Financial data processing system based on block chain

Abstract

The invention relates to the technical field of data processing, in particular to a financial data processing system based on a block chain, which comprises an access chain authorization module, a write-in arbitration scheduling module, a voucher path identification module, a structure back adjustment point module and a chain type result output module. According to the method, the stability score is calculated according to the field calling sequence difference, the calling interval time difference and the calling return content consistency of the node access behavior log, the nodes with stable access behaviors are screened, and block access permission mapping is formed; a sorting label is constructed based on a transaction timestamp and a fund transaction amount to realize sorting of concurrent transaction priorities, dynamic matching judgment is performed through a public key address list and a multi-signature access threshold, and link access path redirection is formed, so that the possibility that a node tampers data is reduced, and the transaction efficiency is improved. And according to the chain segment block height, the relay node confirmation state and the tail end data field variation value, sequence verification and index tracing are carried out, so that the tracing capability of the financial transaction data is obviously improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a financial data processing system based on blockchain. Background Art

[0002] The field of data processing technology primarily involves the entire process of acquiring, cleaning, converting, storing, analyzing, and outputting raw data, with the goal of extracting valuable information from massive, complex, or heterogeneous data. This area encompasses data structure optimization, storage architecture design, data flow control, concurrent processing algorithms, data consistency mechanisms, and efficient query and retrieval methods. Typical implementations include data processing based on database management systems, batch and stream processing solutions supported by distributed computing platforms, and specialized data processing models for specific business scenarios. This technical field focuses on the efficient organization and management of structured, semi-structured, and unstructured data while ensuring processing efficiency, accuracy, and security.

[0003] The financial data processing system is a data processing system designed for financial business scenarios, primarily used to process large-scale financial data, including transaction records, risk indicators, market conditions, and customer behavior. Through the collection, standardization, analysis, calculation, and structured storage of financial data, the system supports specific applications such as risk assessment, transaction auditing, compliance testing, portfolio management, and customer profiling. It is designed to meet the financial business's demand for high real-time, high reliability, and high accuracy processing, enhancing financial institutions' capabilities in regulatory compliance, operational optimization, and intelligent decision-making.

[0004] When processing financial data, traditional processing systems use a unified, standardized model for analyzing and processing data such as transaction records and risk indicators. They fail to make detailed distinctions and controls regarding node stability, the order of concurrent transactions, and data access permissions. This lack of evaluation and screening of node access stability can easily lead to unstable nodes continuously participating in data writes, increasing the risk of data anomalies and loss. During the concurrent transaction write phase, traditional systems lack a clear sorting mechanism for transaction priorities, which often results in chaotic sorting and resource competition when processing concurrent transaction requests, leading to data processing delays or even failures. Traditional systems also lack specific hierarchical controls over transaction access permissions, exposing sensitive data to the risk of improper access and reducing the security and compliance of financial data. For example, when a large number of financial transactions occur simultaneously, the failure to accurately sort and control permissions can make transaction audits difficult, impacting the audit efficiency and risk prevention capabilities of financial institutions. Summary of the Invention

[0005] The purpose of this invention is to solve the shortcomings of the existing technology and propose a financial data processing system based on blockchain.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a financial data processing system based on blockchain, the system comprising: The access chain authorization module obtains the access behavior log records of the nodes within three cycles, calculates the access stability score based on the difference in field call order, the difference in call interval time, and the consistency ratio of call return content, filters out nodes with scores greater than the benchmark value, and generates a block access permission mapping group; The write arbitration scheduling module calls the block access permission mapping group, calculates the priority score according to the transaction timestamp and the transaction amount, compares the priority scores in order to build a write queue, and generates a multi-node transaction write order queue; The credential path identification module calls the multi-node transaction write order queue to determine whether the access control level is less than the data sensitivity level label. If so, it is set as a read-only chain identifier; if so, it is set as a full-chain traceability identifier, and generates a credential-driven chain path label set; The structure callback node module calls the credential-driven chain path label set, compares it with the access control level in the access credential, and determines whether it meets the multi-signature access threshold set in the link. If not, it appends a path redirection tag, builds a path status list, and generates an access chain redirection structure group.

[0007] The present invention has the following improvements: the block access permission mapping group includes a node behavior continuity score record, a node periodic access stability label and a permission allocation level table; the multi-node transaction write order queue includes a sorting priority label set, a cross-node time scheduling index and a transaction conflict mediation identifier; the credential-driven chain path label set specifically includes a chain access control tag, a path selection level identifier and a credential matching path comparison table; the access chain redirection structure group includes a redirection path mapping table, a path verification failure index and a chain segment access fallback node set.

[0008] The present invention is improved in that the access chain authorization module includes: The behavior log collection submodule obtains the node's access behavior logs within three consecutive cycles, calls the three data fields of transaction details, account balance changes, and credit risk scores, establishes an access record set in chronological order of access behavior, and archives the data according to the source node to generate an access behavior log summary table; The stability score calculation submodule extracts the data call sequence, call time interval, and result return content associated with each node based on the access behavior log summary table, calculates the field order difference value, interval difference value, and result consistency ratio, calculates the access stability score value list, establishes a score distribution set based on the concentration of the score values, and obtains the node stability score set; The node permission screening submodule calls the node stability score set, compares each node score value with the set access stability benchmark value, selects nodes with scores higher than the benchmark value, marks the access permission level and constructs a node permission mapping sequence to generate a block access permission mapping group.

[0009] The present invention is improved in that the write arbitration scheduling module includes: The time tag extraction submodule calls the block access permission mapping group to obtain the corresponding transaction timestamp, network delay time, block packaging time, and fund transaction amount in the transaction data, matches the fields with the node identifiers in the block access permission mapping group, and establishes a field comparison table between transaction records and nodes to obtain a transaction parameter matching set; The priority score calculation submodule calls the transaction parameter matching set, normalizes and converts the difference values ​​of the fields, calculates and obtains the priority score value of the transaction, and generates a transaction priority score set; The sorting queue generation submodule arranges the transaction numbers in descending order based on the transaction priority score set and the score value of each transaction, generates a sorting index corresponding to the node identifier and the transaction ID, constructs a transaction record sorting table, and obtains a multi-node transaction write order queue.

[0010] The present invention is improved in that the credential path identification module includes: The field extraction submodule calls the multi-node transaction write order queue to extract the three fields of access control level, resource path identification code, and valid time range from the access credential, writes the field values ​​into a unified structure index table and classifies and identifies them by transaction number to generate a credential field index set; The level comparison submodule reads the data sensitivity level label in the on-chain data structure based on the credential field index set and the access control level corresponding to each transaction credential, compares the two field values ​​sequentially, determines whether the access control level is less than the data sensitivity level label, marks the comparison result status, and obtains the credential level comparison result set; The path tag generation submodule assigns a read-only chain identifier to records whose access control level is lower than the data sensitivity level label according to the credential level comparison result set, and assigns a full-chain traceability identifier to the remaining records. The two types of chain access labels are classified and combined to generate a credential-driven chain path tag set.

[0011] The present invention is improved in that the structure callback node module includes: The chain path extraction submodule calls the credential-driven chain path label set, reads the node public key address list in the associated path according to the path record marked as full chain traceability, and archives it in the order of the path to generate a node link address set; The permission verification submodule obtains the access control level parameter in the access credential based on the node link address set and the node value of each path, compares it with the multi-signature access threshold value set by the link, calculates the path permission offset, and determines whether the offset exceeds the access offset tolerance range. If so, it marks the verification failure status and obtains the permission matching offset sequence; The path state construction submodule calls the permission matching offset sequence, adds a path redirection tag after the path identifier according to the path record marked as verification failure, updates the path state index table, constructs the path state set in path order, and generates an access chain redirection structure group.

[0012] The present invention is improved in that the system further comprises: The chain result output module calls the access chain redirection structure group, extracts the chain segment starting block height, relay node confirmation status code, and terminal data field change value from the record marked as the valid path structure, performs a structural sequence check on the three fields, and writes them into the chain structure index queue to generate an on-chain transaction traceability path structure; The on-chain transaction traceability path structure specifically refers to the chain data traceability path, the structure consistency mapping sequence and the output data change mapping diagram.

[0013] The present invention is improved in that the chain result output module includes: The field extraction submodule calls the access chain redirection structure group, extracts the three fields of the chain segment starting block height, relay node confirmation status code, and terminal data field change value based on the record marked as a valid path structure, reconstructs the three fields into structural units in the path order, and generates a chain structure field set; The sequence check submodule sequentially numbers the block height, relay status, and data change value in each structural unit according to the chain structure field set, determines whether the block height is the path starting index, whether the relay status is continuously increasing, and whether the data change value is less than the preset change tolerance value, and selects the structural units that meet the sequence requirements to obtain a chain structure valid unit set; The path structure generation submodule calls the chain structure valid unit set, writes each unit into the chain structure index queue according to the path number, builds an on-chain path mapping relationship table, and generates an on-chain transaction tracing path structure.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, the stability score is calculated by calculating the difference in field call sequence, call interval time difference and call return content consistency in the node access behavior log, and the nodes with stable access behavior are screened to form a block access permission mapping. The sorting label is constructed based on the transaction timestamp and the transaction amount to realize the sorting of concurrent transaction priorities, solve the disorder of concurrent write order, and jointly analyze the control level, path identifier and validity period in the access credential, and determine the read and write permission level of on-chain data access in a targeted manner, realizing the refined control of the granularity of transaction access rights. The public key address list and the multi-signature access threshold are dynamically matched and judged to form a link access path redirection to reduce the possibility of node tampering with data. The sequence verification and index tracing are performed according to the chain segment block height, the relay node confirmation status and the terminal data field change value, which significantly improves the traceability capability of financial transaction data, ensures the consistency and accuracy of the data structure, reduces the risk of misjudgment and resource consumption during financial business supervision audit and risk investigation, and improves the overall financial data processing efficiency and security. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a system flow chart of the present invention; Figure 2 This is a flow chart of the access chain authorization module of the present invention; Figure 3 A flowchart of the arbitration scheduling module is written into the present invention; Figure 4 This is a flow chart of the credential path identification module of the present invention; Figure 5 This is a flowchart of the structure callback node module of the present invention; Figure 6 This is a flow chart of the chain result output module of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the devices or elements referred to must have a specific direction, be constructed and operate in a specific direction, and therefore should not be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0018] See also Figure 1 The present invention provides a technical solution: a financial data processing system based on blockchain, the system comprising: The access chain authorization module obtains the node's access behavior log records within three cycles, including transaction details, account balance changes, and credit risk scores. Based on the difference in field call order, the difference in call interval time, and the consistency ratio of call return content, it calculates the access stability score, compares the access stability score with the preset access stability benchmark value, filters out nodes with scores greater than the benchmark value, and generates a block access permission mapping group. The write arbitration scheduling module calls the block access permission mapping group and constructs a sorting label based on the transaction timestamp, network delay, block packaging time, and transaction amount of each transaction data. It calculates the priority score based on the transaction timestamp and transaction amount, and constructs a write queue by comparing the priority scores in order. It then sorts concurrent transaction write requests and generates a multi-node transaction write order queue. The transaction timestamp indicates the specific time when the transaction was created or submitted, in UTC format. Network latency refers to the network transmission time required from sending to receiving between nodes, which can be measured by round-trip delay. Block packaging time refers to the average processing time for validating nodes to package transactions into blocks. The transaction amount is the actual value of the funds changed in the transaction, which is used to measure the impact of the transaction. The credential path identification module calls the multi-node transaction write order queue and extracts the access control level, resource path identification code, and valid time range from the access credential based on each transaction record. After reading the three fields together, they are compared with the data sensitivity level label of the on-chain data structure in turn to determine whether the access control level is less than the data sensitivity level label. If so, it is set as a read-only chain identifier; if so, it is set as a full-chain traceability identifier. The chain access labels generated by the comparison are combined to generate a credential-driven chain path label set; The access control level indicates the type of data or scope that the credential allows access to, usually in a multi-level classification, such as public, restricted, confidential, etc. The resource path identifier is the resource address code or smart contract call path; the valid time range indicates the valid usage period of the credential, defined in start and end time format; the data sensitivity level label is based on the definition level of the data type in compliance, privacy and risk, and is generally divided into non-sensitive, internally sensitive, and confidential levels; The structure callback node module calls the credential-driven chain path label set, reads the node public key address list in the path according to the path record marked with the full-chain traceability identifier, compares it with the access control level in the access credential, and determines whether the multi-signature access threshold set in the link is met. If not, a path redirection tag is added, a path status list is constructed, and an access chain redirection structure group is generated; The node public key address list is the address of the participating verification nodes stored and registered in the blockchain network; the multi-signature access threshold is the minimum number of signatures required for joint verification to access data under the multi-signature mechanism, and is commonly set at a ratio of 2 / 3 or 3 / 5; The chain result output module calls the access chain redirection structure group, extracts the chain segment starting block height, relay node confirmation status code, and terminal data field change value from the record marked as a valid path structure, performs a structural sequence check on the three fields, and writes them into the chain structure index queue to generate an on-chain transaction traceability path structure; The chain segment starting block height is the chain height of the first block in the path verification, which is used to confirm the starting point of data tracing. The relay node confirmation status code is the status set returned by the relay node verification transaction, usually 0 (unconfirmed), 1 (confirming), or 2 (confirmed). The terminal data field change value refers to the change range of key fields such as amount and account value in the last block, which is used to backtrack and determine whether data has been rewritten. The block access permission mapping group includes node behavior continuity score records, node periodic access stability labels and permission allocation level tables. The multi-node transaction write order queue includes a sorting priority label set, a cross-node time scheduling index and a transaction conflict mediation identifier. The credential-driven chain path label set specifically includes a chain access control tag, a path selection level identifier and a credential matching path comparison table. The access chain redirection structure group includes a redirection path mapping table, a path verification failure index and a chain segment access fallback node set. The on-chain transaction traceability path structure specifically refers to the chain data traceability path, the structural consistency mapping sequence and the output data change mapping diagram.

[0019] See also Figure 2 , the access chain authorization module includes: The behavior log collection submodule obtains the node's access behavior logs within three consecutive cycles, calls the three data fields of transaction details, account balance changes, and credit risk scores, establishes an access record set in chronological order of access behavior, and archives the data according to the source node to generate an access behavior log summary table; By obtaining the access behavior logs of the nodes in three consecutive cycles, a log collection can be established for the access records of the blockchain nodes to the transaction fields in different time periods, and the three field data of transaction details, account balance change value, and credit risk score are collected. Among them, the transaction details are stored in the form of the original sequence number submitted by the field, the account balance change value is expressed as the difference in the amount of continuous account changes, and the credit risk score is collected as the standardized score of each node in the external rating system. For example, for the node , the transaction field order is 1, 2, 3, the corresponding code is 1, the account change is from +100 in the first cycle to +300 in the third cycle, and the credit risk score is 72 points. The sequence is indexed by the node timestamp, such as Etc., to form a periodic access data structure, then sort the logs in ascending order according to the timestamp field, and create node labels based on the node number associated with each record to achieve identifiable archiving of data sources, and finally generate a summary table of access behavior logs; The stability score calculation submodule extracts the data call sequence, call time interval, and result return content associated with each node based on the access behavior log summary table, and calculates the field order difference value, interval difference value, and result consistency ratio respectively, using the formula: ; Obtain access stability score list through operation, establish score distribution set based on the concentration of score values, and obtain node stability score set; in, Indicates the access stability score, which reflects the quantitative score of the stability of node behavior. Indicates the actual call sequence encoding value of the field in the behavior log. Indicates the field standard call sequence code value set by the system. Indicates the The timestamp of the visit behavior, Indicates the The timestamp of the visit behavior, Indicates the maximum time interval among all access behaviors and is used to normalize the time interval. Indicates the number of times the returned result changes during the access behavior. Indicates the total number of results returned in the access behavior. Indicates the number of access behaviors within a cycle, used as the upper limit index in the cumulative item; Based on the access behavior log summary table, the field sequence number, continuous access timestamp and return field value of each node in the cycle are extracted, and the sequence number difference, time interval normalized sum of squares and result consistency ratio are calculated respectively. The sequence difference is calculated by Calculate the difference term, if the node The actual calling field order is , the standard order is , then the difference is 1, and the time interval normalization part uses the maximum time interval Standardization, such as nodes Timestamp is , then , the normalized expression is , the consistency of change is based on the number of result changes and return the total Calculate the ratio of , set the node The return value changes times , total number of times , then the consistent proportion is , the final access stability score formula is: ; Substitute node parameter: , , , , ; The time items are: ; The access stability score is: ; To show the stability score results of all nodes, the following data table is generated: Table 1 Node access stability score table

[0020] As shown in Table 1, lower scores represent more continuous and stable access behaviors.

[0021] Setting a baseline value , which is derived from all the nodes in the sample set. The 25% percentile interval below the mean of the value is dynamically adjusted as the number of samples changes to avoid concentrated deviation and ensure that the standard can distinguish stable access nodes from highly variable nodes. The calculation reference is set as follows: if the mean score of the sample set is 0.7 and the standard deviation is 0.12, then , in order to enhance the screening conservatism, it can be raised to 0.75 to ensure applicability; The node permission screening submodule calls the node stability score set, compares each node score with the set access stability benchmark value, selects nodes with scores higher than the benchmark value, marks the access permission level, and constructs a node permission mapping sequence to generate a block access permission mapping group; Call the node stability score collection and set the node 、 、 The corresponding scores are in turn related to the set access stability benchmark value Compare and judge the result is , , , the nodes with a screening score less than the benchmark value are qualified, and the nodes are marked The node number, permission level and score are written into the permission mapping sequence, and other nodes are labeled "frozen". At the same time, access denial is marked in the mapping table, and the block access permission mapping group is finally obtained. Under the filtering strategy of Meet access stability requirements and have link-in permissions.

[0022] See also Figure 3 , writing the arbitration scheduling module includes: The time tag extraction submodule calls the block access permission mapping group to obtain the corresponding transaction timestamp, network delay time, block packaging time, and fund transaction amount in the transaction data. It matches the fields with the node identifiers in the block access permission mapping group, and establishes a field comparison table between transaction records and nodes to obtain a transaction parameter matching set. Get the transaction timestamp, network delay time, block packaging time, and transaction amount corresponding to the transaction data, and record them as parameters respectively. 、 、 、 , match each parameter value with the node identifier in the block access permission mapping group, and generate a field comparison table by mapping each transaction number to its node number. For example, transaction number TX1 corresponds to node N1, and the field value is Second, Yuan, millisecond, In milliseconds, the parameter comparison table is established to complete the transaction structure construction and obtain the transaction parameter matching set; The priority score calculation submodule calls the transaction parameter matching set and normalizes the difference values ​​of the fields using the formula: ; Calculate and obtain the priority score value of the transaction and generate a transaction priority score set; in, Representative The priority score of the transaction, Representative The normalized value of the transaction timestamp of the transaction, Representative The normalized value of the transaction amount of the transaction. Representative The normalized value of the network delay time of the transaction, Representative Normalized value of the block packaging time of the transaction; Call transaction parameter matching set of each transaction record, 、 、 、 The four original data are normalized and converted using the maximum normalization method, where the maximum timestamp is , the maximum amount is Yuan, maximum delay Milliseconds, maximum packaging time Milliseconds; perform normalization operations on TX1 transaction records: ; ; ; ; Substitute it into the priority scoring formula: ; In this way, similar calculations are performed on TX2 and TX3 to obtain their corresponding scores; The formula's benefit lies in constructing an anti-interference factor by using latency and packaging time as the denominator. This can suppress priority distortion caused by high latency. It also prioritizes early large-value transactions by multiplying the timestamp and amount, helping to coordinate the pace of concurrent processing. The actual data results are as follows: Table 2 Transaction Priority Score Table

[0023] As shown in Table 2, the scoring results show that TX1 has the highest priority, followed by TX3, and finally TX2. This meets the strategic goal of prioritizing early high-value transactions. Based on the score range, the transaction numbers can be sorted in descending order to establish a priority index table. The sorting queue generation submodule sorts the transaction numbers in descending order based on the transaction priority score set and the score of each transaction. It also generates a sorting index corresponding to the node identifier and transaction ID, constructs a transaction record sorting table, and obtains a multi-node transaction write order queue. Based on the score value recorded in the transaction priority score set, call Value, sort the transaction numbers in descending order, build an index relationship table, record the writing order between transaction numbers and node identifiers, such as TX1 priority score is 0.8944, TX3 is 0.7809, TX2 is 0.5667, the order is TX1, TX3, TX2, suppose node N1 processes TX1, N2 processes TX2, N3 processes TX3, then the order mapping in the sorting index table is , , , and finally obtain the multi-node transaction write order queue. This result shows that under the normalized scoring calculation, transactions are assigned priority ranking values, which supports the system to build a controllable scheduling mechanism and complete node task allocation.

[0024] See also Figure 4 , the credential path identification module includes: The field extraction submodule calls the multi-node transaction write order queue to extract the three fields of the access credential: access control level, resource path identification code, and valid time range. It writes the field values ​​into a unified structure index table and classifies and identifies them by transaction number to generate a credential field index set. Call each transaction record in the multi-node transaction write order queue and extract the access credential content one by one. The extracted fields include access control level, resource path identification code, and valid time range. The access control level is represented by a numerical value, ranging from 0 to 3, representing public, restricted, internal, and confidential. For example, the transaction number TX1 corresponds to access control level 1, indicating restricted access; the resource path identification code is the data block path address to be accessed, such as " / ledger / block / 04523"; the valid time range is represented by a timestamp interval, such as [ , ] indicates that the voucher is valid between 13:00 and 14:00 Beijing time on October 1, 2021. If the transaction timestamp falls within this interval, it is considered valid. The above three fields are called and combined to write into a unified structure index table, and the records are identified and classified according to the transaction number, and finally the voucher field index set is obtained; The level comparison submodule is based on the credential field index set and the access control level corresponding to each transaction credential. It reads the data sensitivity level label in the on-chain data structure, compares the two field values ​​sequentially, determines whether the access control level is lower than the data sensitivity level label, and marks the comparison result status to obtain the credential level comparison result set; According to the access control level corresponding to each transaction in the credential field index set, the sensitivity level label corresponding to the requested data is read from the on-chain data structure database. The label is defined as four levels of permission requirements, namely 0 (public), 1 (restricted), 2 (internal), and 3 (confidential). The fields are sorted by integer values ​​and compared. For example, if the TX1 access control level is 1 and the corresponding path data sensitivity level is 2, then 1 < 2, and it is judged that the access level is insufficient; on the contrary, if the TX2 access control level is 2 and the data sensitivity level is 1, it is judged as authorization coverage. After the result comparison operation is performed, if the comparison is successful, the status is marked as "matched", and if it fails, it is marked as "unmatched". All transactions are compared to form a comparison status record list, and finally a credential level comparison result set is generated; if the TX1 comparison fails, TX2 comparison succeeds, and TX3 comparison fails, the record structure is as follows: Table 3 Credential level comparison record

[0025] As shown in Table 3, through field-level comparison, a structured comparison tag value is formed, which lays the foundation for the subsequent chain path tag generation; The path tag generation submodule assigns read-only chain tags to records with access control levels lower than the data sensitivity level tags based on the credential level comparison result set, and assigns full chain traceability tags to the remaining records. The two types of chain access tags are classified and combined to generate a credential-driven chain path tag set; According to the comparison status recorded in the credential level comparison result set, the transaction numbers are labeled one by one. If the control level of the transaction credential is lower than the sensitivity level of the target field, that is, the comparison status is "unmatched", it is marked as a read-only chain identifier, indicating that the transaction node can only read part of the summary information and does not have chain traceability permission; if the comparison status is "matched", it is marked as a full-chain traceability identifier, indicating that the call of the complete path chain segment data is allowed. Subsequently, the two types of identification labels are combined and written into the chain label structure mapping table. For example, TX1 and TX3 are assigned read-only chain identifiers, and TX2 is assigned a full-chain traceability identifier. Finally, a credential-driven chain path label set is generated. This structure supports the directional decision-making of the subsequent on-chain access path, realizing the complete connection between the access verification module and the link control logic.

[0026] See also Figure 5 , the structure callback node module includes: The chain path extraction submodule calls the credential-driven chain path label set, reads the node public key address list in the associated path according to the path record marked as full-chain traceability, and archives it in the order of the path to generate a node link address set; Call the path record marked as full chain traceability in the credential drive chain path label collection, parse and extract the node chain segment path associated with each record, read the public key address information of all nodes passed on the path, and the node address is represented in a compressed encoding format, such as 0x3a9c... After parsing, it is numbered and sorted in the access order and the archiving operation is completed. For example, the node address order involved in the path record PATH_01 is , then its path length is 3. This structure directly affects the minimum joint verification threshold required for access. After reading all path addresses, the node address list in each path is written into the structured path table with the transaction number as the index, forming a mapping relationship between the path and the node, and finally generating a node link address set; The permission verification submodule is based on the node link address set. According to the node value of each path, it obtains the access control level parameter in the access credential and compares it with the multi-signature access threshold value set by the link. The formula is: ; The path permission offset is obtained by calculation, and whether the offset exceeds the access offset tolerance range is determined. If so, the verification failure status is marked, and the permission matching offset sequence is obtained; in, Represents the path authority offset, Represents the access control level value in the credential, Represents the multi-signature access threshold corresponding to the link, Represents the public key address value of the node in the path, Representative Normalized value of the average access delay of nodes in the path, Representative The normalized value of the path jump frequency in the chain network, is the control factor after the growth compression adjustment of the path jump frequency, Used to express the nonlinear increase or decrease relationship between the number of nodes and the access threshold difference; Extract the path length parameter based on the node value contained in each path in the node link address set , and read the access control level value in the credential structure , set a multi-signature access threshold for the path Matching is performed, and the threshold value is based on the number of path nodes Multiply by the threshold scale factor Calculated, the proportional coefficient Set to 0.7. According to the system settings, in the multi-signature access scenario, more than 70% of the nodes are required to jointly sign before authorization can be processed to ensure security and decision constraints. The threshold value is rounded up, that is: , where the proportional coefficient is a fixed parameter of the system and does not fluctuate with the path change, but ultimately Follow Value fluctuations, when the path length becomes larger Synchronous increase; such as the number of nodes ,but Then, the average single response time of each node in the path is collected and the normalized value of the average access delay is calculated. , such as the node response time is 210, 180, 240, 150 milliseconds, the normalized reference value is the maximum response value of 240 milliseconds in the path, The path jump frequency is the frequency of switching of the path in the chain network scheduling table per hour, which is set to 5 times, and the maximum jump standard is 15 times. , substitute the formula to calculate the authority offset: ; The offset tolerance range value (access offset threshold) here is set to 0.1. This threshold is the boundary value of the system fault tolerance range. It refers to the maximum value of the 90% distribution segment of the average offset concentration of the multi-path link. It reflects the maximum acceptable difference between the path authorization and the actual credential level under the influence of time and jump frequency. If , it is considered to exceed the tolerance and recorded as a rejection state, and finally the permission matching offset sequence is obtained; The path state construction submodule calls the permission matching offset sequence, appends a path redirection tag after the path identifier based on the path record marked as verification failure, updates the path state index table, constructs the path state set in path order, and generates an access chain redirection structure group; The call permission matches the record status field in the offset sequence, processes the path record with the status of "rejected", reads the original path label structure, appends the path redirection tag at the end of the path identifier, such as marking "→ALT_PATH_03" after PATH_01, and writes the redirection target path into the path redirection table to establish a path mapping substitution relationship. The updated record structure is written into the path status index table, and an index pointer structure is generated according to the transaction number and the original path sequence. Finally, the access chain redirection structure group is obtained, which serves as the data input basis for the subsequent path selection and resource scheduling modules.

[0027] See also Figure 6 , the chain result output module includes: The field extraction submodule calls the access chain redirection structure group and extracts the three fields of the chain segment starting block height, relay node confirmation status code, and terminal data field change value based on the records marked as valid path structures. The three fields are reconstructed into structural units in the order of the path to generate a chain structure field set. Call all record paths in the access chain redirection structure group and filter out entries marked as "valid path structure". These paths are considered to be record paths that have passed verification and have traceability. Extract the three key fields of the chain segment: the chain segment starting block height, the relay node confirmation status code, and the end data field change value. The starting block height is an integer representing the starting position on the chain. For example, a block height of 64231 means that the starting point of the path is at block 64231. The relay node confirmation status code is an integer value of 0, 1, and 2, corresponding to the three states of unconfirmed, in progress, and confirmed, respectively. The field change value is expressed as the absolute value of the difference. For example, if a financial indicator item read in the end field changes from 623.11 to 634.57, the change value is 11.46. After extracting the above three fields, they are arranged into structural units in the order of the path and written into the structure set. They are archived and organized using the path number as the index to finally generate the chain structure field set. The sequence check submodule sequentially numbers the block height, relay status, and data change value in each structural unit according to the chain structure field set, determines whether the block height is the path starting index, whether the relay status is continuously increasing, and whether the data change value is less than the preset change tolerance value, and selects the structural units that meet the sequence requirements to obtain the chain structure valid unit set; According to the chain structure field set, the sequence check processing is performed on each structural unit in turn. First, it is determined whether the block height meets the starting index standard of the path sequence. The lower limit of the starting block height is set to 60000. If the path number is PATH_04, the starting block height of its first field is 64231, which meets the requirements; then it is checked whether the relay status is continuously increasing, that is, for the relay nodes passed through in the middle of the path, the confirmation status code should be from 0 to 2 in sequence or remain consistent and irreversible; then the change value of the end field is analyzed. If the field value change exceeds the set tolerance value, it is regarded as an abnormal record. The upper limit of the tolerance for field changes is set to 15.00. The change tolerance value comes from 8 of the concentrated interval of the monitoring field change range in the past 30 days in financial data tracing. The upper limit of the 0% distribution is based on typical volatility financial indicators (such as price changes and balance fluctuations). The weighted value is set after taking the average value of multiple measured paths. For example, if the change value of the PATH_04 terminal field is 11.46, which is lower than 15.00, then it is judged that the PATH_05 block height is 58200 and does not meet the starting block standard, the PATH_06 relay status is discontinuous, and the PATH_07 field change value is 19.63, which exceeds the limit. After screening, only PATH_04 meets all the sequence standards, and finally a valid unit set of the chain structure is selected and formed. The purpose of this valid unit set is to provide node-level input basis for the subsequent construction of a complete and traceable path, avoiding path diagram distortion caused by data structure misalignment or field jumps. The path structure generation submodule calls the chain structure valid unit set, writes each unit into the chain structure index queue according to the path number, builds the on-chain path mapping relationship table, and generates the on-chain transaction traceability path structure; Call the structural units in the chain structure valid unit set, perform structural sequence numbering according to the path number to which they belong, and write the path number, starting block height, relay status and field change value and other data in each structural unit into the chain structure index queue in a unified structural format to complete the mapping index link between the structural nodes. Then, perform the path node aggregation operation in the structure index queue to connect the unified chain segment structure into a complete path mapping structure, and finally generate a graphical data record result, which is output as a structural path graph information package as the system data traceable display output format, and complete the on-chain transaction traceability path structure. The path mapping entries of this structure can be used for subsequent display and data comparison calls.

[0028] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A financial data processing system based on blockchain, characterized in that: The system comprises: The access chain authorization module obtains the access behavior log records of the nodes within three cycles, calculates the access stability score based on the difference in field call order, the difference in call interval time, and the consistency ratio of call return content, filters out nodes with scores greater than the benchmark value, and generates a block access permission mapping group; The write arbitration scheduling module calls the block access permission mapping group, calculates the priority score according to the transaction timestamp and the transaction amount, compares the priority scores in order to build a write queue, and generates a multi-node transaction write order queue; The credential path identification module calls the multi-node transaction write order queue to determine whether the access control level is less than the data sensitivity level label. If so, it is set as a read-only chain identifier; if so, it is set as a full-chain traceability identifier, and generates a credential-driven chain path label set; The structure callback node module calls the credential-driven chain path label set, compares it with the access control level in the access credential, and determines whether it meets the multi-signature access threshold set in the link. If not, it appends a path redirection tag, builds a path status list, and generates an access chain redirection structure group.

2. The blockchain-based financial data processing system according to claim 1, characterized in that: The block access permission mapping group includes a node behavior continuity score record, a node periodic access stability label and a permission allocation level table; the multi-node transaction write order queue includes a sorting priority label set, a cross-node time scheduling index and a transaction conflict mediation identifier; the credential-driven chain path label set specifically includes a chain access control tag, a path selection level identifier and a credential matching path comparison table; the access chain redirection structure group includes a redirection path mapping table, a path verification failure index and a chain segment access fallback node set.

3. The blockchain-based financial data processing system according to claim 2, characterized in that: The access chain authorization module includes: The behavior log collection submodule obtains the node's access behavior logs within three consecutive cycles, calls the three data fields of transaction details, account balance changes, and credit risk scores, establishes an access record set in chronological order of access behavior, and archives the data according to the source node to generate an access behavior log summary table; The stability score calculation submodule extracts the data call sequence, call time interval, and result return content associated with each node based on the access behavior log summary table, calculates the field order difference value, interval difference value, and result consistency ratio, calculates the access stability score value list, establishes a score distribution set based on the concentration of the score values, and obtains the node stability score set; The node permission screening submodule calls the node stability score set, compares each node score value with the set access stability benchmark value, selects nodes with scores higher than the benchmark value, marks the access permission level and constructs a node permission mapping sequence to generate a block access permission mapping group.

4. The blockchain-based financial data processing system according to claim 3, characterized in that: The write arbitration scheduling module includes: The time tag extraction submodule calls the block access permission mapping group to obtain the corresponding transaction timestamp, network delay time, block packaging time, and fund transaction amount in the transaction data, matches the fields with the node identifiers in the block access permission mapping group, and establishes a field comparison table between transaction records and nodes to obtain a transaction parameter matching set; The priority score calculation submodule calls the transaction parameter matching set, normalizes and converts the difference values ​​of the fields, calculates and obtains the priority score value of the transaction, and generates a transaction priority score set; The sorting queue generation submodule arranges the transaction numbers in descending order based on the transaction priority score set and the score value of each transaction, generates a sorting index corresponding to the node identifier and the transaction ID, constructs a transaction record sorting table, and obtains a multi-node transaction write order queue.

5. The blockchain-based financial data processing system according to claim 4, characterized in that: The credential path identification module includes: The field extraction submodule calls the multi-node transaction write order queue to extract the three fields of access control level, resource path identification code, and valid time range from the access credential, writes the field values ​​into a unified structure index table and classifies and identifies them by transaction number to generate a credential field index set; The level comparison submodule reads the data sensitivity level label in the on-chain data structure based on the credential field index set and the access control level corresponding to each transaction credential, compares the two field values ​​sequentially, determines whether the access control level is less than the data sensitivity level label, marks the comparison result status, and obtains the credential level comparison result set; The path tag generation submodule assigns a read-only chain identifier to records whose access control level is lower than the data sensitivity level label according to the credential level comparison result set, and assigns a full-chain traceability identifier to the remaining records. The two types of chain access labels are classified and combined to generate a credential-driven chain path tag set.

6. The blockchain-based financial data processing system according to claim 5, characterized in that: The structure callback node module includes: The chain path extraction submodule calls the credential-driven chain path label set, reads the node public key address list in the associated path according to the path record marked as full chain traceability, and archives it in the order of the path to generate a node link address set; The permission verification submodule obtains the access control level parameter in the access credential based on the node link address set and the node value of each path, compares it with the multi-signature access threshold value set by the link, calculates the path permission offset, and determines whether the offset exceeds the access offset tolerance range. If so, it marks the verification failure status and obtains the permission matching offset sequence; The path state construction submodule calls the permission matching offset sequence, adds a path redirection tag after the path identifier according to the path record marked as verification failure, updates the path state index table, constructs the path state set in path order, and generates an access chain redirection structure group.

7. The blockchain-based financial data processing system according to claim 6, characterized in that: The system further comprises: The chain result output module calls the access chain redirection structure group, extracts the chain segment starting block height, relay node confirmation status code, and terminal data field change value from the record marked as the valid path structure, performs a structural sequence check on the three fields, and writes them into the chain structure index queue to generate an on-chain transaction traceability path structure; The on-chain transaction traceability path structure specifically refers to the chain data traceability path, the structure consistency mapping sequence and the output data change mapping diagram.

8. The blockchain-based financial data processing system according to claim 7, characterized in that: The chain result output module includes: The field extraction submodule calls the access chain redirection structure group, extracts the three fields of the chain segment starting block height, relay node confirmation status code, and terminal data field change value based on the record marked as a valid path structure, reconstructs the three fields into structural units in the path order, and generates a chain structure field set; The sequence check submodule sequentially numbers the block height, relay status, and data change value in each structural unit according to the chain structure field set, determines whether the block height is the path starting index, whether the relay status is continuously increasing, and whether the data change value is less than the preset change tolerance value, and selects the structural units that meet the sequence requirements to obtain a chain structure valid unit set; The path structure generation submodule calls the chain structure valid unit set, writes each unit into the chain structure index queue according to the path number, builds an on-chain path mapping relationship table, and generates an on-chain transaction tracing path structure.

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