Audit data full-link encryption traceability cooperative tracking method and system

Abstract

The application discloses an audit data full-link encryption traceability cooperative tracking method and system, relates to the technical field of auditing, and collects audit full-process multi-source heterogeneous data and builds an audit process knowledge graph to extract a benchmark knowledge correlation path; a bidirectional index field of a graph atlas identifier and a block chain storage address is built, a distributed block chain network node cluster is deployed, audit business disturbance information is used to correct node real resource load, and an encryption traceability cooperative scheduling strategy is generated; audit original data is processed according to the cooperative scheduling strategy, and the processed original data is stored on a chain and solidified; when a traceability query instruction is received, real circulation records stored in the block chain are called, the benchmark knowledge correlation path is corrected with actual data on the chain, real and complete full-link data is generated, and full-process traceability verification is completed without decryption.

Description

Technical Field

[0001] This invention relates to the field of auditing technology, and more specifically to a method and system for end-to-end encrypted traceability and collaborative tracking of audit data. Background Technology

[0002] With the digital upgrade of smart auditing, auditing operations cover the entire lifecycle of data collection, transmission, processing, and archiving, involving massive amounts of sensitive data from multiple sources and heterogeneous structures, with complex flow chains and numerous participating entities. Among these, the traceability and security of audit data transmission and storage have become core compliance requirements and are crucial for mitigating audit risks and fulfilling regulatory responsibilities. Current auditing technologies mostly achieve basic traceability through log recording, timestamps, and data lineage graphs, with some incorporating blockchain to solidify operation records. While these can meet basic traceability compliance needs, they have significant technical shortcomings, failing to simultaneously address the dual requirements of accurate traceability throughout the entire process and data encryption protection. Existing traceability systems commonly suffer from link breakpoints, failing to cover all data flow nodes, resulting in low traceability accuracy and difficulty in accurately defining responsibility. Furthermore, traceability and encryption mechanisms are disconnected, with static encryption only applied to archived data, leaving data in plaintext during transmission and processing, posing extremely high security risks. Moreover, encryption and traceability are technically conflicting; encryption hinders traceability capture, and traceability verification requires decryption, further exacerbating the risk of data leakage. In summary, existing technologies are insufficient to achieve coordinated and unified data traceability and end-to-end security encryption throughout the audit process, and thus cannot meet the application requirements of modern security auditing. Summary of the Invention

[0003] In view of this, the present invention provides a method and system for end-to-end encrypted traceability and collaborative tracking of audit data to solve the problems existing in the background art.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A collaborative tracing method for end-to-end encrypted source tracking of audit data includes the following steps: Collect multi-source heterogeneous data from the entire audit process and build an audit process knowledge graph to extract benchmark knowledge association paths; Establish a bidirectional index field between the graph identifier and the blockchain storage address, deploy a distributed blockchain network node cluster, use audit business disturbance information to correct the actual resource load of the nodes, and generate an encrypted traceability collaborative scheduling strategy; The audit raw data is processed according to the collaborative scheduling strategy, and the processed raw data is then stored on the blockchain. When a traceability query command is received, the actual flow records stored in the blockchain are retrieved. The reference knowledge association path is corrected with the actual data on the chain to generate a real and complete full-link. The entire process traceability verification is completed without decryption.

[0005] A collaborative tracing system for end-to-end encrypted audit data includes: The knowledge graph construction module is used to collect multi-source heterogeneous data from the entire audit process and build an audit process knowledge graph to extract benchmark knowledge association paths. The node strategy operation module is used to build a bidirectional index field between the graph identifier and the blockchain storage address, deploy a distributed blockchain network node cluster, use audit business disturbance information to correct the actual resource load of the nodes, generate an encrypted traceability collaborative scheduling strategy, process the audit raw data according to the collaborative scheduling strategy, and store the processed raw data on the blockchain. The encrypted traceability module is used to retrieve the real flow records stored in the blockchain when receiving traceability query instructions. It corrects the reference knowledge association path with the actual data on the chain, generates a real and complete full-link, and completes the full-process traceability verification without decryption.

[0006] As can be seen from the above technical solution, compared with the prior art, the present invention provides a method for end-to-end encrypted traceability and collaborative tracking of audit data. It utilizes a bidirectional indexing of graph identifiers and blockchain storage addresses, combined with a distributed blockchain node cluster network. By incorporating audit business disturbance information to optimize node load and form an encrypted traceability collaborative scheduling strategy, it can achieve standardized encrypted processing of original audit data and immutable on-chain solidified evidence storage, avoiding the risks of loss and tampering associated with traditional decentralized audit data storage. Furthermore, upon receiving a traceability query request, it can dynamically correct the baseline knowledge association path based on real on-chain data to restore the complete business process. The system covers the entire audit chain and relies on encrypted query logic to complete the entire process of traceability and verification without decryption. While ensuring the confidentiality of the original sensitive audit data throughout the process, it connects the entire chain of control for multi-source heterogeneous audit data from collection, processing, storage to traceability and verification. This significantly improves the authenticity, efficiency and security of audit data traceability and tracking. At the same time, it optimizes the operating efficiency of the blockchain network by dynamically adjusting the node load, reducing redundant resource consumption, and realizing the integration of audit encrypted storage and traceability collaborative control. This effectively solves industry pain points such as fragmented audit traceability data, cumbersome verification, weak data security control and distorted traceability links in traditional auditing. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0008] Figure 1 A flowchart provided for this invention

[0009] Figure 2This is a structural schematic diagram provided for the present invention. Detailed Implementation

[0010] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0011] This invention discloses a method for end-to-end encrypted tracing and collaborative tracking of audit data, such as... Figure 1 As shown, it includes: S1. Collect multi-source heterogeneous data from the entire audit process, extract candidate knowledge triples using a semantic model of the publicly known audit domain, map the triples to the corresponding audit task nodes, identify cross-process shared entities, and construct a baseline knowledge association path in the knowledge graph based on the audit business sequence and preset flow rules. This path is a standardized business flow template that only records the flow logic and constraint rules stipulated by the business. Assign a globally unique identifier to each entity node and associated edge in the graph and generate content feature hashes. Build a bidirectional index field between the graph identifier and the blockchain storage address. S2. Build a distributed blockchain node cluster, collect the computing power, storage, and bandwidth utilization of each node as basic resource indicators; collect node overload, network anomalies, illegal access, batch abnormal requests, and historical failure probabilities as business disturbance data, construct disturbance impact factors to correct the original resource indicators, and obtain the actual resource-constrained vector of the nodes; construct an adjacency matrix based on the blockchain topology, calculate the resource difference between nodes by combining the resource-constrained vector, and use information entropy to obtain the weights of various resources and then calculate the node collaborative redundancy; distinguish between two processing schemes, multi-node collaboration and single-node independence, according to the global collaborative redundancy threshold, and output the collaborative scheduling strategy for encrypted sharding and storage allocation; S3. Process the audit raw data according to the collaborative scheduling strategy: Divide the raw data into data fragments according to a fixed size, generate a key seed by combining the target storage node address and fragment sequence number, obtain the encryption key through hash operation, and encrypt the fragments through XOR operation to obtain encrypted fragments; bind the fragment sequence number, encrypted fragment, and encryption key to form a derived data segment; allocate storage nodes according to node adaptability, and each storage node returns the storage address and data hash, which are integrated to generate a fragment index list; put the fragment index list, graph identifier, feature hash, actual data flow node record, operation log, node resources and disturbance record on the chain for solidified storage. S4. Upon receiving a traceability query, first retrieve the baseline knowledge association path within the knowledge graph as the traceability framework, then retrieve the actual flow details stored in the blockchain through a bidirectional index, use the actual flow data on the chain to correct the baseline path, and generate the true full-link data; extract the specified byte string from the on-chain shard index and compare it byte by byte with the preset verification sample, without decrypting the original ciphertext throughout the process, to complete the traceability verification of data integrity, flow trajectory, and abnormal events; S5. During the tracing process, abnormal information such as node failures and illegal access is captured, and the statistical probability of business disturbances is updated in real time. The calculation results of subsequent node collaborative redundancy are iteratively corrected, and the data fragment size and tracing retrieval scope are adaptively adjusted to achieve dynamic linkage between encryption strategy and tracing logic.

[0012] Furthermore, in S2, the resource-constrained index is the ratio of node-used resources to total resources. The disturbance impact factor is used to eliminate the artificially high or low resource statistics caused by abnormal operating conditions, ensuring that the collaborative redundancy matches the actual available capacity of the node.

[0013] Furthermore, in S1, various audit business constraints are transmitted in reverse along the baseline knowledge association path. The conflict resolution of candidate knowledge triples is completed by relying on constraint verification, and semantically enhanced knowledge is generated to improve the knowledge graph. The graph only retains business template information, and all real-world data is supplemented by blockchain.

[0014] Furthermore, in S3, node adaptability is calculated by combining node bandwidth, historical availability, real-time load, average response time, and storage cost coefficient. The higher the adaptability value, the more likely derived data segments will be allocated for local storage.

[0015] Furthermore, when the S4 byte-level verification result is abnormal, the corresponding disturbance and access record are extracted from the chain synchronously to locate the node that caused the abnormality and the main body of the operation, and the result is synchronously fed back to S5 for disturbance parameter update.

[0016] This embodiment also discloses a collaborative tracing system for end-to-end encrypted audit data, such as... Figure 2 As shown, it includes: The knowledge graph construction module is used to collect multi-source heterogeneous data from the entire audit process and build an audit process knowledge graph to extract benchmark knowledge association paths. The node strategy operation module is used to build a bidirectional index field between the graph identifier and the blockchain storage address, deploy a distributed blockchain network node cluster, use audit business disturbance information to correct the actual resource load of the nodes, generate an encrypted traceability collaborative scheduling strategy, process the audit raw data according to the collaborative scheduling strategy, and store the processed raw data on the blockchain. The encrypted traceability module is used to retrieve the real flow records stored in the blockchain when receiving traceability query instructions. It corrects the reference knowledge association path with the actual data on the chain, generates a real and complete full-link, and completes the full-process traceability verification without decryption.

[0017] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0018] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for end-to-end encrypted traceability and collaborative tracking of audit data, characterized in that, Includes the following steps: Collect multi-source heterogeneous data from the entire audit process and build an audit process knowledge graph to extract benchmark knowledge association paths; Establish a bidirectional index field between the graph identifier and the blockchain storage address, deploy a distributed blockchain network node cluster, use audit business disturbance information to correct the actual resource load of the nodes, and generate an encrypted traceability collaborative scheduling strategy; The audit raw data is processed according to the collaborative scheduling strategy, and the processed raw data is then stored on the blockchain. When a traceability query command is received, the actual flow records stored in the blockchain are retrieved. The reference knowledge association path is corrected with the actual data on the chain to generate a real and complete full-link. The entire process traceability verification is completed without decryption.

2. The method for end-to-end encrypted traceability and collaborative tracking of audit data according to claim 1, characterized in that, To build an audit process knowledge graph and extract benchmark knowledge association paths, specifically: extract candidate knowledge triples, map the triples to the corresponding audit task nodes, identify cross-process shared entities, and construct benchmark knowledge association paths in the knowledge graph based on the audit business sequence and preset flow rules. The benchmark knowledge association paths are standardized business flow templates used to record the flow logic and constraint rules stipulated by the business.

3. The method for end-to-end encrypted traceability and collaborative tracking of audit data according to claim 1, characterized in that, A bidirectional index field is constructed for graph identifiers and blockchain storage addresses. Specifically, a globally unique identifier is assigned to each entity node and associated edge of the graph, and a content feature hash is generated.

4. The method for end-to-end encrypted traceability and collaborative tracking of audit data according to claim 1, characterized in that, Using audit business disturbance information to correct the actual resource load of nodes and generate an encrypted traceability and collaborative scheduling strategy, the specific steps include: The computing power, storage, and bandwidth utilization of each node are collected as basic resource indicators. Node overload, network anomalies, illegal access, batch abnormal requests, and historical failure probabilities are collected as business disturbance data. Disturbance impact factors are constructed to correct the original resource indicators and obtain the actual resource-constrained vector of the node. Based on the blockchain topology, an adjacency matrix is ​​constructed. The resource difference between nodes is calculated by combining the resource-constrained vector. The weights of various resources are obtained by using information entropy and then the node collaborative redundancy is calculated by weighting. Based on the global collaborative redundancy threshold, two processing schemes are distinguished: multi-node collaborative and single-node independent. The collaborative scheduling strategy for encrypted sharding and storage allocation is then output.

5. The method for end-to-end encrypted traceability and collaborative tracking of audit data according to claim 1, characterized in that, The audit raw data is processed according to the collaborative scheduling strategy, and the processed raw data is stored on the blockchain. Specifically, the raw data is divided into data fragments according to a fixed size. A key seed is generated by combining the target storage node address and fragment number. An encryption key is obtained through hash operation. The fragments are encrypted by XOR operation to obtain encrypted fragments. The bound fragment sequence number, encrypted fragment, and encryption key form a derived data segment; Storage nodes are allocated based on node suitability, and each storage node returns its storage address and data hash, which are then integrated to generate a sharded index list. The shard index list, graph identifier, feature hash, actual data flow node records, operation logs, node resources and disturbance records are all stored on the blockchain.

6. The method for end-to-end encrypted traceability and collaborative tracking of audit data according to claim 1, characterized in that, It also includes node failures, illegal access and other abnormal information captured during the tracing process, real-time updates of business disturbance statistical probabilities, iterative correction of subsequent node collaborative redundancy calculation results, adaptive adjustment of data fragment size and tracing retrieval scope, and dynamic linkage between encryption strategy and tracing logic.

7. A collaborative tracing system for end-to-end encrypted audit data, characterized in that, include: The knowledge graph construction module is used to collect multi-source heterogeneous data from the entire audit process and build an audit process knowledge graph to extract benchmark knowledge association paths. The node strategy operation module is used to build a bidirectional index field between the graph identifier and the blockchain storage address, deploy a distributed blockchain network node cluster, use audit business disturbance information to correct the actual resource load of the node, and generate an encrypted traceability collaborative scheduling strategy. The audit raw data is processed according to the collaborative scheduling strategy, and the processed raw data is then stored on the blockchain. The encrypted traceability module is used to retrieve the real flow records stored in the blockchain when receiving traceability query instructions. It corrects the reference knowledge association path with the actual data on the chain, generates a real and complete full-link, and completes the full-process traceability verification without decryption.

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