Blockchain and privacy computing-based audit data processing method, device and product

Abstract

The application is suitable for the technical field of data processing, and particularly relates to an audit data processing method, device and product based on a blockchain and privacy calculation, which comprises the following steps: the application separates and processes audit data and data labeling information in an associated identification manner and superimposes and integrates them, simultaneously combines the blockchain to store and verify the audit authorization information and operation behavior, so that when the audit shared data changes, the data labeling information can be adaptively identified based on the associated identification and regional matching relationship; the blockchain is used to realize permission control and operation traceability, and finally the audit result data is obtained. Through the above method, the problems that the permission control lacks credible support in multi-party collaborative audit, the adaptability of the dynamic update of the labeled data and the audit data is poor, the credible storage and traceability of the audit operation process are difficult to realize, and the actual needs of digitalization and cross-institution collaborative audit cannot be met can be solved.

Description

Technical Field

[0001] This application belongs to the field of data processing technology, and in particular relates to audit data processing methods, devices and products based on blockchain and privacy computing. Background Technology

[0002] The audit data processing method based on blockchain and privacy computing is used to achieve secure sharing, multi-party collaborative annotation, authorization control and trusted traceability of audit data, while taking into account both audit data privacy protection and collaborative processing efficiency.

[0003] Currently, traditional audit data processing methods have significant shortcomings in terms of privacy and security protection. The access control of multi-party collaborative audits lacks credible support, and the adaptability of labeled data and audit data dynamic updates is poor. It is difficult to achieve credible evidence storage and traceability of the audit operation process, and it cannot meet the actual needs of digital and cross-institutional collaborative audits. Summary of the Invention

[0004] This application provides an audit data processing method, device, and product based on blockchain and privacy computing. It can solve the problems of lack of credible support for access control in multi-party collaborative auditing, poor adaptability of dynamic updates of labeled data and audit data, difficulty in achieving credible evidence storage and traceability of audit operation process, and inability to meet the actual needs of digital and cross-institutional collaborative auditing.

[0005] In a first aspect, embodiments of this application provide an audit data processing method based on blockchain and privacy computing, including: Receive audit data sent by the audit initiator; wherein, the audit data is used for collaborative annotation of audit-related content by multiple auditing entities; The audit data is encrypted using a homomorphic encryption algorithm to obtain audit shared data, which is then sent to multiple audit collaborators. The homomorphic encryption algorithm is used to protect privacy and security during the transmission of audit shared data to prevent data leakage. The system receives audit authorization information for multiple audit assisting parties sent by the audit initiator; wherein the audit authorization information is used to control the annotation operations of each audit assisting party. The audit authorization information is hashed to generate an audit authorization information hash value; Based on the hash value of the audit authorization information, data annotation information sent by multiple audit assistance parties is received; wherein, the data annotation information indicates that the encrypted audit shared data is annotated to obtain an audit data stream with annotated data; Based on multiple data annotation information, audit result data is obtained; wherein, the audit result data represents the result of overlaying the audit shared data with the data annotation information to obtain a unified audit data stream.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The audit data processing method based on blockchain and privacy computing provided in this application embodiment receives audit data sent by the audit initiator; wherein the audit data is used for collaborative annotation of audit-related content by multiple audit units; the audit data is encrypted using a homomorphic encryption algorithm to obtain audit shared data, and then the audit shared data is sent to multiple audit assisting parties; wherein the homomorphic encryption algorithm is used to protect the privacy and security of the audit shared data transmission process to prevent audit data leakage; the method receives audit authorization information sent by the audit initiator to multiple audit assisting parties; wherein the audit authorization information is used to control the annotation operations of each audit assisting party; the audit authorization information is hashed to generate an audit authorization information hash value; based on the audit authorization information hash value, the method receives data annotation information sent by multiple audit assisting parties; wherein the data annotation information indicates annotation of the encrypted audit shared data to obtain an audit data stream with annotated data; based on multiple data annotation information, audit result data is obtained; wherein the audit result data indicates that the audit shared data and data annotation information are overlaid to obtain a unified audit data stream. This application separates and integrates audit data and data annotation information using a correlated identifier method. Simultaneously, it combines blockchain technology to record and verify audit authorization information and operational actions on the blockchain, enabling adaptive identification of data annotation information based on correlation identifiers and regional matching relationships when the content of shared audit data changes. Furthermore, blockchain is used to achieve access control and operational traceability, ultimately yielding the audit result data. This method addresses the problems of insufficient trusted support for access control in multi-party collaborative audits, poor adaptability of dynamically updated annotation and audit data, difficulty in achieving trusted evidence storage and traceability of the audit operation process, and inability to meet the practical needs of digital, cross-institutional collaborative audits.

[0007] Secondly, embodiments of this application provide an audit data processing apparatus based on blockchain and privacy computing, applied to an electronic device, for implementing the audit data processing method based on blockchain and privacy computing as described in any one of the first aspects above. The audit data processing apparatus based on blockchain and privacy computing includes: The initiating unit is used to receive audit data sent by the audit initiator; wherein, the audit data is used for multiple audit units to collaboratively annotate audit-related content; An encryption unit is used to encrypt the audit data using a homomorphic encryption algorithm to obtain audit shared data, and then send the audit shared data to multiple audit assistance parties; wherein, the homomorphic encryption algorithm is used to protect the privacy and security of the audit shared data transmission process to prevent audit data leakage; An authorization unit is used to receive audit authorization information sent by the audit initiator for multiple audit assisting parties; wherein the audit authorization information is used to control the annotation operations of each of the audit assisting parties; A hash unit is used to perform hash processing on the audit authorization information to generate an audit authorization information hash value; The annotation unit is used to receive data annotation information sent by multiple audit assistance parties based on the hash value of the audit authorization information; wherein the data annotation information indicates that the encrypted audit shared data is annotated to obtain an audit data stream with annotated data; The result unit is used to obtain audit result data based on multiple data annotation information; wherein the audit result data represents the unified audit data stream obtained by overlaying the audit shared data with the data annotation information.

[0008] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any of the foregoing aspects.

[0009] Fourthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to perform the method described in any one of the first aspects above.

[0010] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the interaction method between electronic devices, audit initiators, and audit assistants in an audit data processing method based on blockchain and privacy computing provided in an embodiment of this application; Figure 2This is a flowchart illustrating an embodiment of the audit data processing method based on blockchain and privacy computing provided in this application; Figure 3 This is a schematic diagram illustrating the operation of an audit data processing method based on blockchain and privacy computing provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of the audit data processing device based on blockchain and privacy computing provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0014] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0015] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0016] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0017] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0018] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0019] Among related technologies, traditional audit data processing methods have significant shortcomings in terms of privacy and security protection. The access control of multi-party collaborative audits lacks credible support, the adaptability of labeled data and audit data dynamic updates is poor, and it is difficult to achieve credible evidence storage and traceability of the audit operation process, thus failing to meet the actual needs of digital and cross-institutional collaborative audits.

[0020] To address the aforementioned issues, this application provides an audit data processing method based on blockchain and privacy computing. The method includes: receiving audit data sent by an audit initiator; wherein the audit data is used for collaborative annotation of audit-related content by multiple audit units; encrypting the audit data using a homomorphic encryption algorithm to obtain shared audit data, and then sending the shared audit data to multiple audit assisting parties; wherein the homomorphic encryption algorithm is used to protect privacy and security during the transmission of shared audit data to prevent audit data leakage; receiving audit authorization information sent by the audit initiator for multiple audit assisting parties; wherein the audit authorization information is used to control the annotation operations of each audit assisting party; hashing the audit authorization information to generate an audit authorization information hash value; receiving data annotation information sent by multiple audit assisting parties based on the audit authorization information hash value; wherein the data annotation information indicates annotation of the encrypted shared audit data to obtain an audit data stream with annotated data; obtaining audit result data based on multiple data annotation information; wherein the audit result data indicates that the shared audit data and the data annotation information are overlaid to obtain a unified audit data stream. This application separates and integrates audit data and data annotation information using a correlated identifier method. Simultaneously, it combines blockchain technology to record and verify audit authorization information and operational actions on the blockchain, enabling adaptive identification of data annotation information based on correlation identifiers and regional matching relationships when the content of shared audit data changes. Furthermore, blockchain is used to achieve access control and operational traceability, ultimately yielding the audit result data. This method addresses the problems of insufficient trusted support for access control in multi-party collaborative audits, poor adaptability of dynamically updated annotation and audit data, difficulty in achieving trusted evidence storage and traceability of the audit operation process, and inability to meet the practical needs of digital, cross-institutional collaborative audits.

[0021] The audit data processing method based on blockchain and privacy computing provided in this application embodiment can be applied to electronic devices. In this case, the electronic device is the executing entity of the audit data processing method based on blockchain and privacy computing provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of electronic device.

[0022] Please see Figure 1 , Figure 1This is a schematic diagram illustrating the interaction process between an electronic device, an audit initiator, and audit assistants in an audit data processing method based on blockchain and privacy computing, provided in one embodiment of this application. The application scenario of this interaction process includes an electronic device, an audit initiator, and audit assistants. The audit initiator sends audit data to the electronic device, which encrypts and generates shared audit data and sends it to multiple audit assistants. The audit assistants obtain audit authorization information from the audit initiator, and the electronic device receives the audit authorization information sent by the audit initiator. The electronic device hashes the audit authorization information on the blockchain to determine its hash value and receives data annotation information from the audit assistants based on this hash value. The electronic device obtains the audit result data through the data annotation information and sends it to the audit initiator.

[0023] In this embodiment, the electronic device may be a cloud server, cloud host, commercial desktop computer, laptop computer, e-commerce dedicated smart terminal, tablet computer, etc. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method as described in any of the foregoing aspects.

[0024] In this application embodiment, the audit initiator and the audit assistant can be physical devices such as smartphones, desktop computers, tablets, laptops, digital assistants, and smart wearable devices used by the auditing entity, and can also include software running on the physical devices, such as applications.

[0025] To better understand the audit data processing method based on blockchain and privacy computing provided in the embodiments of this application, the specific implementation process of the audit data processing method based on blockchain and privacy computing provided in the embodiments of this application will be described by way of example below.

[0026] Figure 2 A flowchart illustrating the audit data processing method based on blockchain and privacy computing provided in an embodiment of this application is shown. Figure 3 The illustration shows a schematic diagram of the operation of the audit data processing method based on blockchain and privacy computing provided in an embodiment of this application. The audit data processing method based on blockchain and privacy computing includes: S100 receives audit data sent by the audit initiator. This audit data is used for collaborative annotation of audit-related content by multiple auditing entities.

[0027] As we can understand, the audit initiator refers to the entity that submits the audit request and provides the original audit data, which can be the company's finance department, auditing firm, etc. Audit data is the core foundational data for audit work, encompassing various audit-related data such as company financial statements, accounting vouchers, transaction records, contract documents, and internal control process records. Audit data can be obtained through methods such as exporting from the audit initiator's internal database or uploading scanned offline documents. For example, if the audit initiator is the audit department of a manufacturing company, the audit data sent by the audit department may include the manufacturing company's monthly balance sheet, profit and loss statement, bank statements, raw material purchase contracts, and production workshop cost accounting records for 2024.

[0028] S200 employs a homomorphic encryption algorithm to encrypt audit data, obtaining shared audit data, which is then sent to multiple audit collaborators. The homomorphic encryption algorithm protects privacy and security during the transmission of shared audit data to prevent data leakage.

[0029] Homomorphic encryption is a special encryption technique and a common computational method in privacy computing. Its core characteristic is that when homomorphic encryption is applied to encrypted data, the decrypted result is identical to the result of applying the same operation directly to the original data. Simply put, "data can still be processed after encryption without affecting the correctness of the result." Audit shared data is encrypted audit data obtained after homomorphic encryption. It retains the structure and processability of the original audit data but cannot be deciphered or viewed by unauthorized entities. Audit assistance parties are entities commissioned by the audit initiator to participate in the annotation of audit data. They may include external auditors, industry compliance experts, third-party audit institutions, etc., and can access electronic devices through dedicated physical equipment within the audit unit. For example, the audit data sent by the audit initiator includes the company's core financial transactions (involving trade secrets). After encrypting the audit data of the company's core financial transactions using a homomorphic encryption algorithm, the audit shared data is obtained and sent to the audit units of three audit assisting parties. The audit assisting parties can only perform annotation operations on the encrypted audit data (such as annotating the location of suspicious transaction records), and cannot view the specific amount of the transactions, counterparties, or other original private information, thus achieving a balance between data sharing and privacy protection.

[0030] As an optional embodiment of this application, in step S200, the audit data is encrypted using a homomorphic encryption algorithm to obtain audit shared data, which is then sent to multiple audit assistance parties, including: S210 cleans and verifies the audit data sent by the audit initiator, removes invalid data, corrects data format deviations, and filters out valid audit data that meets the collaborative annotation requirements.

[0031] It is understandable that invalid data includes data lacking key information (such as voucher records without transaction dates or amounts), duplicate data (such as uploading the same contract multiple times), data with incorrect formats (such as entering "2024 / 01 / 01" instead of "2024-01-01" and not standardizing the date format), and data irrelevant to the audit (such as employees' private communication records). Valid audit data refers to data that, after cleaning and verification, is formatted correctly, has complete information, is relevant to audit requirements, and can be directly used for collaborative annotation. For example, the audit data sent by the audit initiator contains 1000 purchase voucher records, of which 50 are missing "supplier name" (invalid data), 30 are duplicate entries (invalid data), and 20 have incorrect date formats (format deviation). After data cleaning to remove these 100 invalid data records and correcting the 20 format-incorrect data records, 900 purchase voucher records with correct formats and complete information are ultimately selected as valid audit data that meets the requirements for collaborative annotation, for subsequent encryption processing.

[0032] S220: Select a homomorphic encryption algorithm suitable for the requirements of valid audit data and generate a corresponding encryption key pair. The key pair includes a public key and a private key. The public key is used to perform encryption operations. The private key is used for decryption and verification of the audit result data.

[0033] As we understand it, an encryption key pair is a pair of interconnected keys automatically generated by an electronic device using an encryption algorithm. The public key can be publicly distributed and used to encrypt valid audit data. Anyone can obtain the public key to perform encryption operations, but cannot decrypt the data using the public key. The private key is kept separately by the audit initiator and is only used to decrypt the final audit result data and verify the authenticity and integrity of the audit results. If the private key is leaked, it will lead to the leakage of audit data privacy; therefore, it must be stored securely (e.g., encrypted in a dedicated hardware key device). For example, if the valid audit data is monthly financial data of a company (such as revenue, cost, profit, etc.), and it needs to support numerical comparison and annotation by the audit assistance party after encryption, the Paillier homomorphic encryption algorithm can be selected. The electronic device automatically generates a key pair (public key PK, private key SK). The public key PK is used to encrypt the amount, quantity, and other numerical data in 900 purchase voucher records. The private key SK is properly kept by the audit initiator and used to decrypt the annotated audit result data later to view the original annotation information.

[0034] S230, based on a public key, performs full encryption on valid audit data, preserving the original relationships between the audit data during the encryption process, and generating shared audit data.

[0035] Full encryption means encrypting all fields and all content in the valid audit data, leaving no data or information point out of the loop, thus protecting the privacy of every detail of the original audit data. The original relationships in the audit data refer to the inherent connections between data fields and entries in the valid audit data, such as the relationship between "purchase voucher records" and "supplier information" (multiple purchase vouchers for the same supplier), the relationship between "financial statements" and "accounting vouchers" (report data is generated by summarizing corresponding vouchers), and the relationship between "transaction records" and "contract documents" (transaction records correspond to specific contract numbers). Shared audit data is the final shareable data obtained after full encryption. Shared audit data not only achieves privacy protection but also retains the original data's relationship logic, allowing audit collaborators to perform collaborative annotation based on these relationships even in an encrypted state (e.g., viewing annotation information for corresponding transaction records by contract number). For example, based on the public key PK, 900 purchase voucher records are fully encrypted. All fields in each voucher record, such as "voucher number, supplier name, purchase amount, purchase date, and corresponding contract number", are encrypted. At the same time, a unique associated ID is added to each voucher, and the association between "voucher number and contract number" is preserved. After encryption, 900 encrypted voucher records are generated and integrated to form audit shared data.

[0036] In one possible implementation, S230, based on the public key, performs full encryption on the valid audit data, preserving the original associations of the audit data during the encryption process, and generating shared audit data, including: S231, based on the public key, performs structured parsing on valid audit data, extracting each data field, field relationship, and data hierarchy structure from the valid audit data.

[0037] Structured analysis, as we understand it, refers to breaking down and analyzing valid audit data to identify its organizational structure and internal relationships, transforming unstructured or semi-structured audit data (such as scanned contracts and handwritten vouchers) into identifiable and processable structured data. A data field is the smallest unit of information in valid audit data; for example, in a purchase voucher, "voucher number, supplier name, purchase amount, and purchase date" are all independent data fields. Field relationships refer to the correspondence between different data fields, such as the relationship between "purchase amount" and "tax rate" (used to calculate tax), or the relationship between "supplier name" and "supplier number" (used to uniquely identify the supplier). Data hierarchy refers to the hierarchical division of audit data. For example, audit data may be divided into three levels: "basic audit information (such as audit object and audit period), financial data (such as vouchers and reports), and audit supporting data (such as contracts and bank statements)." The financial data level is further divided into sub-levels such as "purchase vouchers, sales vouchers, and expense vouchers." For example, by performing structured parsing on 900 valid purchase vouchers, eight data fields were extracted, including "voucher number, supplier name, supplier number, purchase amount, purchase date, contract number, purchase quantity, and tax rate". The relationships between "voucher number and contract number", "supplier name and supplier number", and "purchase amount, purchase quantity, and tax rate" were identified, and the data hierarchy was determined to be "audit basic information - financial data - purchase voucher data".

[0038] For example, in S231, the valid audit data is structured and parsed to extract each data field, field relationships, and data hierarchy from the valid audit data, including: S2311, Data storage format and encoding rules for obtaining valid audit data.

[0039] It's understandable that data storage format refers to the way valid audit data is stored on the audit initiator's electronic device. Commonly used formats include CSV, Excel, JSON, and database table formats, each corresponding to different data organization methods. Encoding rules refer to the character encoding, field naming rules, and data format specifications of valid audit data (e.g., date encoding is "YYYY-MM-DD", amount encoding is "values ​​with two decimal places", and field names use the format "English abbreviation + full Chinese name"). The purpose of encoding rules is to ensure data uniformity and identifiability. For example, valid audit data (900 purchase vouchers) sent by the audit initiator is stored in Excel format with the following encoding rules: character encoding is UTF-8, date format is "YYYY-MM-DD", amount format is "values ​​with two decimal places", and field naming rules are "English abbreviation_full Chinese name" (e.g., "CPBH_voucher number" "GYSXM_supplier name"). These storage formats and encoding rules can be obtained through electronic device integration.

[0040] S2312, based on data storage format and encoding rules, decomposes valid audit data to obtain audit basic information field, financial data field, and audit supporting evidence field.

[0041] Data decomposition, as we understand it, refers to breaking down valid audit data into three core field categories based on different information types, according to data storage formats and encoding rules. This facilitates subsequent classification, encryption, and integration. The audit basic information field describes the basic audit situation, including the audit object, audit period, audit batch, and auditors. The financial data field refers to the core financial-related fields, including voucher number, amount, quantity, tax rate, transaction date, and accounting subject. The audit supporting field verifies the authenticity and compliance of the financial data, including contract number, supplier number, bank transaction number, and invoice number. The audit basic information field, financial data field, and audit supporting field are obtained by using data decomposition tools to classify and decompose valid audit data according to storage formats and encoding rules, categorizing different types of fields to obtain three sets of fields. For example, based on the Excel storage format and corresponding coding rules, the valid data of 900 purchase vouchers were broken down. The audit basic information fields include "Audit Object_A Manufacturing Enterprise", "Audit Period_October 2024", and "Audit Batch_20241001". The financial data fields include "CPBH_Voucher Number", "CGJE_Purchase Amount", "CGSJ_Purchase Date", "CGSL_Purchase Quantity", and "SL_Tax Rate". The audit supporting fields include "HTBH_Contract Number", "GYSBH_Supplier Number", and "YPSH_Invoice Number", thus completing the data breakdown.

[0042] S2313, based on the subordinate and correlation verification relationships of the audit basic information field, financial data field, and audit supporting evidence field, obtain the field association list and data hierarchy structure.

[0043] It can be understood that the subordinate relationship refers to the hierarchical relationship between the three field categories. Specifically, the audit basic information field is the overall hierarchy, the financial data field is subordinate to the audit basic information field (multiple financial data points correspond to the same audit period), and the audit supporting field is subordinate to the financial data field (multiple supporting fields correspond to the same financial data). The correlation verification relationship refers to the mutual verification relationship between the three field categories, used to improve the accuracy and completeness of the data. For example, the "purchase amount" in the financial data field must be consistent with the "invoice amount" in the audit supporting field, and the "contract number" in the financial data field must have a corresponding record in the audit supporting field. The field correlation list is a list recording the subordinate and correlation verification relationships between the three field categories, clearly defining the corresponding related fields and verification rules for each field. The data hierarchy structure refers to the hierarchical division based on the subordinate relationship, namely a three-level hierarchy structure of "audit basic information field—financial data field—audit supporting field". For example, the subordinate relationship can be summarized as "audit basic information (audited in October 2024)—financial data (900 purchase vouchers during the period)—audit supporting field (contracts and invoices corresponding to each voucher)". The correlation verification relationships are "Purchase amount = Purchase quantity × Unit price (internal verification of financial field)", "Purchase amount = Invoice amount (verification of financial field and supporting field)", and "Contract number has a corresponding record in the supporting field (verification of financial field and supporting field)". Based on these relationships, a field correlation list is generated to improve the three-level data hierarchy structure.

[0044] By employing steps S2311 to S2313, the following can be achieved: Standardizing the breakdown and correlation of effective audit data, clarifying the data storage format, encoding rules, and hierarchical relationships, thus resolving issues of chaotic data formats and unclear relationships. Simultaneously, through classification, breakdown, and correlation verification, the accuracy and completeness of the data can be improved.

[0045] S232, based on the extracted field relationships and data hierarchy, add association identifiers to valid audit data.

[0046] As can be understood, an association identifier is a unique identifier used to mark the relationship between fields and data entries in valid audit data. It can be a unique string of characters or numbers (such as UUID, auto-incrementing ID). The purpose of the association identifier is to allow for quick location and association of related data even after encryption, enabling audit collaborators to collaboratively annotate based on the relationship. To avoid the association identifier revealing data structure and business relationships, and to ensure data association and location are still possible after encryption, this embodiment adopts a blind association identifier mechanism: the association identifier is a random string with no semantic or business meaning, and is globally unique. It does not contain any identifiable information such as voucher number, contract number, field type, or hierarchical relationship, and is only used to mark the ownership and binding relationship between encrypted data. Blind association identifiers can be transmitted securely without encryption because they do not leak privacy or expose the structure. The addition of association identifiers needs to be combined with field relationship and data hierarchy structure. All data fields and data entries under the same relationship should have the same or corresponding association identifier added, and identifiers for different relationships should not be duplicated. For example, based on the association between "voucher number and contract number", a primary association identifier "GuanLian-001" is assigned to the purchase voucher number "CP-2024001", and a secondary association identifier "GuanLian-001-1" is assigned to the contract number "HT-2024001" corresponding to the purchase voucher. Based on the association between "supplier name and supplier number", an association identifier "GuanLian-002" is assigned to the supplier name "XX Building Materials Company" and the supplier number "GS-001".

[0047] S233, according to the preset encryption order, perform full field-by-field encryption on the valid audit data with associated identifiers to obtain encrypted data.

[0048] It is understandable that a preset encryption order refers to the order in which valid audit data fields are encrypted by an electronic device in advance. This can be set according to the data hierarchy from high to low, or the field importance from high to low (e.g., encrypting financial data fields first, then basic audit information fields; encrypting core privacy fields such as amount and password first, then ordinary fields such as voucher number). The purpose of a preset encryption order is to ensure the orderliness and standardization of the encryption process, avoiding omissions or chaotic encryption. Encrypted data refers to the encrypted result obtained after encrypting a single field; multiple encrypted fields combine to form an encrypted set of a single data entry. For example, for a purchase voucher with the associated identifier "GuanLian-001", the "Purchase Amount" field is encrypted first (original amount 10,000 yuan, encrypted as "xxx-xxxx-xxx"), then the "Supplier Name" field is encrypted (original name "XX Building Materials Company", encrypted as "yyy-yyyy-yyy"), and so on, until all fields are encrypted, ultimately yielding the encrypted data of the purchase voucher, making the original information of each field unviewable.

[0049] S234 integrates encrypted data and forms complete audit shared data based on the association logic corresponding to the association identifier.

[0050] Encrypted data integration refers to summarizing and organizing the encrypted fields of all individual data entries according to certain rules to form a complete and shareable encrypted data set. The association logic corresponding to the association identifier refers to the data relationship reflected after adding the association identifier (such as the correspondence between the main association identifier and the sub-association identifier, and the subordinate relationship of different fields under the same association identifier). Audit shared data refers to the integrated data set that retains both the encrypted content of all valid audit data and the original data relationships, and can be directly sent to audit collaborators for collaborative annotation. The method for obtaining audit shared data is as follows: The encrypted fields of all individual data entries are categorized and summarized according to the data hierarchy; based on the association logic of the association identifiers, the associated data is bound and integrated, ensuring that the encrypted data still reflects the original relationships, ultimately forming complete audit shared data. For example, the encrypted data of 900 purchase vouchers are integrated according to the hierarchical structure of "Audit Basic Information - Financial Data - Purchase Voucher Data". Based on the association identifier "GuanLian-001", the corresponding encrypted purchase voucher data is bound to the encrypted contract data. Based on the association identifier "GuanLian-002", the corresponding encrypted supplier name is bound to the encrypted supplier number. Finally, the data is integrated to form complete audit shared data.

[0051] By adopting the above steps S231 to S234, it is helpful to: achieve the structured sorting and standardized encryption of effective audit data, which not only protects the privacy of the entire audit data and avoids the leakage of original data, but also fully preserves the original relationship between data, improves the efficiency and accuracy of collaborative annotation, and provides reliable encrypted data support for collaborative audit annotation by multiple audit units.

[0052] S240: Obtain the legitimate node addresses and identity information of multiple audit assistance parties, verify the legitimacy of the node identities of each audit assistance party, and obtain authorized compliant nodes.

[0053] It is understandable that the legitimate node address of an audit assisting party refers to the node address (such as IP address, dedicated node ID) of the audit unit used by the audit assisting party to access the audit collaboration electronic device. Each assisting party has a unique node address used to receive shared audit data. Identity information refers to the main information of the audit assisting party, including the assisting party's name, qualification certificates (such as audit firm qualification certificates, auditor practice certificates), and authorization letter (collaborative annotation authorization document issued by the audit initiator). Node identity legitimacy verification refers to the electronic device verifying the node address and identity information of the audit assisting party to confirm whether the audit assisting party is a legitimate assisting party authorized by the audit initiator and whether it has the qualifications for collaborative annotation. Authorized compliant nodes refer to audit unit nodes of audit assisting parties that have passed the legitimacy verification and are confirmed to have collaborative annotation qualifications and legitimate node addresses. Only authorized compliant nodes can receive shared audit data and perform annotation operations. The method for obtaining authorized compliant nodes is as follows: When an audit assisting party connects to the electronic device, it submits its node address and identity information. The electronic device compares the node address with the list of authorized assisting parties provided in advance by the audit initiator, verifies the authenticity of the identity information (such as verifying the qualification certificate number and the validity of the power of attorney), and checks the legality of the node address (such as checking whether it is a malicious node or whether it is within the authorized IP range). After verification, authorized compliant nodes are selected. For example, the audit initiator pre-authorizes three audit assisting parties (A audit firm, B industry expert, and C third-party compliance agency). Each of the three assisting parties submits its own node address (such as A firm's node address "IP:192.168.1.100") and identity information (A firm's audit qualification certificate and the power of attorney issued by the audit initiator). The electronic device compares the authorized list, verifies the authenticity of the qualification certificate and the validity of the power of attorney, checks whether the node address is legal, and finally confirms that the nodes of the three assisting parties are all authorized compliant nodes and can receive audit shared data.

[0054] The S250 transmits audit-shared data to authorized compliance nodes of each audit assisting party via a dedicated encrypted transmission channel for privacy computing.

[0055] It is understandable that a dedicated encrypted transmission channel for privacy computing refers to a secure channel built on privacy computing technology specifically for transmitting encrypted data. During data transmission, the data undergoes secondary encryption and employs technologies such as identity authentication and data verification to prevent data theft, tampering, and interception during transmission. Compared to ordinary transmission channels, it offers higher security and further protects the privacy and security of audit shared data transmission. Sending to authorized compliance nodes means that the integrated audit shared data is sent to each authorized compliance node according to their respective addresses. Only authorized compliance nodes can receive the data; unauthorized nodes cannot obtain any data. The method for sending to authorized compliance nodes can be as follows: electronic devices construct a dedicated encrypted transmission channel for privacy computing (e.g., based on SSL / TLS protocols or privacy computing frameworks), perform secondary encryption on the audit shared data, and then, according to the addresses of the authorized compliance nodes, send the data to the authorized compliance nodes of each collaborating party using targeted transmission technology. After transmission is complete, the electronic device receives confirmation information from the receiving node, confirming successful data transmission. For example, the electronic device re-encrypts the integrated audit shared data (900 encrypted purchase vouchers and related data) through a dedicated encrypted transmission channel for privacy computing. Then, it sends the data to the authorized compliance nodes of Audit Institution A (node ​​address IP: 192.168.1.100), Industry Expert B (node ​​address IP: 192.168.1.101), and Third-Party Compliance Institution C (node ​​address IP: 192.168.1.102). After receiving the data, each node sends a confirmation message to the electronic device to ensure that the data transmission is error-free and has not been tampered with.

[0056] By employing steps S210 to S250, the following benefits can be achieved: Secure processing of audit data throughout the entire process, from raw data to shared data; Improved labeling accuracy through data cleaning and verification; Double protection of data privacy and transmission security through homomorphic encryption and dedicated encrypted transmission channels, preventing leakage of raw audit data; and Node identity verification ensuring that only authorized parties can access the data, preventing unauthorized access.

[0057] S300 receives audit authorization information from the audit initiator for multiple audit assisting parties. This audit authorization information is used to control the annotation operations of each audit assisting party.

[0058] It is understandable that audit authorization information refers to information issued by the audit initiator to clarify the annotation permissions and operational scope of each audit assistant. The core function of audit authorization information is to control the annotation operations of each assistant, preventing unauthorized or irregular annotation, and ensuring that the annotation process is standardized and controllable. Audit authorization information may include assistant identification, authorized annotation scope (e.g., only allowing annotation of abnormal amounts on purchase vouchers, only allowing annotation of contract compliance), authorization period (e.g., annotation operations end on November 10, 2024), and annotation operation permissions (e.g., only allowing viewing and annotation, not allowing modification of encrypted data), etc. The audit authorization information is obtained as follows: the audit initiator generates corresponding audit authorization information based on the qualifications and division of labor of each audit assistant, and sends it to an electronic device via encrypted transmission. The electronic device receives and stores the audit authorization information for subsequent annotation operation control. For example, the audit initiator assigns different annotation permissions to three authorized assistants: Audit institution A is authorized to annotate "abnormal amounts on purchase vouchers" within the scope of "annotation", with an authorization period from October 20, 2024 to November 10, 2024, and permissions of "viewing and annotation". Industry expert B is authorized to annotate "procurement contract compliance," with the same authorization period as above and the permissions to "view, annotate, and provide annotation opinions." Third-party compliance agency C is authorized to annotate "supplier qualification compliance," with the same authorization period as above and the permissions to "view and annotate." This information is then integrated to form audit authorization information and sent to electronic devices.

[0059] S400 performs hash processing on the audit authorization information to generate an audit authorization information hash value.

[0060] In essence, hashing refers to converting audit authorization information of arbitrary length into a fixed-length hash value (which can be a string of hexadecimal characters) using a hash algorithm (such as SHA-256 or MD5). The core characteristics of a hash value are "irreversibility" and "uniqueness." The audit authorization information hash value is a fixed-length string obtained after hashing, used to verify the integrity and authenticity of the audit authorization information and prevent its tampering. For example, receiving audit authorization information and processing it using the SHA-256 hash algorithm generates a 64-bit hexadecimal hash value "a1b2c3d4...f7g8h9". This hash value uniquely corresponds to the original audit authorization information. If the original authorization information is tampered with (e.g., the scope of authorization for organization A is modified), the hash value generated after re-hashing will be completely different from the original hash value.

[0061] As an optional embodiment of this application, S400 involves hashing the audit authorization information to generate an audit authorization information hash value, including: S410, preprocess the received audit authorization information. Preprocessing removes redundant information from the audit authorization information.

[0062] Preprocessing, as we understand it, refers to cleaning and standardizing the received audit authorization information. Its core purpose is to remove redundant information and standardize the format, ensuring the accuracy and consistency of hash processing. Redundant information refers to information in the audit authorization information that is irrelevant to the core content of the authorization and does not affect its validity. This includes extra spaces, line breaks, duplicate descriptions (such as repeatedly stating "the authorization period is November 10, 2024"), and irrelevant remarks (such as "please assist in completing the annotation as soon as possible"). This redundant information can cause the same authorization information to generate different hash values, affecting subsequent verification. For example, if the received audit authorization information contains extra line breaks and spaces, and repeatedly states "the authorization period is November 10, 2024," along with an irrelevant note such as "please assist in paying attention to the annotation standard," preprocessing removes this redundant information and standardizes the format, resulting in standardized audit authorization information and ensuring the accuracy of subsequent hash processing.

[0063] S420: Perform a hash operation on the preprocessed audit authorization information to generate a fixed-length audit authorization information hash value. This hash value is used to verify the integrity of the audit authorization information to prevent tampering.

[0064] As can be understood, hashing refers to inputting preprocessed audit authorization information (without redundancy and in a standardized format) into a hash algorithm, and then outputting a fixed-length hash value through the algorithm's operation. Commonly used hash algorithms include SHA-256 (generating a 64-bit hash value) and MD5 (generating a 32-bit hash value). This application prefers the SHA-256 algorithm for its higher security. A fixed-length audit authorization information hash value means that regardless of the original length of the audit authorization information, the length of the hash value obtained after the hash operation is fixed. This characteristic facilitates subsequent verification operations. The principle behind using the audit authorization information hash value to verify the integrity of audit authorization information is that if the original authorization information is tampered with, even by a minor modification (such as changing a single character), the hash value generated after the hash operation will change significantly. By comparing the hash values, it can be determined whether the authorization information has been tampered with. The audit authorization information hash value is obtained by calling the SHA-256 hash algorithm to perform a hash operation on the preprocessed audit authorization information, generating a 64-bit hexadecimal audit authorization information hash value, which is then stored on the consortium blockchain for verification of subsequent annotation requests. For example, the pre-processed audit authorization information is processed using the SHA-256 hash algorithm to generate a hash value "a1b2c3d4e5f6...x7y8z9". This hash value is then stored on the consortium blockchain. When the audit assistance party subsequently initiates a labeling request, the electronic device will compare the hash value of the authorization information in the request with the hash value stored on the blockchain to determine whether the authorization information has been tampered with.

[0065] By employing steps S410 to S420, the accuracy and reliability of audit authorization information hash values ​​are improved. Simultaneously, preprocessing removes redundant information, ensuring that identical authorization information generates the same hash value. The hash operation generates fixed-length hash values, facilitating rapid subsequent verification. The irreversibility and uniqueness of the hash value effectively prevent tampering with audit authorization information, guaranteeing its authenticity and integrity.

[0066] In one possible implementation, S420 performs a hash operation on the preprocessed audit authorization information to generate a fixed-length audit authorization information hash value, including: S421, serializes the preprocessed audit authorization information, converting it into a binary data stream that can be used for hash operations.

[0067] Serialization, as we understand it, refers to converting pre-processed audit authorization information (which can be in text, JSON, etc.) into a binary data stream (composed of 0s and 1s) that a computer can recognize and process. The purpose of serialization is to convert non-binary authorization information into a format suitable for hash algorithms, because hash algorithms can only operate on binary data. A binary data stream is a continuous sequence of binary numbers (0s and 1s). The length of the binary data stream is related to the content of the original authorization information, but the format is uniform and can be directly input into a hash algorithm for calculation. For example, if the pre-processed audit authorization information is in JSON format (containing assisting party identification, authorization scope, authorization period, etc.), a JSON serialization tool can convert the JSON-formatted audit authorization information into a binary data stream "0101001101101000 01100101 01100101...", which can be directly input into a hash algorithm for calculation.

[0068] S422 performs a hash operation on the binary data stream to generate an audit authorization information hash value.

[0069] Hash operations, as the name suggests, involve inputting a binary data stream into a pre-defined hash algorithm (such as SHA-256), processing the binary data stream using the algorithm, and ultimately outputting a fixed-length hash value for audit authorization information. Compared to directly hashing audit authorization information in text format, hashing binary data streams avoids inconsistencies in hash values ​​caused by differences in text encoding and format, further improving the accuracy and consistency of audit authorization information hash values. For example, inputting the binary data stream "0101001101101000 01100101 01100101..." into the SHA-256 hash algorithm generates a 64-bit hexadecimal audit authorization information hash value "a1b2c3d4e5f6...x7y8z9". This 64-bit hexadecimal hash value corresponds one-to-one with the original binary data stream, and thus one-to-one with the original audit authorization information, improving the accuracy of verification.

[0070] Adopting steps S421 to S422 above helps to: further standardize the hash operation process. Through serialization, authorization information is uniformly converted into a binary data stream, improving the uniformity of the input format for hash operations and enhancing the accuracy and consistency of hash values. Simultaneously, performing hash operations on the binary data stream better preserves the characteristics of the original audit authorization information, confirms the uniqueness and irreversibility of the audit authorization information hash value, and further strengthens the verification of the integrity and authenticity of the audit authorization information.

[0071] The S500 receives data annotation information from multiple audit assistance parties based on the hash value of the audit authorization information. This data annotation information represents the annotation of encrypted shared audit data, resulting in an audit data stream with annotated data.

[0072] It is understandable that, based on the hash value of audit authorization information, electronic devices first verify the legitimacy of the audit assistance provider's annotation request and the completeness and tamper-proof nature of the audit authorization information before receiving data annotation information sent by the audit assistance provider. Only after passing the verification will the electronic device receive the data annotation information sent by the audit assistance provider. Data annotation information refers to the encrypted annotation information generated by the audit assistance provider within the authorized scope after annotating the encrypted shared audit data. This includes annotation location (such as the amount field of a purchase voucher), annotation type (such as abnormal annotation, compliance annotation, question annotation), annotation content (such as "Purchase amount exceeds the average amount of the same period by 50%, suspected of being abnormal" or "Contract lacks signature, compliance is questionable"), annotation time, annotation personnel, and other information. It is encrypted annotation information of the original audit data without decrypting the original audit data. For example, audit firm A, through an authorized compliance node, annotates encrypted purchase voucher data. If it finds that the encrypted purchase amount field of a certain voucher is marked as "suspected anomaly, exceeding the average amount of the same period by 50%", it generates data annotation information and sends the annotation request along with the hash value of the audit authorization information. After the electronic device compares the hash value of the audit authorization information and finds that it is correct, it receives the data annotation information and associates the data annotation information with the corresponding encrypted voucher data to form an annotated audit data stream.

[0073] As an optional embodiment of this application, in step S500, based on the hash value of the audit authorization information, data annotation information sent by multiple audit assistance parties is received, including: S510 compares and verifies the annotation request initiated by the audit assistance party with the hash value of the audit authorization information stored on the consortium blockchain.

[0074] It is understandable that a labeling request refers to a request initiated by the audit assistance party to submit data labeling information. The labeling request includes the node identifier of the audit assistance party, the hash value of the audit authorization information, the data labeling information, and the corresponding encrypted data identifier. Consortium blockchain notarization refers to storing the generated audit authorization information hash value on the consortium blockchain. Utilizing the blockchain's "immutable and traceable" characteristics, the authenticity and integrity of the audit authorization information hash value cannot be tampered with. Comparison and verification refers to the electronic device extracting the audit authorization information hash value from the labeling request and comparing it one by one with the audit authorization information hash value stored on the consortium blockchain to determine if the two audit authorization information hash values ​​are completely identical. Simultaneously, it verifies whether the node identifier in the labeling request is an authorized and compliant node and whether the labeling scope is within the authorized range. For example, an expert from industry B initiates a labeling request, which includes the audit authorization information hash value "a1b2c3d4...f7g8h9", the node identifier "IP:192.168.1.101", and the labeling content (contract compliance labeling). The electronic device extracts the audit authorization information hash value and compares it with the audit authorization information hash value stored on the consortium blockchain. If they match, the node identifier is verified to be an authorized and compliant node, and the labeling scope is within the authorized range, thus completing the comparison and verification.

[0075] S520, after successful verification, receives data annotation information submitted by the audit assistance party for the audit shared data.

[0076] It's understandable that successful verification means the hash value of the audit authorization information in the annotation request is completely consistent with the hash value stored on the consortium blockchain, the node identifier is an authorized and compliant node, and the annotation scope is within the range specified in the audit authorization information. This confirms the annotation request is legal and valid, and the assisting party possesses the corresponding annotation permissions. Receiving data annotation information means the electronic device receives the annotation content submitted by the audit assisting party and simultaneously associates and binds the annotation information with the corresponding audit shared data (encrypted data), recording information such as annotation time, annotation personnel, and annotation type for subsequent summarization and audit result generation. For example, after verifying the annotation request from an expert in Industry B, the electronic device receives the annotation information submitted by the expert: "The purchase contract lacks supplier signature, compliance is questionable." It associates the data annotation information with the corresponding encrypted contract data identifier, stores it in the electronic device, and records the annotation time as "October 25, 2024" and the annotation personnel as "Expert in Industry B," thus completing the receipt of data annotation information.

[0077] By employing steps S510 to S520, the following benefits are achieved: Ensuring the legitimacy of annotation requests. Comparing the hash values ​​stored on the consortium blockchain improves the authenticity and integrity of audit authorization information, preventing its tampering. Verifying node identifiers and annotation scope ensures that only annotation requests initiated by authorized, compliant nodes within their authorized scope are accepted, thus standardizing the annotation process.

[0078] S600 obtains audit result data based on multiple data annotation information. The audit result data represents the unified audit data stream obtained by overlaying shared audit data with the data annotation information.

[0079] It is understandable that "based on multiple data annotation information" refers to the electronic device aggregating the encrypted annotation information submitted by all audit collaborators. Without decrypting the original audit data and annotation content, it organizes, verifies, and integrates the encrypted annotation information to form a unified encrypted annotation opinion. The audit result data is encrypted throughout the process, including encrypted original audit data, encrypted unified annotation opinions, and summarized annotation information. Only the audit initiator can decrypt and view this data using a private key. This is the core basis for issuing the audit report, preventing the plaintext leakage of audit conclusions, anomaly judgments, and suspected violations during the collaboration process. For example, the electronic device aggregates the annotation information from three collaborators, A, B, and C. For a specific encrypted purchase voucher, A annotates "Amount suspected to be abnormal," B annotates "Contract compliance questionable," and C annotates "Supplier qualifications compliant." The electronic device organizes and verifies this annotation information to form a unified annotation opinion: "Amount suspected to be abnormal, contract compliance questionable, supplier qualifications compliant." This unified annotation opinion is then overlaid with the corresponding encrypted purchase voucher data, integrating all encrypted data annotation information and shared audit data to form the audit result data.

[0080] As an optional embodiment of this application, in step S600, the audit shared data is annotated based on multiple data annotation information to obtain audit result data, including: S610 categorizes and organizes multiple data annotation information, summarizes all annotation content corresponding to the same data field, and obtains summarized annotation data.

[0081] It can be understood that classification and organization refers to the electronic device categorizing all data annotation information submitted by audit assistance parties according to data fields, data items, and annotation types. For example, categorizing by "purchase amount field," "contract compliance field," and "supplier qualification field," or by the identifier of each encrypted data entry, or by "abnormal annotations," "compliant annotations," and "questionable annotations," making the annotation information clear and organized. All annotation content corresponding to the same data field refers to all annotation content submitted by different audit assistance parties for the same encrypted data field (such as the "purchase amount" field of a purchase voucher). Summary annotation data refers to the annotation set formed by summarizing all annotation content for the same data field and data item, including all annotation opinions, annotation personnel, annotation time, etc., for multiple data annotation information. The summary annotation data can be obtained by the electronic device classifying all data annotation information using a data classification algorithm, grouping it according to data fields and data items, and summarizing all annotation content within the same group to form summary annotation data, facilitating subsequent consistency verification. For example, the electronic device summarizes the annotation information of three assisting parties. For the "Purchase Amount" field, A annotates "Exceeds the average amount of the same period by 50%, suspected of being abnormal", B annotates "Amount is consistent with the invoice amount, no abnormality", and C does not annotate the "Purchase Amount" field. The electronic device summarizes these two annotation contents to form the summary annotation data of the "Purchase Amount" field, which includes information such as annotation content, annotation personnel, and annotation time.

[0082] S620 performs consistency verification on the summarized annotation data, compares different annotation contents corresponding to the same data field, and obtains the final annotation opinion.

[0083] Consistency verification refers to the process by which electronic devices compare and analyze different annotations for the same data field in aggregated annotation data to determine whether the annotations are consistent. If inconsistencies exist, they are coordinated using preset rules (such as majority rule or priority given to authoritative assisting parties) to form a unified annotation opinion. Different annotation content refers to annotations submitted by different audit assisting parties for the same data field with inconsistent opinions (e.g., A labels it "abnormal," B labels it "no abnormality"). The final annotation opinion refers to the unified and standardized annotation opinion formed after consistency verification. It is the core annotation content that is subsequently overlaid with audit shared data, improving the consistency and accuracy of the annotation results. For example, for the aggregated annotation data of the "purchase amount" field (A labels it "suspected abnormality," B labels it "no abnormality"), the electronic device performs consistency verification and finds a discrepancy. At this point, according to preset rules and combined with the original audit data, it is determined that the "purchase amount" does indeed exceed the average amount of the same period, and A's annotation opinion is judged to be correct, forming the final annotation opinion "purchase amount exceeds the average amount of the same period by 50%, suspected abnormality."

[0084] S630 overlays the final annotations with the shared audit data to obtain unified audit result data.

[0085] Data overlay processing can be understood as associating and binding the final annotation opinions with the corresponding audit shared data, adding the final annotation opinions to the corresponding audit shared data, so that each audit shared data piece carries a unique final annotation opinion, forming a complete and unified audit data stream. Unified audit result data refers to the data stream obtained after overlay, containing audit shared data, encrypted final annotation opinions, and annotation summary information (such as annotation personnel, annotation time, and verification process). The audit result data remains encrypted and can only be decrypted and viewed by the audit initiator using a private key. It is the core basis for the audit initiator to issue the audit report. The audit result data is obtained as follows: the electronic device associates and binds each audit shared data piece with the corresponding final annotation opinion, integrates them according to the data hierarchy, adds annotation summary information, forms unified audit result data, stores it in the electronic device, and simultaneously sends a result notification to the audit initiator for decryption and viewing. For example, the final annotation opinion of "purchase amount exceeds the average amount of the same period by 50%, suspected of being abnormal" for electronic devices is superimposed with the corresponding encrypted purchase voucher data, and the annotation summary information is linked. At the same time, all the superimposed encrypted data is integrated by level to form a unified audit result data, which is available for the audit initiator to decrypt and view.

[0086] By employing steps S610 to S630 above, the labeled information can be clearly organized through classification, facilitating subsequent verification and summarization. This improves the efficiency and quality of the audit work while maintaining the traceability of the labeling process, facilitating subsequent audit review.

[0087] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0088] Corresponding to the audit data processing method based on blockchain and privacy computing described in the above embodiments, this application also provides an audit data processing device based on blockchain and privacy computing. Each unit of the device can implement each step of the audit data processing method based on blockchain and privacy computing. Figure 4 This diagram illustrates the structural block diagram of an audit data processing apparatus based on blockchain and privacy computing provided in an embodiment of this application. For ease of explanation, only the parts relevant to the embodiments of this application are shown.

[0089] Reference Figure 4 The device includes: The initiating unit is used to receive audit data sent by the audit initiator. This audit data is used by multiple auditing entities to collaboratively annotate audit-related content.

[0090] The encryption unit is used to encrypt audit data using a homomorphic encryption algorithm to obtain shared audit data, which is then sent to multiple audit collaborators. The homomorphic encryption algorithm is used to protect privacy and security during the transmission of shared audit data, preventing data leakage.

[0091] The authorization unit is used to receive audit authorization information from the audit initiator for multiple audit assisting parties. This audit authorization information is used to control the annotation operations of each audit assisting party.

[0092] The hash unit is used to perform hash processing on the audit authorization information to generate the audit authorization information hash value.

[0093] The annotation unit is used to receive data annotation information from multiple audit assistance parties based on the hash value of the audit authorization information. The data annotation information represents the annotation of encrypted shared audit data, resulting in an audit data stream with annotated data.

[0094] The results unit is used to obtain audit result data based on multiple data annotation information. Specifically, the audit result data represents the unified audit data stream obtained by overlaying shared audit data with the data annotation information.

[0095] It should be noted that the information interaction and execution process between the above-mentioned units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0096] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units is used as an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the device can be divided into different functional units to complete all or part of the functions described above. The functional units in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0097] This application also provides an electronic device. Figure 5This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Figure 5 Only one is shown in the image), at least one memory 61 ( Figure 5 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60, wherein when the processor 60 executes the computer program 62, it causes the electronic device 6 to perform the steps in any of the above embodiments of the blockchain and privacy computing-based audit data processing method, or causes the electronic device 6 to perform the functions of the units in the above embodiments of the apparatus.

[0098] For example, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the electronic device 6.

[0099] The electronic device 6 may be a cloud server, cloud host, commercial desktop computer, laptop computer, e-commerce dedicated smart terminal, tablet computer, etc. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method as described in any of the foregoing aspects. The electronic device 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 5 This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0100] The processor 60 can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0101] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may be an external storage device of the electronic device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 6. Furthermore, the memory 61 may include both internal and external storage units of the electronic device 6. The memory 61 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0102] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0103] This application provides a computer program product that, when run on an electronic device, causes the electronic device to perform the steps in any of the above method embodiments.

[0104] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or system capable of carrying computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0105] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0106] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0107] In the embodiments provided in this application, it should be understood that the disclosed blockchain-based and privacy-preserving computing-based audit data processing method, apparatus, and electronic device can be implemented in other ways. For example, the embodiments of the blockchain-based and privacy-preserving computing-based audit data processing apparatus and electronic device described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between units may be electrical, mechanical, or other forms.

[0108] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An audit data processing method based on blockchain and privacy computing, characterized in that, include: Receive audit data sent by the audit initiator; wherein, the audit data is used for collaborative annotation of audit-related content by multiple auditing entities; The audit data is encrypted using a homomorphic encryption algorithm to obtain audit shared data, which is then sent to multiple audit collaborators. The homomorphic encryption algorithm is used to protect privacy and security during the transmission of audit shared data to prevent data leakage. The system receives audit authorization information for multiple audit assisting parties sent by the audit initiator; wherein the audit authorization information is used to control the annotation operations of each audit assisting party. The audit authorization information is hashed to generate an audit authorization information hash value; Based on the hash value of the audit authorization information, data annotation information sent by multiple audit assistance parties is received; wherein, the data annotation information indicates that the encrypted audit shared data is annotated to obtain an audit data stream with annotated data; Based on multiple data annotation information, audit result data is obtained; wherein, the audit result data represents the result of overlaying the audit shared data with the data annotation information to obtain a unified audit data stream.

2. The audit data processing method based on blockchain and privacy computing according to claim 1, characterized in that, The audit data is encrypted using a homomorphic encryption algorithm to obtain shared audit data, which is then sent to multiple audit assistance parties, including: The audit data received from the audit initiator is cleaned and verified, invalid data is removed, data format deviations are corrected, and valid audit data that meets the collaborative annotation requirements is selected. A homomorphic encryption algorithm suitable for the required valid audit data is selected, and a corresponding encryption key pair is generated; wherein, the key pair includes a public key and a private key; the public key is used to perform encryption operations; and the private key is used for decryption and verification of the audit result data; Based on the public key, the valid audit data is fully encrypted, and the original association relationship of the audit data is preserved during the encryption process to generate shared audit data; Obtain the legitimate node addresses and identity information of multiple audit assistance parties, verify the legitimacy of the node identities of each audit assistance party, and obtain authorized and compliant nodes; The audit shared data is sent to the authorized compliance nodes of each of the audit assisting parties via a dedicated encrypted transmission channel for privacy computing.

3. The audit data processing method based on blockchain and privacy computing according to claim 2, characterized in that, The process involves fully encrypting the valid audit data based on the public key, preserving the original associations of the audit data during encryption, and generating shared audit data, including: Based on the public key, the valid audit data is structured and parsed to extract each data field, field relationship, and data hierarchy structure from the valid audit data; Based on the extracted field relationships and the data hierarchy, add association identifiers to the valid audit data; According to the preset encryption order, the valid audit data with the associated identifier is fully encrypted field by field to obtain encrypted data; The encrypted data is integrated and, based on the association logic corresponding to the association identifier, complete audit shared data is formed.

4. The audit data processing method based on blockchain and privacy computing according to claim 3, characterized in that, The step of performing structured parsing on the valid audit data, extracting each data field, field relationships, and data hierarchy from the valid audit data, includes: Obtain the data storage format and encoding rules of the valid audit data; Based on the data storage format and the encoding rules, the valid audit data is decomposed to obtain the audit basic information field, the financial data field, and the audit supporting evidence field; Based on the subordinate and correlation verification relationships of the audit basic information field, the financial data field, and the audit supporting evidence field, a field association list and data hierarchy structure are obtained.

5. The audit data processing method based on blockchain and privacy computing according to claim 1, characterized in that, The step of hashing the audit authorization information to generate an audit authorization information hash value includes: The received audit authorization information is preprocessed; wherein, the preprocessing is used to remove redundant information from the audit authorization information; A hash operation is performed on the preprocessed audit authorization information to generate a fixed-length audit authorization information hash value; wherein, the audit authorization information hash value is used to verify the integrity of the audit authorization information to prevent the information from being tampered with.

6. The audit data processing method based on blockchain and privacy computing according to claim 5, characterized in that, The step of performing a hash operation on the preprocessed audit authorization information to generate a fixed-length audit authorization information hash value includes: The preprocessed audit authorization information is serialized and converted into a binary data stream that can be used for hash operations; A hash operation is performed on the binary data stream to generate an audit authorization information hash value.

7. The audit data processing method based on blockchain and privacy computing according to claim 1, characterized in that, The step of receiving data annotation information from multiple audit assistance parties based on the hash value of the audit authorization information includes: The annotation request initiated by the audit assistance party is compared and verified with the hash value of the audit authorization information stored on the consortium blockchain; After successful verification, the system receives data annotation information submitted by the audit assistance party regarding the audit shared data.

8. The audit data processing method based on blockchain and privacy computing according to claim 1, characterized in that, The audit result data obtained based on multiple data annotation information includes: The multiple data annotation information are classified and organized, and all annotation content corresponding to the same data field is summarized to obtain the summarized annotation data; The summarized annotation data is subjected to consistency verification, and different annotation contents corresponding to the same data field are compared to obtain the final annotation opinion; The final annotation opinions are overlaid with the audit shared data to obtain unified audit result data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 8.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 8.

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