Electronic accounting file data processing method and device and electronic equipment

Abstract

This application provides a method, apparatus, and electronic device for processing electronic accounting record data, relating to the field of data processing technology, and solves the technical problem of low data transmission efficiency in network environments where external and internal networks are isolated. The method includes: encrypting electronic accounting record data using a symmetric or asymmetric encryption algorithm and transmitting it to a designated receiving end; performing MD5 verification on the electronic accounting record data at the designated receiving end; performing consistency verification on structured data through format verification, range verification, and logical verification; and performing consistency verification on unstructured data through file comparison; importing structured data into a database using an import tool or custom script provided by the database; uploading the target file corresponding to the unstructured data to a file server through a web interface or API; and storing the target file on the file server through NAS, SAN, or cloud storage services.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, and electronic device for processing electronic accounting record data. Background Technology

[0002] Currently, for security reasons, many large enterprises build their digital systems within their own proprietary IT environments, without providing external network access. For company archive platforms managing electronic accounting data, the data sources are complex, with most data originating from the external network. However, the platform is deployed within the enterprise's intranet environment, isolated from the external network, preventing data transmission and resulting in low data transmission efficiency in this isolated network environment. Summary of the Invention

[0003] The purpose of this invention is to provide a method, apparatus, and electronic device for processing electronic accounting record data, in order to solve the technical problem of low data transmission efficiency in network environments where external and internal networks are isolated from each other.

[0004] In a first aspect, embodiments of this application provide a method for processing electronic accounting record data, the method comprising:

[0005] The system obtains raw electronic accounting record data from the source system. The structured data in the electronic accounting record data is obtained by calling an Application Programming Interface (API). The structured data is converted into a standard format according to a specified data structure definition standard, and a data dictionary is generated based on the structured data to record the meaning and type of each field. The unstructured data in the electronic accounting record data is compressed using a compression algorithm, and a Message Digest Algorithm (MD5) file digest is generated based on the unstructured data.

[0006] The electronic accounting record data is encrypted using a symmetric encryption algorithm or an asymmetric encryption algorithm and then transmitted to the designated receiving end.

[0007] The electronic accounting record data is subjected to MD5 verification by the designated receiving end to obtain the MD5 verification result. If the MD5 verification result is successful, the structured data is subjected to consistency verification by means of format verification, range verification and logical verification, and the unstructured data is subjected to consistency verification by means of file comparison to obtain the consistency verification result.

[0008] If the consistency verification result is successful, the structured data is imported into the database using the import tool or custom script provided by the database. The target file corresponding to the unstructured data is uploaded to the file server through the World Wide Web (Web) interface or API. The target file is then stored in the file server through Network Attached Storage (NAS), Storage Area Network (SAN), or cloud storage services.

[0009] In one possible implementation, the step of obtaining the original electronic accounting record data from the source system includes:

[0010] For the structured data in the electronic accounting archive data, the original structured data is obtained from the source system by calling the API interface, the structured data is converted into a standard format according to the specified archive data structure definition standard, and a data dictionary is generated based on the structured data, recording the meaning and data type of the data fields;

[0011] For the unstructured data in the electronic accounting archive data, a compression algorithm is used to compress the data to obtain a compressed file, and an MD5 file digest is generated based on the compressed file; wherein, the MD5 file digest is used to verify the integrity of the compressed file.

[0012] In one possible implementation, the step of encrypting the electronic accounting record data using a symmetric encryption algorithm or an asymmetric encryption algorithm and transmitting it to a designated receiving end includes:

[0013] The electronic accounting record data is encrypted using an encryption program through a symmetric encryption algorithm or an asymmetric encryption algorithm to obtain encrypted electronic accounting record data;

[0014] The encrypted electronic accounting record data is transmitted through a designated physical storage medium with anti-interference capabilities and write protection, and the transmission result is determined.

[0015] The integrity of the electronic accounting record data in the transmission result is verified using a hash function or a message authentication code (MAC).

[0016] In one possible implementation, the step of performing MD5 verification on the electronic accounting record data through the designated receiving end to obtain the MD5 verification result includes:

[0017] The electronic accounting record data is subjected to MD5 verification by the designated receiving end to obtain the hash value matching result.

[0018] If the hash value matching result is a complete hash value match, it is determined that the electronic accounting record data has not been tampered with during transmission;

[0019] If the hash value matching result is a hash value mismatch, it is determined that the electronic accounting record data has changed during transmission, and a signal of refusal to receive is sent through the designated receiving end so that the sender can retransmit the electronic accounting record data.

[0020] In one possible implementation, the steps of performing consistency checks on the structured data through format validation, range validation, and logical validation, and on the unstructured data through file comparison, to obtain the consistency check result, include:

[0021] For the structured data, format validation is performed according to the specified data format definition standard to check whether the data values ​​in the structured data are within the specified range, and the consistency of the structured data is checked according to the specified business logic to obtain the consistency validation result.

[0022] For the unstructured data, compare whether the file size of the unstructured data is consistent before and after transmission. Use a hash algorithm to hash the target file corresponding to the unstructured data, compare whether the hash value of the target file is consistent before and after transmission, and compare the metadata information of the target file before and after transmission to obtain the consistency verification result.

[0023] In one possible implementation, the steps of importing the structured data into the database using an import tool or custom script provided by the database, uploading the target file corresponding to the unstructured data to a file server via a web interface or API, and storing the target file on the file server via NAS, SAN, or cloud storage services include:

[0024] For the structured data, the correspondence between the source data structure and the database table structure of the structured data is determined by data mapping. The source data is cleaned, and the cleaned data is imported into the database using the import tool provided by the database or a custom script. Transactions are used to maintain data consistency during data import, and data verification is performed after the data import is completed.

[0025] For the unstructured data, a file upload interface is created that allows uploading files to a file server via a web interface or API. This interface is used to upload the target file corresponding to the unstructured data to the file server. During the upload process, the type of the target file is verified to ensure that target files of specified allowed file types are uploaded to the file server. Appropriate file processing is then performed based on the target file type. The target file is stored on the file server using NAS, SAN, or cloud storage services. Metadata of the target file is recorded during storage, and access permissions are set to ensure that only authorized users can access the target file.

[0026] In one possible implementation, it also includes:

[0027] The process of preparing, transmitting, verifying, and processing the electronic accounting record data is analyzed to obtain analysis results, and the processes that can be automated are determined based on the analysis results.

[0028] The automated process can be automated by developing automated scripts using various programming languages; the automated scripts include data preparation scripts, transmission scripts, verification scripts, processing scripts, error handling scripts, and script scheduling settings;

[0029] The data preparation script automatically extracts data from the source system and prepares the data according to the specified data structure definition standard; the transmission script automatically transmits the prepared data to a specified storage medium or to a specified receiving end through a specified network channel; the verification script automatically verifies the data received by the specified receiving end; the processing script automatically imports the structured data into the database and performs data cleaning operations, and automatically uploads the unstructured data to the file server for file processing; the error handling automatically records error information and performs corresponding recovery operations when errors occur during the automation process; and the script scheduling settings are used to execute the automation script at regular intervals using a task scheduling tool.

[0030] Secondly, an electronic accounting record data processing device is provided, comprising:

[0031] The acquisition module is used to acquire raw electronic accounting archive data from the source system. The structured data in the electronic accounting archive data is acquired by calling an API interface, converted into a standard format according to a specified data structure definition standard, and a data dictionary is generated based on the structured data to record the meaning and type of fields. The unstructured data in the electronic accounting archive data is compressed using a compression algorithm, and an MD5 file digest is generated based on the unstructured data.

[0032] The transmission module is used to encrypt the electronic accounting file data using a symmetric encryption algorithm or an asymmetric encryption algorithm and transmit it to a designated receiving end;

[0033] The verification module is used to perform MD5 verification on the electronic accounting file data through the designated receiving end to obtain the MD5 verification result. If the MD5 verification result is successful, the structured data is verified for consistency through format verification, range verification and logical verification, and the unstructured data is verified for consistency through file comparison to obtain the consistency verification result.

[0034] The processing module is used to import the structured data into the database using the database's import tool or a custom script if the consistency verification result is successful, upload the target file corresponding to the unstructured data to the file server through a web interface or API, and store the target file on the file server through NAS, SAN, or cloud storage services.

[0035] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the method described in the first aspect above.

[0036] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to perform the method described in the first aspect above.

[0037] The embodiments of this application bring the following beneficial effects:

[0038] This application provides a method, apparatus, and electronic device for processing electronic accounting archive data, capable of acquiring raw electronic accounting archive data from a source system. The structured data in the electronic accounting archive data is obtained by calling an API interface, converted into a standard format according to a specified data structure definition standard, and a data dictionary is generated based on the structured data to record the meaning and type of fields. The unstructured data in the electronic accounting archive data is compressed using a compression algorithm, and an MD5 file digest is generated based on the unstructured data. The electronic accounting archive data is encrypted using a symmetric encryption algorithm or an asymmetric encryption algorithm and transmitted to a designated receiving end. The data is then transmitted via the designated receiving end. The electronic accounting record data is subjected to MD5 verification to obtain an MD5 verification result. If the MD5 verification result is successful, the structured data is subjected to consistency verification through format verification, range verification, and logical verification, and the unstructured data is subjected to consistency verification through file comparison to obtain a consistency verification result. If the consistency verification result is successful, the structured data is imported into the database using the database's import tool or a custom script, and the target file corresponding to the unstructured data is uploaded to the file server through a web interface or API. The target file is then stored on the file server through NAS, SAN, or cloud storage services. This solution utilizes physical storage devices to transmit data in a network environment where the external and internal networks are isolated. This effectively solves the data transmission problem of electronic accounting archives in isolated network environments, improves data transmission efficiency, and enhances data security through encrypted transmission, ensuring the safety of data transmission and storage and preventing data leakage. Furthermore, MD5 verification and consistency verification ensure that data is not tampered with during transmission and storage, reducing the risk of security incidents such as data leakage, tampering, and loss, ensuring the authenticity and reliability of electronic accounting archives, and improving the integrity and accuracy of electronic accounting archive data.

[0039] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1A flowchart illustrating the method for processing electronic accounting record data provided in this application embodiment;

[0042] Figure 2 Another flowchart illustrating the method for processing electronic accounting record data provided in the embodiments of this application;

[0043] Figure 3 A schematic diagram of the structure of an electronic accounting record data processing device provided in an embodiment of this application;

[0044] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0046] The terms "comprising" and "having," and any variations thereof, used in the embodiments of this application, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0047] Currently, the platform is deployed in the enterprise's intranet environment, which is isolated from the external network and cannot transmit data. This results in low data transmission efficiency in the isolated network environment.

[0048] Based on this, embodiments of this application provide a method, apparatus, and electronic device for processing electronic accounting archive data. This method can solve the technical problem of low data transmission efficiency in network environments where external and internal networks are isolated from each other.

[0049] The embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0050] Figure 1 This is a flowchart illustrating a method for processing electronic accounting record data, provided as an embodiment of this application. Figure 1 As shown, the method includes:

[0051] Step S110: Obtain the original electronic accounting record data from the source system.

[0052] The structured data in the electronic accounting archives is obtained by calling the API interface, and the structured data is converted into a standard format according to the specified data structure definition standard. A data dictionary is generated based on the structured data to record the meaning and type of the fields. The unstructured data in the electronic accounting archives is compressed using a compression algorithm, and an MD5 file digest is generated based on the unstructured data.

[0053] It should be noted that the preparation of electronic accounting archive data includes two parts: structured data and unstructured data. For structured data: APIs are used to retrieve the data, and it is formatted using standard formats such as JSON and XML; according to the data structure definition, the data is converted to a standard format, and a data dictionary is generated to record the meaning and type of each field. For unstructured data: files are compressed to reduce file size, using compression algorithms such as gzip and bzip2; a file digest (MD5) is generated for verifying file integrity.

[0054] As an optional implementation method, a unified naming rule is adopted, which is to formulate and adopt a unified naming rule to facilitate file management and identification. The naming rule includes the following information: data type, data source, data generation time and data version.

[0055] In the process of preparing structured data: Data acquisition involves obtaining raw data from accounting software, financial systems, and other applications through API calls or other means, ensuring the completeness, accuracy, and consistency of the acquired data; Data formatting involves converting the acquired raw data into standard formats, such as JSON and XML, to improve data readability and exchangeability. Data formatting should follow relevant specifications and standards, such as the "Electronic Accounting Archives Management Measures"; Data conversion involves converting the formatted data into standard formats according to the accounting archive data structure definition, ensuring data completeness, accuracy, and consistency; Data dictionary generation involves generating a data dictionary for the structured data, recording the meaning and data type of the data fields. The data dictionary should facilitate data understanding and use.

[0056] In the process of preparing unstructured data: First, data compression is performed, that is, unstructured data, such as images and scanned documents, are compressed to reduce file size. The compression algorithm should support mainstream formats, such as gzip and bzip2. Then, file digest generation is performed, that is, MD5 or other file digests are generated from the compressed files to verify file integrity. The file digest algorithm should be secure, reliable and easy to use.

[0057] Step S120: Encrypt the electronic accounting file data using a symmetric encryption algorithm or an asymmetric encryption algorithm and transmit it to the designated receiving end.

[0058] In practical applications, for the transmission of electronic accounting data, a secure and reliable transmission medium should be selected, using physical storage methods such as USB flash drives, optical discs, and portable hard drives to transmit data, while ensuring the security of the transmission medium. Encrypted transmission can also be implemented, i.e., encrypting the transmitted data to improve security, using either symmetric or asymmetric encryption algorithms.

[0059] Specifically, to ensure the secure transmission of electronic accounting data, the first step is to select appropriate physical storage media. Commonly used storage media include USB flash drives, optical discs, and portable hard drives. When selecting media, the following points should be considered: Media quality: Choose well-known brands to ensure media stability and lifespan; Capacity: Select storage media with an appropriate capacity based on the amount of data to be transmitted; Interference resistance: Ensure the media can resist external electromagnetic interference during transportation to prevent data corruption; Write protection: Use storage media with write protection to prevent data from being tampered with during transmission.

[0060] As one possible implementation method, encrypting transmitted data is necessary to improve data security. Encryption can prevent unauthorized access and data leakage. Based on how the encryption key is used, encryption algorithms can be divided into symmetric encryption and asymmetric encryption.

[0061] Symmetric encryption algorithms use the same key for both encryption and decryption. Common symmetric encryption algorithms include AES (Advanced Encryption Standard) and DES (Data Encryption Standard). Symmetric encryption is fast, but key distribution and management require additional security measures. Asymmetric encryption algorithms use a pair of keys: a public key and a private key. The public key is used to encrypt data, and the private key is used for decryption. Common asymmetric encryption algorithms include RSA and ECC (Elliptic Curve Cryptography). Asymmetric encryption offers better security, especially in key distribution, but it has higher computational overhead and is slower.

[0062] When implementing encrypted transmission, the following procedures can be followed: Data encryption: Before transmitting data to the storage medium, encrypt the data using encryption software; Key management: Employ a secure key management scheme to ensure the secure storage and transmission of keys. For asymmetric encryption, the public key can be made public, but the private key must be kept strictly confidential; Integrity verification: Use hash functions or Message Authentication Codes (MACs) to verify the integrity and authenticity of the data, ensuring that the data has not been tampered with during transmission.

[0063] Step S130: Perform MD5 verification on the electronic accounting archive data through the designated receiving end to obtain the MD5 verification result. If the MD5 verification result is successful, perform consistency verification on the structured data through format verification, range verification and logical verification, and perform consistency verification on the unstructured data through file comparison to obtain the consistency verification result.

[0064] It should be noted that for the verification of electronic accounting archive data, the receiving end performs the verification, that is, it performs MD5 checksum verification on the received data to ensure data integrity. If the verification fails, it rejects the data and requests retransmission. For data consistency verification, structured data is checked for consistency to ensure data accuracy, and unstructured data is compared with other documents to ensure document integrity.

[0065] Ensuring data integrity and accuracy is crucial during data transmission. The following is a detailed description of receiver verification and data consistency verification:

[0066] Receiver verification: MD5 checksum. MD5 (Message Digest Algorithm 5) is a widely used hash function that generates a 128-bit hash value to ensure data integrity. During data transmission, the sender performs MD5 hashing on the data, generating a hash value, and sends this hash value along with the data to the receiver. Upon receiving the data, the receiver uses the same MD5 algorithm to hash the data again, generating a new hash value. The receiver then compares this newly generated hash value with the hash value provided by the sender.

[0067] If two hash values ​​match exactly, the data can be considered intact and unaltered during transmission. If the hash values ​​do not match, the data may have been altered during transmission, and the receiver should refuse to receive it and request the sender to retransmit it.

[0068] Data consistency verification, which ensures the accuracy of data, typically involves checking the structure and content of the data.

[0069] For structured data (such as records in a database), consistency checks typically include the following aspects: format checks, ensuring that the data format conforms to expected standards, such as date formats, number formats, etc.; range checks, checking whether the data values ​​are within a reasonable range, such as age should be between 0 and 150; and logical checks, checking the consistency of the data according to business logic, such as if a record represents an order, then the order amount should not be negative.

[0070] For unstructured data (such as documents, images, and videos), consistency checks are typically achieved through file comparison: file size comparison, comparing the file size before and after transmission; if the sizes are inconsistent, it may indicate that the file was corrupted during transmission; file hash comparison, using hash algorithms such as MD5 and SHA-256 to hash the file and comparing the hash values ​​before and after transmission to ensure that the file content has not been tampered with; and file metadata comparison, comparing the file's metadata information, such as creation date, modification date, and file type, to ensure that the file's metadata is consistent.

[0071] Step S140: If the consistency verification result is successful, use the import tool or custom script provided by the database to import the structured data into the database, upload the target file corresponding to the unstructured data to the file server through the web interface or API, and store the target file in the file server through NAS, SAN or cloud storage services.

[0072] In processing electronic accounting archive data, structured data is imported into a database and validated to ensure data quality. Unstructured data is uploaded to a file server and processed according to its file type.

[0073] For example, when processing electronic accounting record data, structured and unstructured data require different processing methods. The following is a detailed description of the technical solutions for importing structured data into a database and uploading unstructured files:

[0074] For structured data processing, data is imported into the database. Data mapping: Before importing data, it's necessary to determine the correspondence between the source data structure (e.g., CSV files, Excel spreadsheets) and the database table structure. This includes field mapping and data type conversion. Data cleaning: Before importing data, the source data may need to be cleaned to ensure data quality. This may include removing duplicate records, handling missing values, and correcting erroneous data. Import tools / scripts: Use the database's provided import tools or write custom scripts to import data into the database. For example, use SQL statements to insert data or use ETL (Extract, Transform, Load) tools. Transaction management: Transactions should be used during data import to ensure data consistency. If errors occur during import, transactions can be rolled back to avoid an inconsistent database state. Data validation: After importing, data validation is performed, including checking data integrity, accuracy, and consistency. This may involve executing SQL queries, using database constraints (e.g., foreign keys, unique constraints), and triggers. Backup and recovery: The database should be backed up before importing data so that data can be recovered in case of problems during the import process.

[0075] For unstructured data processing, files are uploaded to a file server. File Upload Interface: Develop a file upload interface that allows users to upload files to the file server via a web interface or API. File Type Validation: During the upload process, validate the file type to ensure only allowed file types (such as PDF, JPG, PNG, etc.) can be uploaded. File Size Limit: Set file size limits to prevent the upload of excessively large files, which helps protect server resources. Virus Scan: Scan files for viruses before uploading to ensure they do not contain malicious software. File Storage: Store files on the file server, using NAS (Network Attached Storage), SAN (Storage Area Network), or cloud storage services. Metadata Management: Record file metadata such as filename, upload date, file size, and file type when storing files for management and retrieval. Access Control: Set file access permissions to ensure only authorized users can access and download files. File Processing: Perform appropriate processing based on file type. For example, for image files, generate thumbnails; for PDF files, extract text content for indexing.

[0076] In this embodiment, data transmission is performed using physical storage devices in a network environment where the external and internal networks are isolated. This effectively solves the data transmission problem of electronic accounting archives in isolated network environments, improves data transmission efficiency, and enhances data security through encrypted transmission, ensuring the safety of data transmission and storage and preventing data leakage. Furthermore, MD5 verification and consistency verification ensure that data is not tampered with during transmission and storage, reducing the risk of security incidents such as data leakage, tampering, and loss, ensuring the authenticity and reliability of electronic accounting archives, and improving the integrity and accuracy of electronic accounting archive data to meet the needs of accounting, auditing, and supervision.

[0077] To address the need for secure data transmission of electronic accounting archives under the domestic IT innovation environment, this application provides a complete workflow solution based on data preparation, transmission, verification, and processing, which enables data transmission of electronic accounting archives across internal and external networks within the domestic IT innovation environment, thereby improving data transmission efficiency.

[0078] The steps described above will be explained in detail below.

[0079] In some embodiments, step S110 above may include the following steps:

[0080] Step a) For the structured data in the electronic accounting archive data, the original structured data is obtained from the source system by calling the API interface, the structured data is converted into a standard format according to the specified archive data structure definition standard, and a data dictionary is generated based on the structured data and the meaning and data type of the data fields are recorded;

[0081] Step b) involves compressing the unstructured data in the electronic accounting archives using a compression algorithm to obtain a compressed file, and then generating an MD5 file digest based on the compressed file. The MD5 file digest is used to verify the integrity of the compressed file.

[0082] The preparation process for structured data involves three steps: First, data acquisition, which involves obtaining raw data from accounting software, financial systems, and other applications through API calls or other means, ensuring the data is complete, accurate, and consistent. Second, data formatting, which involves converting the acquired raw data into standard formats such as JSON and XML to improve readability and exchangeability. Data formatting should follow relevant specifications and standards, such as the "Electronic Accounting Archives Management Measures." Third, data conversion, which involves converting the formatted data into standard formats according to the accounting archive data structure definition, ensuring data completeness, accuracy, and consistency. Finally, data dictionary generation, which involves creating a data dictionary for the structured data, recording the meaning and data type of each data field. The data dictionary should facilitate data understanding and use.

[0083] For the preparation of unstructured data, the first step is data compression, which involves compressing unstructured data such as images and scanned documents to reduce file size. The compression algorithm should support mainstream formats such as gzip and bzip2. The next step is file digest generation, which involves generating MD5 or other file digests from the compressed files to verify file integrity. The file digest algorithm should be secure, reliable, and easy to use.

[0084] By standardizing data formats and structures, data storage, management, and utilization are facilitated. Data availability ensures that users can access and use electronic accounting records anytime, anywhere. Furthermore, by recording data operation logs, including the meaning and data type of data fields, it is easy to trace and investigate security incidents, enabling security auditing.

[0085] In some embodiments, step S120 above may include the following steps:

[0086] Step c) Use an encryption program to encrypt the electronic accounting record data using a symmetric encryption algorithm or an asymmetric encryption algorithm to obtain the encrypted electronic accounting record data;

[0087] Step d) involves transmitting the encrypted electronic accounting record data through a designated physical storage medium with anti-interference capabilities and write protection, and determining the transmission result.

[0088] Step e) uses a hash function or message authentication code (MAC) to verify the integrity of the electronic accounting record data in the transmission result.

[0089] For example, before transmitting data to a storage medium, the data is encrypted using encryption software; key management employs a secure key management scheme to ensure the secure storage and transmission of keys. For asymmetric encryption, the public key can be made public, but the private key must be kept strictly confidential; integrity verification uses hash functions or Message Authentication Codes (MACs) to verify the integrity and authenticity of the data, ensuring that the data has not been tampered with during transmission.

[0090] In this embodiment of the application, by encrypting the transmitted data, unauthorized access and data leakage can be prevented, thereby improving data security.

[0091] In some embodiments, the process of performing MD5 verification on the electronic accounting file data through a designated receiving end to obtain the MD5 verification result in step S130 above may include the following steps:

[0092] Step f) involves performing an MD5 check on the electronic accounting record data through a designated receiving end to obtain the hash value matching result;

[0093] Step g): If the hash value matching result is a complete hash value match, it is determined that the electronic accounting record data has not been tampered with during transmission.

[0094] Step h): If the hash value matching result is a hash value mismatch, it is determined that the electronic accounting record data has changed during transmission, and a signal of rejection is sent by the designated receiving end to make the sender retransmit the electronic accounting record data.

[0095] As one possible implementation, the receiving end can generate a 128-bit hash value using MD5 checksum to ensure data integrity. During data transmission, the sender performs MD5 hashing on the data, generating a hash value, and sends this hash value along with the data to the receiver. Upon receiving the data, the receiver uses the same MD5 algorithm to hash the data again, generating a new hash value. The receiver then compares this newly generated hash value with the hash value provided by the sender. If the two hash values ​​match exactly, it confirms that the data has not been tampered with during transmission and is intact. If the hash values ​​do not match, it confirms that the data has been altered during transmission, and the receiver should refuse to receive the data and request the sender to retransmit it.

[0096] In this embodiment of the application, MD5 verification and hash value matching can ensure the integrity and accuracy of data during data transmission.

[0097] In some embodiments, the process of performing consistency checks on structured data through format verification, range verification, and logical verification, and on unstructured data through file comparison, in step S130 above, to obtain the consistency check result may include the following steps:

[0098] Step i) For structured data, perform format validation according to the specified data format definition standard, check whether the data values ​​in the structured data are within the specified range, and check the consistency of the structured data according to the specified business logic to obtain the consistency validation result.

[0099] Step j) For unstructured data, compare whether the file size of the unstructured data is consistent before and after sending. Use a hash algorithm to hash the target file corresponding to the unstructured data, compare whether the hash value of the target file is consistent before and after sending, and compare the metadata information of the target file before and after sending to obtain the consistency verification result.

[0100] As an example, for structured data (such as records in a database), consistency checks typically include the following aspects: format checks, ensuring that the data format conforms to expected standards, such as date formats, number formats, etc.; range checks, checking whether data values ​​are within a reasonable range, such as age should be between 0 and 150; and logic checks, checking the consistency of data according to business logic, such as if a record represents an order, the order amount should not be negative.

[0101] As another example, for unstructured data (such as documents, images, videos, etc.), consistency checks are usually implemented through file comparison: file size comparison, comparing the file size before and after sending; if the size is inconsistent, it may indicate that the file was corrupted during transmission; file hash comparison, using hash algorithms such as MD5 and SHA-256 to hash the file, comparing the hash values ​​before and after sending to ensure that the file content has not been tampered with; file metadata comparison, comparing the file's metadata information, such as creation date, modification date, file type, etc., to ensure that the file's metadata is consistent.

[0102] In some embodiments, step S140 above may include the following steps:

[0103] Step k) For structured data, determine the correspondence between the source data structure of the structured data and the database table structure of the database through data mapping, clean the source data, import the cleaned data into the database using the import tool provided by the database or a custom script, maintain data consistency using transactions during data import, and perform data verification after the data import is completed.

[0104] Step 1): For unstructured data, create a file upload interface that uploads files to a file server via a web interface or API. Use the file upload interface to upload the target file corresponding to the unstructured data to the file server. During the upload process, verify the type of the target file to ensure that target files of the specified allowed file types are uploaded to the file server and perform type-appropriate file processing according to the target file type. Store the target file on the file server through NAS, SAN, or cloud storage services, record the target file's metadata when storing the target file, and set access permissions for the target file so that only authorized users can access the target file.

[0105] For structured data processing, data is imported into the database. Data mapping: Before importing data, it's necessary to determine the correspondence between the source data structure (e.g., CSV files, Excel spreadsheets, etc.) and the database table structure. This includes field mapping and data type conversion. Data cleaning: Before importing data, the source data may need to be cleaned to ensure data quality. This may include removing duplicate records, handling missing values, and correcting erroneous data. Import tools / scripts: Use the database's provided import tools or write custom scripts to import data into the database. For example, use SQL statements to insert data or use ETL (Extract, Transform, Load) tools. Transaction management: Transactions should be used during data import to ensure data consistency. If errors occur during import, transactions can be rolled back to avoid an inconsistent database state. Data validation: After importing, perform data validation, including checking data integrity, accuracy, and consistency. This may involve executing SQL queries, using database constraints (e.g., foreign keys, unique constraints, etc.), and triggers. Backup and recovery: Before importing data, the database should be backed up so that data can be recovered in case of problems during the import process.

[0106] For unstructured data processing, files are uploaded to a file server. File Upload Interface: Develop a file upload interface that allows users to upload files to the file server via a web interface or API. File Type Validation: During the upload process, validate the file type to ensure only allowed file types (such as PDF, JPG, PNG, etc.) can be uploaded. File Size Limit: Set file size limits to prevent the upload of excessively large files, which helps protect server resources. Virus Scan: Scan files for viruses before uploading to ensure they do not contain malicious software. File Storage: Store files on the file server, using NAS (Network Attached Storage), SAN (Storage Area Network), or cloud storage services. Metadata Management: Record file metadata such as filename, upload date, file size, and file type when storing files for management and retrieval. Access Control: Set file access permissions to ensure only authorized users can access and download files. File Processing: Perform appropriate processing based on file type. For example, for image files, generate thumbnails; for PDF files, extract text content for indexing.

[0107] In this embodiment, access control is implemented to manage permissions and prevent data misuse. Furthermore, by recording data operation logs such as metadata of the target file, security auditing is achieved, facilitating the tracing and investigation of security incidents.

[0108] In some embodiments, such as Figure 2 As shown, the method may further include the following steps:

[0109] Step m) Analyze the process of preparing, transmitting, verifying and processing electronic accounting data, obtain the analysis results, and determine the processes that can be automated based on the analysis results;

[0110] Step n), develop automation scripts using multiple programming languages ​​based on the automatable process.

[0111] Automation scripts include data preparation scripts, transmission scripts, verification scripts, processing scripts, error handling scripts, and script scheduling settings;

[0112] The system includes: a data preparation script for automatically extracting data from the source system and preparing the data according to a specified data structure definition standard; a transmission script for automatically transmitting the prepared data to a specified storage medium or to a specified receiving end via a specified network channel; a verification script for automatically verifying the data received by the specified receiving end; a processing script for automatically importing structured data into the database and performing data cleaning operations, and automatically uploading unstructured data to a file server for file processing; an error handling script for automatically recording error information and performing corresponding recovery operations when errors occur during the automation process; and script scheduling settings for using task scheduling tools to execute the automation scripts on a scheduled basis.

[0113] In practical applications, automated scripts can optimize processes. Specifically, they can be developed for the preparation, transmission, verification, and processing of electronic accounting record data, thereby improving efficiency and reducing manual operations. Regarding the security management of electronic accounting record data, it is essential to first establish a data security management system to standardize the transmission and storage processes of electronic accounting record data, ensuring its security and preventing its leakage.

[0114] Specifically, the process begins with a requirements analysis, which analyzes the specific workflow of electronic accounting record data preparation, transmission, verification, and processing to determine which steps can be automated. Next, script development is undertaken, creating automation scripts based on the requirements analysis results. These scripts can be written in various programming languages, such as Python and Shell. Following this, a data preparation script automatically extracts data from the source system and prepares it according to a predetermined format, potentially including data conversion and formatting operations. Then, a transmission script automatically transmits the prepared data to a designated storage medium or through a secure network channel to the receiving end. Finally, script verification is performed, automatically validating the received data, including MD5 checksums and data consistency checks, to ensure data integrity and accuracy.

[0115] In the processing script, for structured data, the data is automatically imported into the database and data cleaning is performed; for unstructured data, it is automatically uploaded to the file server and processed. For error handling, the script should include an error handling mechanism to automatically record error information and take appropriate recovery measures when errors occur during automation. For script scheduling, task scheduling tools (such as cron jobs, Windows Task Scheduler, etc.) are used to execute the automated scripts on a scheduled basis, achieving timed data preparation, transmission, and verification.

[0116] As an optional implementation method, establish an electronic accounting record data security management system. This includes: Policy formulation: Developing clear electronic accounting record data security policies, including data classification, access permissions, data backup, and data recovery. Process standardization: Establishing standard operating procedures for the transmission and storage of electronic accounting record data, ensuring clear guidance and supervision for all operations. Access control: Implementing strict access control to ensure only authorized personnel can access and process electronic accounting record data. Encryption measures: Encrypting the storage and transmission of sensitive data using strong encryption algorithms and properly managing keys. Monitoring and auditing: Establishing monitoring and auditing mechanisms to record all operations on electronic accounting record data for tracing in the event of a security incident. Employee training: Regularly providing data security awareness training to employees to improve their understanding of data security. Backup and recovery: Regularly backing up electronic accounting record data and ensuring the security of backup data, while regularly testing data recovery processes to ensure rapid recovery in the event of data loss or corruption. Physical security: Ensuring the physical security of data storage media to prevent unauthorized physical access. By developing automated scripts and establishing an electronic accounting record data security management system, data processing efficiency can be improved, human error reduced, and data security ensured throughout its entire lifecycle. By standardizing the management of electronic accounting records, we can improve the transparency and traceability of data management.

[0117] In this embodiment, data processing efficiency is enhanced and reduced labor costs are achieved through automated data processing workflows. Furthermore, optimizations focusing on automation and security management improve data transmission efficiency and security.

[0118] Figure 3 A schematic diagram of an electronic accounting record data processing device is provided. Figure 3 As shown, the electronic accounting record data processing device 300 includes:

[0119] The acquisition module 301 is used to acquire the original electronic accounting archive data from the source system; wherein, the structured data in the electronic accounting archive data is acquired by calling the API interface, the structured data is converted into a standard format according to the specified data structure definition standard, and a data dictionary is generated based on the structured data to record the meaning and type of the fields; the unstructured data in the electronic accounting archive data is compressed using a compression algorithm, and an MD5 file digest is generated based on the unstructured data;

[0120] Transmission module 302 is used to encrypt the electronic accounting file data using a symmetric encryption algorithm or an asymmetric encryption algorithm and transmit it to a designated receiving end;

[0121] The verification module 303 is used to perform MD5 verification on the electronic accounting file data through the designated receiving end to obtain the MD5 verification result. If the MD5 verification result is successful, the structured data is verified for consistency through format verification, range verification and logical verification, and the unstructured data is verified for consistency through file comparison to obtain the consistency verification result.

[0122] The processing module 304 is used to import the structured data into the database using the import tool or custom script provided by the database if the consistency verification result is successful, upload the target file corresponding to the unstructured data to the file server through a web interface or API, and store the target file on the file server through NAS, SAN or cloud storage services.

[0123] The electronic accounting record data processing device provided in this application embodiment has the same technical features as the electronic accounting record data processing method provided in the above embodiment, so it can also solve the same technical problems and achieve the same technical effects.

[0124] An electronic device provided in this application embodiment, such as Figure 4 As shown, the electronic device 400 includes a processor 402 and a memory 401. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the steps of the method provided in the above embodiments.

[0125] See Figure 4 The electronic device also includes a bus 403 and a communication interface 404. The processor 402, the communication interface 404 and the memory 401 are connected via the bus 403. The processor 402 is used to execute executable modules, such as computer programs, stored in the memory 401.

[0126] The memory 401 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 404 (which can be wired or wireless), such as the Internet, wide area network, local area network, or metropolitan area network.

[0127] Bus 403 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0128] The memory 401 is used to store programs. After receiving an execution instruction, the processor 402 executes the program. The method executed by the apparatus defined by the process disclosed in any of the preceding embodiments of this application can be applied to the processor 402 or implemented by the processor 402.

[0129] Processor 402 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 402 or by instructions in software form. The processor 402 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 401, and processor 402 reads the information from memory 401 and, in conjunction with its hardware, completes the steps of the above method.

[0130] Corresponding to the above-described method for processing electronic accounting record data, this application embodiment also provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are invoked and executed by a processor, the computer-executable instructions cause the processor to perform the steps of the above-described method for processing electronic accounting record data.

[0131] The electronic accounting record data processing device provided in this application embodiment can be specific hardware on a device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in this application embodiment are the same as those in the foregoing method embodiments. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the foregoing method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the above method embodiments, and will not be repeated here.

[0132] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0133] For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0134] 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.

[0135] In addition, the functional units in the embodiments provided in this application 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.

[0136] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the electronic accounting archive data processing method described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0137] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0138] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for processing electronic accounting record data, characterized in that, The method includes: The system obtains raw electronic accounting record data from the source system; wherein, the structured data in the electronic accounting record data is obtained by calling the API interface, the structured data is converted into a standard format according to the specified data structure definition standard, and a data dictionary is generated based on the structured data to record the meaning and type of the fields; the unstructured data in the electronic accounting record data is compressed using a compression algorithm, and an MD5 file digest is generated based on the unstructured data. The electronic accounting record data is encrypted using a symmetric encryption algorithm or an asymmetric encryption algorithm and then transmitted to the designated receiving end. The electronic accounting record data is subjected to MD5 verification by the designated receiving end to obtain the MD5 verification result. If the MD5 verification result is successful, the structured data is subjected to consistency verification by means of format verification, range verification and logical verification, and the unstructured data is subjected to consistency verification by means of file comparison to obtain the consistency verification result. If the consistency verification result is successful, the structured data is imported into the database using the database import tool or a custom script. The target file corresponding to the unstructured data is uploaded to the file server via a web interface or API, and the target file is stored on the file server via NAS, SAN, or cloud storage services.

2. The method according to claim 1, characterized in that, The step of obtaining the original electronic accounting record data from the source system includes: For the structured data in the electronic accounting archive data, the original structured data is obtained from the source system by calling the API interface, the structured data is converted into a standard format according to the specified archive data structure definition standard, and a data dictionary is generated based on the structured data, recording the meaning and data type of the data fields; For the unstructured data in the electronic accounting archive data, a compression algorithm is used to compress the data to obtain a compressed file, and an MD5 file digest is generated based on the compressed file; wherein, the MD5 file digest is used to verify the integrity of the compressed file.

3. The method according to claim 1, characterized in that, The step of encrypting the electronic accounting record data using a symmetric encryption algorithm or an asymmetric encryption algorithm and transmitting it to the designated receiving end includes: The electronic accounting record data is encrypted using an encryption program through a symmetric encryption algorithm or an asymmetric encryption algorithm to obtain encrypted electronic accounting record data; The encrypted electronic accounting record data is transmitted through a designated physical storage medium with anti-interference capabilities and write protection, and the transmission result is determined. The integrity of the electronic accounting record data in the transmission result is verified using a hash function or Message Authentication Code (MAC).

4. The method according to claim 1, characterized in that, The step of performing MD5 verification on the electronic accounting record data through the designated receiving end to obtain the MD5 verification result includes: The electronic accounting record data is subjected to MD5 verification by the designated receiving end to obtain the hash value matching result. If the hash value matching result is a complete hash value match, it is determined that the electronic accounting record data has not been tampered with during transmission; If the hash value matching result is a hash value mismatch, it is determined that the electronic accounting record data has changed during transmission, and a signal of refusal to receive is sent through the designated receiving end so that the sender can retransmit the electronic accounting record data.

5. The method according to claim 1, characterized in that, The steps of performing consistency checks on the structured data through format verification, range verification, and logical verification, and performing consistency checks on the unstructured data through file comparison, to obtain the consistency check results, include: For the structured data, format validation is performed according to the specified data format definition standard to check whether the data values ​​in the structured data are within the specified range, and the consistency of the structured data is checked according to the specified business logic to obtain the consistency validation result. For the unstructured data, compare whether the file size of the unstructured data is consistent before and after transmission. Use a hash algorithm to hash the target file corresponding to the unstructured data, compare whether the hash value of the target file is consistent before and after transmission, and compare the metadata information of the target file before and after transmission to obtain the consistency verification result.

6. The method according to claim 1, characterized in that, The steps of importing the structured data into the database using the database's import tool or custom script, uploading the target file corresponding to the unstructured data to the file server via a web interface or API, and storing the target file on the file server via NAS, SAN, or cloud storage services include: For the structured data, the correspondence between the source data structure and the database table structure of the structured data is determined by data mapping. The source data is cleaned, and the cleaned data is imported into the database using the import tool provided by the database or a custom script. Transactions are used to maintain data consistency during data import, and data verification is performed after the data import is completed. For the unstructured data, a file upload interface is created that allows uploading files to a file server via a web interface or API. This interface is used to upload the target file corresponding to the unstructured data to the file server. During the upload process, the type of the target file is verified to ensure that target files of specified allowed file types are uploaded to the file server. Appropriate file processing is then performed based on the target file type. The target file is stored on the file server using NAS, SAN, or cloud storage services. Metadata of the target file is recorded during storage, and access permissions are set to ensure that only authorized users can access the target file.

7. The method according to claim 1, characterized in that, Also includes: The process of preparing, transmitting, verifying, and processing the electronic accounting record data is analyzed to obtain analysis results, and the processes that can be automated are determined based on the analysis results. Automated scripts can be developed using various programming languages ​​based on the described automatable process; The automation scripts include data preparation scripts, transmission scripts, verification scripts, processing scripts, error handling scripts, and script scheduling settings; The data preparation script is used to automatically extract data from the source system and prepare the data according to the specified data structure definition standard. The transmission script is used to automatically transmit the prepared data to a specified storage medium or to a specified receiving end through a specified network channel; the verification script is used to automatically verify the data received by the specified receiving end; the processing script is used to automatically import the structured data into the database and perform data cleaning operations, and automatically upload the unstructured data to the file server and perform file processing; the error handling is used to automatically record error information and perform corresponding recovery operations when errors occur during the automation process; the script scheduling settings are used to execute the automation script at regular intervals using a task scheduling tool.

8. A device for processing electronic accounting record data, characterized in that, include: The acquisition module is used to acquire raw electronic accounting archive data from the source system. The structured data in the electronic accounting archive data is acquired by calling an API interface, converted into a standard format according to a specified data structure definition standard, and a data dictionary is generated based on the structured data to record the meaning and type of fields. The unstructured data in the electronic accounting archive data is compressed using a compression algorithm, and an MD5 file digest is generated based on the unstructured data. The transmission module is used to encrypt the electronic accounting file data using a symmetric encryption algorithm or an asymmetric encryption algorithm and transmit it to a designated receiving end; The verification module is used to perform MD5 verification on the electronic accounting file data through the designated receiving end to obtain the MD5 verification result. If the MD5 verification result is successful, the structured data is verified for consistency through format verification, range verification and logical verification, and the unstructured data is verified for consistency through file comparison to obtain the consistency verification result. The processing module is used to import the structured data into the database using the database's import tool or a custom script if the consistency verification result is successful, upload the target file corresponding to the unstructured data to the file server through a web interface or API, and store the target file on the file server through NAS, SAN, or cloud storage services.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when invoked and executed by a processor, cause the processor to perform the method according to any one of claims 1 to 7.

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