pre-processed financial data, wherein the financial data includes contract data, logistics data, and invoice data;

[0020] The contract data includes transaction amount, contract terms and signing time;

[0021] The logistics data includes transportation route and estimated arrival time;

[0022] The invoice data includes invoice type, amount and tax rate;

[0023] Based on the financial data set D, natural language processing technology is used to extract business records in the financial data set D and generate a structured table. Based on each business record in the structured table, a hash algorithm is used to generate a unique identifier, where the unique identifier includes the data type, timestamp, and data content summary;

[0024] The data encryption unit is used to encrypt each business record in the structured table based on the structured table using the symmetric encryption algorithm AES-256, generate a ciphertext Ei, and bind the ciphertext Ei to a unique identifier, and record an encryption operation log for each data encryption, wherein the encryption operation log includes the encryption time, the operating user, and the encryption result.

[0025] Preferably, the data storage module includes a hierarchical storage unit and a data query unit;

[0026] The hierarchical storage unit is used to obtain the priority score YX of each business record based on the financial data set D. The priority score YX is obtained in the following manner:

[0027]

[0028] Where, v q Indicates the number of times the business record is accessed, t s Indicates the time span from the generation of business records to the current time point, φ w Indicates the weight coefficient of the business record. Different weight coefficients are set for contract data, logistics data, and invoice data. The specific data of the weight coefficient is set by the customer based on actual conditions.

[0029] A priority score threshold YZ is preset, and the priority score YX of each business record is compared and analyzed with the priority score threshold YZ to evaluate the priority level of each business record, and perform data on-chain and off-chain operations. The specific evaluation content is as follows:

[0030] If the priority score YX is greater than or equal to the priority score threshold YZ, that is, YX ≥ YZ, the business record is determined to be first-priority financial data, and the first-priority financial data is stored on the blockchain;

[0031] If the priority score YX is less than the priority score threshold YZ, that is, YX<YZ, the business record is determined to be second-priority financial data. At this time, the second-priority financial data is stored in the off-chain auxiliary node, where the off-chain auxiliary node includes the distributed file system IPFS and the cloud storage service system.

[0032] Preferably, the data query unit is used to exchange data between the off-chain auxiliary node and the blockchain, regularly synchronize on-chain data, and build a hash tree model based on the on-chain data to perform fast data query. The specific construction process of the hash tree model is as follows:

[0033] The hash value of a single business record is used as a child node of the hash tree model. The hash values ​​of two adjacent child nodes are combined to obtain the hash value of the combined child node. The hash value of the combined child node is regarded as the parent node. The two adjacent parent nodes are combined to calculate the combined hash value of the two adjacent parent nodes. The node combination process is repeated until all child nodes are combined. The node formed by combining all child nodes is used as the root node, and the hash value of the root node is recorded. The hash value of the root node is the unique identifier of the financial data set D.

[0034] The financial data set D is sharded based on the different transaction types of the financial data. An independent hash tree model is constructed for each shard, and an independent root node is generated for each shard and recorded in the blockchain.

[0035] Generate a multidimensional index based on each business record, store the generated multidimensional index in the blockchain, build a multidimensional index table, and perform financial data query based on the hash tree model and multidimensional index table of each business record. The specific query process includes:

[0036] After the user enters the query conditions, the system quickly locates the target child node through the multidimensional index table, and obtains the hash values ​​of the child node, parent node, and root node according to the hash tree model. Finally, it verifies whether the hash value of the root node is consistent with the hash value of the root node stored in the blockchain. The multidimensional index includes the time dimension index, the amount dimension index, and the transaction type dimension index. The hash value verification process includes:

[0037] If the hash values ​​are the same, the verification is considered successful, indicating that the data has not been tampered with. The data verification status is marked as "Verification Successful" and the queried data record is output;

[0038] If the hash values ​​are different, the verification is judged to have failed, indicating that the data is abnormal, triggering an abnormality warning, marking the data verification status as "verification failed", recording the hash value, timestamp and query conditions of the abnormal data, and providing them for manual data review.

[0039] Preferably, the smart contract execution module includes a contract construction unit and an anomaly detection unit;

[0040] The contract construction unit is used to write a smart contract on the blockchain, wherein the smart contract includes a transaction number TX i Transaction Amount i , transaction timestamp T i , transaction score JY, transaction status S i and transaction score threshold PF;

[0041] Based on the smart contract, the financial data uploaded to the chain is regularly checked. When the financial data reaches the preset upload time, the smart contract is triggered to detect financial data anomalies and record the financial data. The financial data includes the contract number, current payment status, paid amount, remaining payment amount, and the percentage of contract fulfillment progress.

[0042] Preferably, the anomaly detection unit is used to obtain a transaction score JY for each financial transaction based on the first-priority financial data stored on the blockchain, and the transaction score JY is obtained in the following manner:

[0043]

[0044] Where A i represents the transaction amount of real-time financial transactions, μ A represents the mean of historical transaction amounts, σ A Indicates the standard deviation of historical transaction amounts;

[0045] A transaction scoring threshold PF is preset and compared with the transaction score JY to evaluate the transaction status. The specific evaluation contents are as follows:

[0046] If the transaction score JY is greater than or equal to the transaction score threshold PF, that is, JY ≥ PF, the transaction is considered to be in an abnormal state. At this time, the smart contract is triggered to freeze the transaction funds, mark the transaction, and issue an alarm. It also generates alarm information and abnormal transaction records, and notifies the financial management personnel of the relevant companies until the financial management personnel responds.

[0047] If the transaction score JY is less than the transaction score threshold PF, that is, JY<PF, the transaction is determined to be in a normal state. At this time, according to the transaction content, the smart contract is triggered to conduct subsequent transactions and update the contract status and transaction records of the financial transaction on the blockchain.

[0048] Preferably, the data collaborative analysis module is used to perform data collaborative analysis in combination with all parties involved in the transaction when the transaction score JY is greater than or equal to the transaction score threshold PF, that is, when the transaction is in an abnormal state. The data collaborative analysis includes:

[0049] Suppliers, customers, and enterprises encrypt their respective local financial data using a homomorphic encryption algorithm, and upload the encrypted local financial data to the secure multi-party computing platform SMPC through a secure information channel. The secure multi-party computing platform SMPC is used to conduct a joint analysis of the encrypted local financial data through distributed computing, obtain the joint analysis results, and encrypt and transmit the joint analysis results to suppliers, customers, and enterprises. The joint analysis results include data consistency verification results and conflict points of abnormal transactions.

[0050] Preferably, the data repair module is used to locate abnormal transaction data and perform data repair based on the joint analysis results, and transmit the repaired transaction data to the financial information system of each enterprise, while triggering the smart contract to record the repaired transaction data on the blockchain, including updating the payment cycle, transaction amount and contract status, and synchronously updating the financial data records on and off the blockchain to generate a data repair report, wherein the data repair report includes the data repair results and data repair records.

[0051] A financial information sharing method based on blockchain, comprising the following steps:

[0052] Step 1: Integrate blockchain into the enterprise’s financial information system and facilitate information flow between the blockchain and the financial information system.

[0053] Step 2: Based on the enterprise's financial information system, collect and pre-process the financial data to construct a financial data set D. Then, structure the financial data set D to obtain a structured table of the financial data. Then, encrypt each business record in the structured table to generate a unique identifier.

[0054] Step 3: Based on the financial data set D, obtain the priority score YX of each business record, preset the priority score threshold YZ, and compare and analyze the priority score YX with the priority score threshold YZ. The business records are divided into first-priority financial data and second-priority financial data, and stored in the blockchain and off-chain auxiliary nodes respectively. Based on the financial data stored in the blockchain, a hash tree model is constructed for each business record, and a multi-dimensional index is generated for financial data query;

[0055] Step 4: Write a smart contract in the blockchain. For the first-priority financial data on the chain, trigger the smart contract to obtain the transaction score JY for each financial transaction and preset the transaction score threshold PF. Compare and analyze the transaction score JY with the transaction score threshold PF to evaluate the transaction status. If the transaction status evaluation result is abnormal, trigger the early warning mechanism and make data collaborative adjustments.

[0056] Step 5: After the transaction status is evaluated as abnormal, the local financial data of suppliers, customers, and enterprises is collected and homomorphically encrypted. The encrypted local financial data is transmitted to the secure multi-party computing platform SMPC for joint analysis to obtain the cause of the abnormal state and generate joint analysis results. The joint analysis results are then transmitted to suppliers, customers, and enterprises.

[0057] Step 6: Based on the joint analysis results, locate the abnormal transaction data and repair the abnormal transaction data. Update the transaction records on and off the chain based on the repaired transaction data and generate a data repair report.

[0058] The present invention provides a blockchain-based financial information sharing system and method, which has the following beneficial effects:

[0059] (1) The present invention realizes data collaborative analysis through homomorphic encryption algorithm and secure multi-party computing platform SMPC to ensure the privacy and security of data between enterprises. When an abnormality occurs in a transaction, the system collects the local financial data of each enterprise, encrypts the data first, and then uploads it to the SMPC platform through a secure information channel for joint analysis. The original data always remains encrypted during the transmission, calculation and analysis process to avoid data leakage. At the same time, the joint analysis results are encrypted and transmitted to all parties. Only the analysis results are shared without sharing the original data. This design effectively solves the problem of data privacy protection when sharing data between enterprises, enabling enterprises to achieve efficient data collaborative analysis under the premise of ensuring privacy and security.

[0060] (2) The present invention uses a priority scoring mechanism to perform hierarchical storage of financial data, storing first-priority financial data on the blockchain and second-priority financial data in off-chain auxiliary nodes, including IPFS and cloud storage, effectively reducing the storage pressure of the blockchain. In addition, the system constructs a hash tree model and a multidimensional index table based on the on-chain data, supporting fast data query and verification. After the user enters the query conditions, the system quickly locates the target data through the multidimensional index table, and verifies the integrity and consistency of the data through the hash tree model, thereby achieving efficient financial data query and improving data storage management and query efficiency.

[0061] (3) The present invention uses smart contracts to automatically detect anomalies in the first-priority financial data on the chain, combines the transaction scoring mechanism JY and the preset transaction scoring threshold PF, and evaluates the transaction status in real time. When an abnormal transaction is detected, the system automatically triggers the early warning mechanism and analyzes the cause of the anomaly through the data collaborative analysis module. Based on the analysis results, the system can automatically locate the abnormal transaction data and perform data repair, while updating the data records on and off the chain and generating a data repair report. This process not only improves the efficiency of handling financial data anomalies and reduces manual intervention, but also ensures the consistency and reliability of on-chain and off-chain data, and guarantees the quality and accuracy of financial information sharing. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a block diagram of a financial information sharing system based on blockchain in the present invention.

[0063] Figure 2This is a flowchart of a blockchain-based financial information sharing method of the present invention. DETAILED DESCRIPTION

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0065] Example 1

[0066] See also Figure 1 , the present invention provides a financial information sharing system based on blockchain, including a blockchain integration module, a data acquisition and encryption module, a data storage module, a smart contract execution module, a data collaborative analysis module and a data repair module;

[0067] The blockchain integration module is used to integrate the blockchain into the financial information system within the enterprise and to transfer information between the blockchain and the financial information system;

[0068] The data collection and encryption module is used to collect financial data based on the financial information system within the enterprise, pre-process the financial data, construct a financial data set D, and perform structured processing on the financial data set D to obtain a structured table of financial data, and encrypt each business record in the structured table to generate a unique identifier;

[0069] The data storage module is used to obtain a priority score YX for each business record based on the financial data set D, preset a priority score threshold YZ, and compare and analyze the priority score YX with the priority score threshold YZ, classify the business records into first-priority financial data and second-priority financial data, and store them in the blockchain and the off-chain auxiliary node respectively. Based on the financial data stored in the blockchain, a hash tree model is constructed for each business record, and a multi-dimensional index is generated to perform financial data queries;

[0070] The smart contract execution module is used to write a smart contract in the blockchain. For the first-priority financial data on the chain, the smart contract is triggered to obtain the transaction score JY of each financial transaction, and a transaction score threshold PF is preset. The transaction score JY is compared and analyzed with the transaction score threshold PF to evaluate the transaction status. If the transaction status evaluation result is abnormal, the early warning mechanism is triggered to perform data collaborative adjustment;

[0071] The data collaborative analysis module is used to collect local financial data of suppliers, customers, and enterprises after the transaction status assessment result is abnormal, perform homomorphic encryption, and transmit the encrypted local financial data to the secure multi-party computing platform SMPC for joint analysis to obtain the cause of the abnormal state, generate joint analysis results, and transmit the joint analysis results to suppliers, customers, and enterprises;

[0072] The data repair module is used to locate abnormal transaction data based on the joint analysis results, repair the abnormal transaction data, update the transaction records on and off the chain based on the repaired transaction data, and generate a data repair report.

[0073] In the embodiment, through the blockchain integration module, data collection and encryption module, data storage module, smart contract execution module, data collaborative analysis module and data repair module, the problems of low efficiency, insufficient privacy protection and data inconsistency in the traditional financial information sharing process are effectively solved. The blockchain integration module realizes the seamless connection between the blockchain and the enterprise financial information system, and ensures the real-time and traceability of data flow. The data collection and encryption module pre-processes, structures and encrypts the enterprise financial data, generates a unique identifier, ensures data integrity and tamper-proofness, and realizes data privacy protection through the AES-256 encryption algorithm. The data storage module divides the data into first-priority financial data and second-priority financial data through the priority scoring mechanism, and stores them in the blockchain and the off-chain auxiliary node respectively, which not only reduces the storage pressure of the blockchain, but also improves the storage Efficiency, and fast data query and verification are achieved through hash trees and multi-dimensional indexes, ensuring the efficiency and accuracy of data access. The smart contract execution module automatically triggers smart contracts based on the on-chain data, performs transaction anomaly detection in real time, and improves the automation and response speed of data processing. If an anomaly is detected, the data collaborative analysis module conducts multi-party data joint analysis under the premise of protecting data privacy through homomorphic encryption and secure multi-party computing platform SMPC, accurately locates the cause of the anomaly, and ensures privacy security and collaborative analysis efficiency in the data sharing process. Finally, the data repair module repairs the abnormal data according to the collaborative analysis results and updates it synchronously on and off the chain, generates a data repair report, and ensures data consistency and integrity. In summary, the present invention realizes safe, privacy-protecting, efficient and traceable financial information sharing, and improves the intelligence level and collaborative efficiency of financial data management between enterprises.

[0074] Example 2

[0075] Please refer to Figure 1Specifically: the blockchain integration module is used to establish a connection between the enterprise's internal financial information system and the blockchain through the communication interface RESTful API, and use the communication interface RESTful API to perform two-way data transmission on and off the chain, and regularly synchronize the enterprise's financial data to the blockchain.

[0076] In the embodiment, an efficient connection is established between the enterprise's internal financial information system and the blockchain through the communication interface RESTful API, realizing two-way data transmission on and off the chain, and regularly synchronizing the enterprise's financial data to the blockchain. The integration and data synchronization mechanism of this module effectively solves the problems of data silos and system fragmentation in traditional financial information sharing, opens up the data flow channel between the enterprise's internal system and the blockchain platform, and ensures the real-time and accuracy of data transmission. Through regular synchronization, the system can automatically upload financial data to the chain, reducing manual intervention and delays in data upload, thereby improving the efficiency of data synchronization. In addition, as a standardized communication interface, RESTful API has the advantages of lightweight, high compatibility and easy scalability. It can support the access of multiple financial systems and realize the rapid integration and sharing of financial data across platforms and departments of the enterprise. At the same time, the tamper-proof characteristics of the on-chain data enhance the credibility of the data, provide reliable support for the transparent management and real-time decision-making of the enterprise's financial data, and meet the comprehensive needs of the enterprise for data security, accuracy and efficiency.

[0077] Example 3

[0078] Please refer to Figure 1 ,Specifically: the data acquisition and encryption module includes a data acquisition unit and a data encryption unit;

[0079] The data collection unit is used to use ETL tools to obtain the company's financial data from the company's internal financial information system, and pre-process the collected financial data, wherein the pre-processing includes field cleaning and data standardization, and construct a financial data set D based on the pre-processed financial data, wherein the financial data includes contract data, logistics data, and invoice data;

[0080] The contract data includes transaction amount, contract terms and signing time;

[0081] The logistics data includes transportation route and estimated arrival time;

[0082] The invoice data includes invoice type, amount and tax rate;

[0083] Based on the financial data set D, natural language processing technology is used to extract business records in the financial data set D and generate a structured table. Based on each business record in the structured table, a hash algorithm is used to generate a unique identifier, where the unique identifier includes the data type, timestamp, and data content summary;

[0084] The data encryption unit is used to encrypt each business record in the structured table based on the structured table using the symmetric encryption algorithm AES-256, generate a ciphertext Ei, and bind the ciphertext Ei to a unique identifier, and record an encryption operation log for each data encryption, wherein the encryption operation log includes the encryption time, the operating user, and the encryption result.

[0085] In the embodiment, the data collection unit and the data encryption unit work together to achieve efficient collection, standardized preprocessing and encrypted storage of corporate financial data, solving the problems of irregular data processing and insufficient security in the prior art. First, the data collection unit uses ETL tools to automatically extract data from the company's internal financial information system, reducing manual intervention and improving the efficiency and accuracy of data collection. Through field cleaning and data standardization, the system effectively handles problems such as data redundancy and format inconsistency, ensuring the integrity and standardization of financial data. At the same time, natural language processing technology NLP is used to intelligently extract business records and generate structured tables, laying a standardized foundation for subsequent data analysis and processing. Secondly, a unique identifier is generated for each business record through a hash algorithm. The identifier contains the data type, timestamp and data content summary, ensuring the integrity of the data. Uniqueness and traceability help to quickly locate target data during data sharing and verification, while preventing data tampering and improving data integrity and credibility. Finally, the data encryption unit uses the AES-256 symmetric encryption algorithm to encrypt structured data, generate encrypted ciphertext Ei, and bind the ciphertext Ei to a unique identifier to ensure security during data transmission and storage. The system also records encryption logs for each encryption operation, including encryption time, operating user, and encryption results, to facilitate subsequent audits and traceability, further enhancing the system's security management capabilities, ensuring efficient collection, data integrity, privacy protection, and secure sharing of corporate financial data, effectively solving the problems of inefficient data processing and insufficient data security in the traditional financial data sharing process, and meeting the requirements of modern enterprises for efficient, standardized, and secure financial data management.

[0086] Example 4

[0087] Please refer to Figure 1 ,Specifically: the data storage module includes a hierarchical storage unit and a data query unit;

[0088] The hierarchical storage unit is used to obtain the priority score YX of each business record based on the financial data set D. The priority score YX is obtained in the following manner:

[0089]

[0090] Where, v q Indicates the number of times the business record is accessed, t s Indicates the time span from the generation of business records to the current time point, φ w Indicates the weight coefficient of the business record. Different weight coefficients are set for contract data, logistics data, and invoice data. The specific data of the weight coefficient is set by the customer based on actual conditions.

[0091] A priority score threshold YZ is preset, and the priority score YX of each business record is compared and analyzed with the priority score threshold YZ to evaluate the priority level of each business record, and perform data on-chain and off-chain operations. The specific evaluation content is as follows:

[0092] If the priority score YX is greater than or equal to the priority score threshold YZ, that is, YX ≥ YZ, the business record is determined to be first-priority financial data, and the first-priority financial data is stored on the blockchain;

[0093] If the priority score YX is less than the priority score threshold YZ, that is, YX<YZ, the business record is determined to be second-priority financial data. At this time, the second-priority financial data is stored in the off-chain auxiliary node, where the off-chain auxiliary node includes the distributed file system IPFS and the cloud storage service system to reduce the storage pressure of the blockchain.

[0094] The data query unit is used to exchange data between the off-chain auxiliary node and the blockchain, regularly synchronize on-chain data, and build a hash tree model based on the on-chain data to perform fast data query. The specific construction process of the hash tree model is as follows:

[0095] The hash value of a single business record is used as a child node of the hash tree model. The hash values ​​of two adjacent child nodes are combined to obtain the hash value of the combined child node. The hash value of the combined child node is regarded as the parent node. The two adjacent parent nodes are combined to calculate the combined hash value of the two adjacent parent nodes. The node combination process is repeated until all child nodes are combined. The node formed by combining all child nodes is used as the root node, and the hash value of the root node is recorded. The hash value of the root node is the unique identifier of the financial data set D, which is used for online storage and verification.

[0096] The financial data set D is sharded based on the different transaction types of the financial data. An independent hash tree model is constructed for each shard, and an independent root node is generated for each shard and recorded in the blockchain.

[0097] Generate a multidimensional index based on each business record, store the generated multidimensional index in the blockchain, build a multidimensional index table, and perform financial data query based on the hash tree model and multidimensional index table of each business record. The specific query process includes:

[0098] After the user enters the query conditions, the system quickly locates the target child node through the multidimensional index table, and obtains the hash values ​​of the child node, parent node, and root node according to the hash tree model. Finally, it verifies whether the hash value of the root node is consistent with the hash value of the root node stored in the blockchain. Among them, the multidimensional index includes the time dimension index, the amount dimension index, and the transaction type dimension index. The target child node refers to the child node corresponding to the specific business record that the system quickly locates through the multidimensional index table based on the query conditions entered when the user performs a financial data query. The hash value verification process includes:

[0099] If the hash values ​​are the same, the verification is considered successful, indicating that the data has not been tampered with. The data verification status is marked as "Verification Successful" and the queried data record is output;

[0100] If the hash values ​​are different, the verification is judged to have failed, indicating that the data is abnormal, triggering an abnormality warning, marking the data verification status as "verification failed", recording the hash value, timestamp and query conditions of the abnormal data, and providing them for manual data review.

[0101] In the embodiment, efficient data storage, fast query and security verification are achieved through the hierarchical storage unit and the data query unit. First, the hierarchical storage unit scores the business records according to the priority score YX based on the financial data set D, and combines the preset priority score threshold YZ to divide the data into first-priority financial data and second-priority financial data. The first-priority financial data is stored on the blockchain to ensure the immutability and transparency of key data. The second-priority financial data is stored in the off-chain auxiliary nodes, including IPFS and cloud storage, which effectively reduces the storage pressure of the blockchain and improves the storage efficiency of the system. In addition, the data query unit constructs a hash The tree model and multidimensional index table enable rapid location and integrity verification of financial data. After the user enters the query conditions, the system uses the multidimensional index table to quickly locate the target child node and performs node verification through the hash tree model to ensure that the data has not been tampered with. Once a data anomaly is detected, the system immediately triggers the early warning mechanism and provides anomaly information, ensuring the accuracy and security of data queries. While improving storage efficiency, this system achieves rapid retrieval and verification of financial data, ensuring distributed management of data storage, high concurrent access performance, and data tampering protection, effectively solving the problems of high storage pressure, low query efficiency, and insufficient data consistency verification in existing technologies.

[0102] Example 5

[0103] Please refer to Figure 1 ,Specifically: the smart contract execution module includes a contract construction unit and an anomaly detection unit;

[0104] The contract construction unit is used to write a smart contract on the blockchain, wherein the smart contract includes a transaction number TX i Transaction Amount i , transaction timestamp T i , transaction score JY, transaction status S i and transaction score threshold PF;

[0105] Based on the smart contract, the financial data uploaded to the chain is regularly checked. When the financial data reaches the preset upload time, the smart contract is triggered to detect financial data anomalies and record the financial data. The financial data includes the contract number, current payment status, paid amount, remaining payment amount, and the percentage of contract fulfillment progress.

[0106] The anomaly detection unit is used to obtain a transaction score JY for each financial transaction based on the first-priority financial data stored on the blockchain. The transaction score JY is obtained in the following manner:

[0107]

[0108] Where A i represents the transaction amount of real-time financial transactions, μ A represents the mean of historical transaction amounts, σ A Indicates the standard deviation of historical transaction amounts;

[0109] A transaction scoring threshold PF is preset and compared with the transaction score JY to evaluate the transaction status. The specific evaluation contents are as follows:

[0110] If the transaction score JY is greater than or equal to the transaction score threshold PF, that is, JY ≥ PF, the transaction is considered to be in an abnormal state. At this time, the smart contract is triggered to freeze the transaction funds, mark the transaction, and issue an alarm. It also generates alarm information and abnormal transaction records, and notifies the financial management personnel of the relevant companies until the financial management personnel responds.

[0111] If the transaction score JY is less than the transaction score threshold PF, that is, JY<PF, the transaction is determined to be in a normal state. At this time, according to the transaction content, the smart contract is triggered to conduct subsequent transactions and update the contract status and transaction records of the financial transaction on the blockchain.

[0112] In the embodiment, the smart contract execution module, including the contract construction unit and the anomaly detection unit, effectively solves the problems of insufficient data monitoring, delayed anomaly detection and lack of automated execution capabilities in traditional financial information sharing. First, the contract construction unit writes a smart contract based on blockchain technology, covering transaction number TX i Transaction Amount i , transaction timestamp T i , transaction score JY, transaction status S i And the transaction scoring threshold PF, through the preset chain time, regularly detects the on-chain financial data to ensure that the data is verified and executed on time, and automatically records key information such as contract number, payment status and performance progress, realizing real-time tracking and full-process management of financial data, improving the transparency and integrity of the data. Secondly, the anomaly detection unit uses the transaction scoring mechanism to perform real-time analysis on the high-priority financial data stored on the chain. Combined with the average value of historical transaction amount μ A Standard deviation σ from historical transaction amounts A , calculate the transaction score JY of the financial transaction, and compare the transaction score JY with the preset transaction score threshold PF. When it is detected that the transaction score JY is greater than or equal to the transaction score threshold PF, the system automatically freezes the transaction funds, marks the abnormal status and triggers the early warning mechanism, generates alarm information and notifies relevant financial management personnel to ensure that abnormal transactions are handled in a timely manner, reduce transaction risks, and realize automatic monitoring, abnormality detection and response of financial transaction status. The intelligent contract drives the automated execution of the entire process, greatly reducing manual intervention and ensuring the efficiency, timeliness and security of the transaction process. At the same time, the system stores and synchronizes abnormal status and contract data on the blockchain to ensure that the data cannot be tampered with, enhancing the credibility of financial information and the security of sharing.

[0113] Example 6

[0114] Please refer to Figure 1 Specifically, the data collaborative analysis module is used to perform data collaborative analysis with all parties involved in the transaction when the transaction score JY is greater than or equal to the transaction score threshold PF, that is, when the transaction is in an abnormal state. The data collaborative analysis includes:

[0115] Suppliers, customers, and enterprises encrypt their local financial data using a homomorphic encryption algorithm and upload the encrypted local financial data to the secure multi-party computing platform (SMPC) via a secure information channel. SMPC then performs a joint analysis on the encrypted local financial data through distributed computing, obtains the joint analysis results, and transmits them encrypted to suppliers, customers, and enterprises. The joint analysis results include data consistency verification results and conflict points of abnormal transactions.

[0116] The secure multi-party computing platform SMPC is used to achieve secure data sharing among multiple enterprises. The original data is encrypted throughout the process and will not be leaked during transmission, calculation and analysis. Multiple enterprises only share joint analysis results, not original data, thus achieving privacy protection of corporate financial data.

[0117] In the embodiment, through the data collaborative analysis module, combined with the secure multi-party computing platform SMPC and homomorphic encryption technology, the secure sharing and joint analysis of financial data between enterprises under the premise of privacy protection is realized. When the transaction score JY exceeds the preset transaction score threshold PF, the system automatically triggers the data collaborative analysis process. Suppliers, customers and enterprises will encrypt their local financial data in a homomorphic manner to ensure that the original data is transmitted and calculated in an encrypted state. After uploading it to the SMPC platform through a secure information channel, the SMPC platform will conduct a joint analysis of the encrypted data based on distributed computing to generate joint analysis results such as data consistency verification results and abnormal transaction conflict points. This process ensures that the data is The encryption status during transmission, calculation and analysis avoids the risk of leakage of original data and realizes the privacy protection requirements when sharing data between enterprises. In addition, the joint analysis results are returned to each enterprise after encryption, ensuring that each party can only obtain the analysis results and it is difficult to view the original data of other parties, effectively eliminating data security and privacy concerns. Through this design, the present invention solves the problem of insufficient privacy protection in traditional financial data sharing, while improving the efficiency of abnormal transaction detection and processing, promoting the feasibility and security of cross-enterprise data collaborative analysis, providing reliable and accurate data support for financial management and decision-making between enterprises, and effectively improving the security, availability and privacy protection capabilities of the system.

[0118] Example 7

[0119] Please refer to Figure 1 Specifically: the data repair module is used to locate abnormal transaction data and perform data repair based on the joint analysis results, and transmit the repaired transaction data to the financial information system of each enterprise. At the same time, it triggers the smart contract to record the repaired transaction data on the blockchain, including updating the payment cycle, transaction amount and contract status, and synchronously updates the financial data records on and off the blockchain to generate a data repair report, wherein the data repair report includes data repair results and data repair records.

[0120] In the implementation, the results of the joint analysis were used to efficiently locate and accurately repair abnormal transaction data, forming a complete process of anomaly discovery - analysis and diagnosis - repair feedback - and closed-loop management. First, the data repair module accurately locates the transaction data that generates anomalies based on the joint analysis results and performs targeted repair operations to ensure the authenticity and accuracy of the data. The repaired data is then transmitted to the financial information systems of each enterprise through an automatic synchronization mechanism, achieving consistent updates of on-chain and off-chain data. At the same time, the smart contract is triggered to upload the repaired data to the chain in real time, including key information such as the updated payment cycle, transaction amount, and contract status, thereby ensuring the integrity, immutability, and credibility of the data. In addition, the system automatically generates a data repair report that details the repair results, repair time, and operation logs, providing traceable records to facilitate subsequent audits and management by the enterprise, reducing manual intervention, improving repair efficiency, ensuring data consistency, transparency, and security, further enhancing the coordination and standardization of enterprise financial management, avoiding the spread of risks caused by data errors, and effectively supporting data credibility and decision-making accuracy in the process of enterprise financial information sharing.

[0121] Example 8

[0122] Please refer to Figure 2 ,Specifically: A financial information sharing method based on blockchain, including the following steps,

[0123] Step 1: Integrate blockchain into the enterprise’s financial information system and facilitate information flow between the blockchain and the financial information system.

[0124] Step 2: Based on the enterprise's financial information system, collect and pre-process the financial data to construct a financial data set D. Then, structure the financial data set D to obtain a structured table of the financial data. Then, encrypt each business record in the structured table to generate a unique identifier.

[0125] Step 3: Based on the financial data set D, obtain the priority score YX of each business record, preset the priority score threshold YZ, and compare and analyze the priority score YX with the priority score threshold YZ. The business records are divided into first-priority financial data and second-priority financial data, and stored in the blockchain and off-chain auxiliary nodes respectively. Based on the financial data stored in the blockchain, a hash tree model is constructed for each business record, and a multi-dimensional index is generated for financial data query;

[0126] Step 4: Write a smart contract in the blockchain. For the first-priority financial data on the chain, trigger the smart contract to obtain the transaction score JY for each financial transaction and preset the transaction score threshold PF. Compare and analyze the transaction score JY with the transaction score threshold PF to evaluate the transaction status. If the transaction status evaluation result is abnormal, trigger the early warning mechanism and make data collaborative adjustments.

[0127] Step 5: After the transaction status is evaluated as abnormal, the local financial data of suppliers, customers, and enterprises is collected and homomorphically encrypted. The encrypted local financial data is transmitted to the secure multi-party computing platform SMPC for joint analysis to obtain the cause of the abnormal state and generate joint analysis results. The joint analysis results are then transmitted to suppliers, customers, and enterprises.

[0128] Step 6: Based on the joint analysis results, locate the abnormal transaction data and repair the abnormal transaction data. Update the transaction records on and off the chain based on the repaired transaction data and generate a data repair report.

[0129] In the embodiment, the internal financial information system of the enterprise is integrated through the blockchain, which opens up the information flow channel and improves the real-time and automation level of data sharing. Secondly, through the data hierarchical storage and encryption mechanism, the system manages the financial data in a hierarchical manner according to the priority score, effectively reducing the storage pressure of the blockchain. At the same time, based on the hash tree model and multi-dimensional indexing technology, it realizes the rapid query and integrity verification of the on-chain data, improving the query efficiency and data security. In addition, the system automatically detects and warns of financial data anomalies through smart contracts, and combines the secure multi-party computing platform SMPC to conduct joint analysis of abnormal transactions, locates the cause of the anomaly while protecting data privacy, and ensures the unity of data security sharing and privacy protection. Finally, the system achieves the consistency and integrity of on-chain and off-chain data through the repair and synchronous update of abnormal data, forming a closed-loop process of data collection, storage, verification, analysis and repair, and improving the efficiency, transparency and security of financial data sharing.

[0130] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A financial information sharing system based on blockchain, characterized by: It includes blockchain integration module, data collection and encryption module, data storage module, smart contract execution module, data collaborative analysis module and data repair module; The blockchain integration module is used to integrate the blockchain into the financial information system within the enterprise and to transfer information between the blockchain and the financial information system; The data collection and encryption module is used to collect financial data based on the financial information system within the enterprise, pre-process the financial data, construct a financial data set D, and perform structured processing on the financial data set D to obtain a structured table of financial data, and encrypt each business record in the structured table to generate a unique identifier; The data storage module is used to obtain a priority score YX for each business record based on the financial data set D, preset a priority score threshold YZ, and compare and analyze the priority score YX with the priority score threshold YZ, classify the business records into first-priority financial data and second-priority financial data, and store them in the blockchain and the off-chain auxiliary node respectively. Based on the financial data stored in the blockchain, a hash tree model is constructed for each business record, and a multi-dimensional index is generated to perform financial data queries; The smart contract execution module is used to write a smart contract in the blockchain. For the first-priority financial data on the chain, the smart contract is triggered to obtain the transaction score JY of each financial transaction, and a transaction score threshold PF is preset. The transaction score JY is compared and analyzed with the transaction score threshold PF to evaluate the transaction status. If the transaction status evaluation result is abnormal, the early warning mechanism is triggered to perform data collaborative adjustment; The data collaborative analysis module is used to collect local financial data of suppliers, customers, and enterprises after the transaction status assessment result is abnormal, perform homomorphic encryption, and transmit the encrypted local financial data to the secure multi-party computing platform SMPC for joint analysis to obtain the cause of the abnormal state, generate joint analysis results, and transmit the joint analysis results to suppliers, customers, and enterprises; The data repair module is used to locate abnormal transaction data based on the joint analysis results, repair the abnormal transaction data, update the transaction records on and off the chain based on the repaired transaction data, and generate a data repair report.

2. The blockchain-based financial information sharing system according to claim 1, characterized in that: The blockchain integration module is used to establish a connection between the enterprise's internal financial information system and the blockchain through the communication interface RESTful API, and use the communication interface RESTful API to perform two-way data transmission on and off the chain, and regularly synchronize the enterprise's financial data to the blockchain.

3. The blockchain-based financial information sharing system according to claim 2, characterized in that: The data acquisition and encryption module includes a data acquisition unit and a data encryption unit; The data collection unit is used to use ETL tools to obtain the company's financial data from the company's internal financial information system, and pre-process the collected financial data, wherein the pre-processing includes field cleaning and data standardization, and construct a financial data set D based on the pre-processed financial data, wherein the financial data includes contract data, logistics data, and invoice data; The contract data includes transaction amount, contract terms and signing time; The logistics data includes transportation route and estimated arrival time; The invoice data includes invoice type, amount and tax rate; Based on the financial data set D, natural language processing technology is used to extract business records in the financial data set D and generate a structured table. Based on each business record in the structured table, a hash algorithm is used to generate a unique identifier, where the unique identifier includes the data type, timestamp, and data content summary; The data encryption unit is used to encrypt each business record in the structured table based on the structured table using the symmetric encryption algorithm AES-256, generate a ciphertext Ei, and bind the ciphertext Ei to a unique identifier, and record an encryption operation log for each data encryption, wherein the encryption operation log includes the encryption time, the operating user, and the encryption result.

4. The blockchain-based financial information sharing system according to claim 3, characterized in that: The data storage module includes a hierarchical storage unit and a data query unit; The hierarchical storage unit is used to obtain the priority score YX of each business record based on the financial data set D. The priority score YX is obtained in the following manner: Where, v q Indicates the number of times the business record is accessed, t s Indicates the time span from the generation of business records to the current time point, φ w Indicates the weight coefficient of the business record. Different weight coefficients are set for contract data, logistics data, and invoice data. The specific data of the weight coefficient is set by the customer based on actual conditions. A priority score threshold YZ is preset, and the priority score YX of each business record is compared and analyzed with the priority score threshold YZ to evaluate the priority level of each business record, and perform data on-chain and off-chain operations. The specific evaluation content is as follows: If the priority score YX is greater than or equal to the priority score threshold YZ, that is, YX ≥ YZ, the business record is determined to be first-priority financial data, and the first-priority financial data is stored on the blockchain; If the priority score YX is less than the priority score threshold YZ, that is, YX<YZ, the business record is determined to be second-priority financial data. At this time, the second-priority financial data is stored in the off-chain auxiliary node, where the off-chain auxiliary node includes the distributed file system IPFS and the cloud storage service system.

5. The blockchain-based financial information sharing system according to claim 4, characterized in that: The data query unit is used to exchange data between the off-chain auxiliary node and the blockchain, regularly synchronize on-chain data, and build a hash tree model based on the on-chain data to perform fast data query. The specific construction process of the hash tree model is as follows: The hash value of a single business record is used as a child node of the hash tree model. The hash values ​​of two adjacent child nodes are combined to obtain the hash value of the combined child node. The hash value of the combined child node is regarded as the parent node. The two adjacent parent nodes are combined to calculate the combined hash value of the two adjacent parent nodes. The node combination process is repeated until all child nodes are combined. The node formed by combining all child nodes is used as the root node, and the hash value of the root node is recorded. The hash value of the root node is the unique identifier of the financial data set D. The financial data set D is sharded based on the different transaction types of the financial data. An independent hash tree model is constructed for each shard, and an independent root node is generated for each shard and recorded in the blockchain. Generate a multidimensional index based on each business record, store the generated multidimensional index in the blockchain, build a multidimensional index table, and perform financial data query based on the hash tree model and multidimensional index table of each business record. The specific query process includes: After the user enters the query conditions, the system quickly locates the target child node through the multidimensional index table, and obtains the hash values ​​of the child node, parent node, and root node according to the hash tree model. Finally, it verifies whether the hash value of the root node is consistent with the hash value of the root node stored in the blockchain. The multidimensional index includes the time dimension index, the amount dimension index, and the transaction type dimension index. The hash value verification process includes: If the hash values ​​are the same, the verification is considered successful, indicating that the data has not been tampered with. The data verification status is marked as "Verification Successful" and the queried data record is output; If the hash values ​​are different, the verification is considered to have failed, indicating a data anomaly. This triggers an anomaly warning, marks the data verification status as "Verification Failed," and records the hash value, timestamp, and query conditions of the abnormal data for manual data review.

6. The blockchain-based financial information sharing system according to claim 5, characterized in that: The smart contract execution module includes a contract construction unit and an anomaly detection unit; The contract construction unit is used to write a smart contract on the blockchain, wherein the smart contract includes a transaction number TX i Transaction Amount i , transaction timestamp T i , transaction score JY, transaction status S i and transaction score threshold PF; Based on the smart contract, the financial data uploaded to the chain is regularly checked. When the financial data reaches the preset upload time, the smart contract is triggered to detect financial data anomalies and record the financial data. The financial data includes the contract number, current payment status, paid amount, remaining payment amount, and the percentage of contract fulfillment progress.

7. The blockchain-based financial information sharing system according to claim 6, characterized in that: The anomaly detection unit is used to obtain a transaction score JY for each financial transaction based on the first-priority financial data stored on the blockchain. The transaction score JY is obtained in the following manner: Where A i represents the transaction amount of real-time financial transactions, μ A represents the mean of historical transaction amounts, σ A Indicates the standard deviation of historical transaction amounts; A transaction scoring threshold PF is preset and compared with the transaction score JY to evaluate the transaction status. The specific evaluation contents are as follows: If the transaction score JY is greater than or equal to the transaction score threshold PF, that is, JY ≥ PF, the transaction is considered to be in an abnormal state. At this time, the smart contract is triggered to freeze the transaction funds, mark the transaction, and issue an alarm. It also generates alarm information and abnormal transaction records, and notifies the financial management personnel of the relevant companies until the financial management personnel responds. If the transaction score JY is less than the transaction score threshold PF, that is, JY<PF, the transaction is determined to be in a normal state. At this time, according to the transaction content, the smart contract is triggered to conduct subsequent transactions and update the contract status and transaction records of the financial transaction on the blockchain.

8. The blockchain-based financial information sharing system according to claim 7, characterized in that: The data collaborative analysis module is used to perform data collaborative analysis in conjunction with all parties involved in the transaction when the transaction score JY is greater than or equal to the transaction score threshold PF, that is, when the transaction is in an abnormal state. The data collaborative analysis includes: Suppliers, customers, and enterprises encrypt their respective local financial data using a homomorphic encryption algorithm, and upload the encrypted local financial data to the secure multi-party computing platform SMPC through a secure information channel. The secure multi-party computing platform SMPC is used to conduct a joint analysis of the encrypted local financial data through distributed computing, obtain the joint analysis results, and encrypt and transmit the joint analysis results to suppliers, customers, and enterprises. The joint analysis results include data consistency verification results and conflict points of abnormal transactions.

9. The blockchain-based financial information sharing system according to claim 8, characterized in that: The data repair module is used to locate abnormal transaction data and perform data repair based on the joint analysis results, and transmit the repaired transaction data to the financial information system of each enterprise. At the same time, it triggers the smart contract to record the repaired transaction data on the blockchain, including updating the payment cycle, transaction amount and contract status, and synchronously updates the financial data records on and off the blockchain to generate a data repair report, wherein the data repair report includes the data repair results and data repair records.

10. A blockchain-based financial information sharing method, used to implement the blockchain-based financial information sharing system described in any one of claims 1 to 9, characterized in that: The following steps are included: Step 1: Integrate blockchain into the enterprise’s financial information system and facilitate information flow between the blockchain and the financial information system. Step 2: Based on the enterprise's financial information system, collect and pre-process the financial data to construct a financial data set D. Then, structure the financial data set D to obtain a structured table of the financial data. Then, encrypt each business record in the structured table to generate a unique identifier. Step 3: Based on the financial data set D, obtain the priority score YX of each business record, preset the priority score threshold YZ, and compare and analyze the priority score YX with the priority score threshold YZ. The business records are divided into first-priority financial data and second-priority financial data, and stored in the blockchain and off-chain auxiliary nodes respectively. Based on the financial data stored in the blockchain, a hash tree model is constructed for each business record, and a multi-dimensional index is generated for financial data query; Step 4: Write a smart contract in the blockchain. For the first-priority financial data on the chain, trigger the smart contract to obtain the transaction score JY for each financial transaction and preset the transaction score threshold PF. Compare and analyze the transaction score JY with the transaction score threshold PF to evaluate the transaction status. If the transaction status evaluation result is abnormal, trigger the early warning mechanism and make data collaborative adjustments. Step 5: After the transaction status is evaluated as abnormal, the local financial data of suppliers, customers, and enterprises is collected and homomorphically encrypted. The encrypted local financial data is transmitted to the secure multi-party computing platform SMPC for joint analysis to obtain the cause of the abnormal state and generate joint analysis results. The joint analysis results are then transmitted to suppliers, customers, and enterprises. Step 6: Based on the joint analysis results, locate the abnormal transaction data and repair the abnormal transaction data. Update the transaction records on and off the chain based on the repaired transaction data and generate a data repair report.

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