Method, device, equipment, medium and product for updating data classification grading standard

Abstract

The application relates to a data classification and grading standard updating method and device, equipment, medium and product, in particular to the technical field of data retrieval. The application comprises the following steps: monitoring business data and policy and regulation files in real time; analyzing the business data according to an initial classification and grading standard to obtain an analysis result; performing a preset analysis operation on the policy and regulation files, and combining the analysis result to calculate an evaluation index of the initial classification and grading standard; and adjusting the initial classification and grading standard according to the analysis result and the evaluation index. The embodiments of the application are used for solving the problem that a static data classification and grading standard has poor adaptability.

Description

Technical Field

[0001] This application relates to the field of data classification and grading technology, and in particular to a method, apparatus, equipment, medium and product for updating data classification and grading standards. Background Technology

[0002] Data classification and grading is a fundamental and crucial task in the field of data element governance. It refers to dividing data into different categories and levels based on factors such as its nature, importance, and sensitivity. This process is similar to classifying and organizing books in a library, aiming to improve data manageability, security, and utilization efficiency.

[0003] Traditional methods often employ static data classification and grading standards. However, a company's business and data situation change over time, such as launching new products, entering new markets, or adopting new technologies. For example, when a company begins to expand into overseas markets and involves cross-border data transfers, it may need to reassess the sensitivity and classification level of certain data to comply with the laws and regulations of different countries and regions. Static data classification and grading standards lack mechanisms for continuous improvement and iteration, making them difficult to adapt to rapidly changing data environments, business needs, and regulatory environments. Summary of the Invention

[0004] To solve the above-mentioned technical problems, or at least partially solve them, this application provides a method, apparatus, device, medium, and product for updating data classification and grading standards.

[0005] In a first aspect, this application provides a method for updating data classification and grading standards. The method includes: real-time monitoring of business data and policy and regulatory documents; analyzing the business data according to the initial classification and grading standards to obtain analysis results; performing preset analysis operations on the policy and regulatory documents and calculating the evaluation indicators of the initial classification and grading standards based on the analysis results; and adjusting the initial classification and grading standards based on the analysis results and evaluation indicators.

[0006] As an optional implementation method provided in this application, real-time monitoring of business data and policy and regulatory documents includes: calling the Flink monitoring system to monitor business data; and using web crawling technology to crawl policy and regulatory documents from relevant websites corresponding to the business data.

[0007] As an optional implementation method provided in this application, after real-time monitoring of business data and policy and regulatory documents, and before performing preset analysis operations on the policy and regulatory documents and calculating the evaluation indicators of the initial classification and grading standards based on the analysis results, the method further includes: extracting key information from the policy and regulatory documents, the key information including at least one of document attributes, document content, release time, effective time, and implementation status; determining the amount of change in the policy and regulatory documents based on the key information; and issuing an alarm when the amount of change in the policy and regulatory documents meets the triggering conditions; wherein the triggering conditions include at least one of the following: the number of policy and regulatory documents increases beyond a preset number threshold; the document attributes of the policy and regulatory documents change; or the document content of the policy and regulatory documents changes.

[0008] As an optional implementation method provided in this application, business data is analyzed according to the initial classification and grading standards to obtain analysis results, including: calculating the data volume or growth rate of business data to analyze the growth trend of business data volume; parsing classified business data to analyze the attribute changes of business data; monitoring the operation logs of business data, and statistically analyzing the access frequency, access duration and access users of business data to analyze the usage of business data; and detecting the data sensitivity and potential risks of business data.

[0009] As an optional implementation method provided in this application, the preset analysis operations include: correlation analysis, relevance analysis, and time series analysis; the evaluation indicators of the initial classification and grading standards include: compliance indicators, used to evaluate the compliance of the initial classification and grading standards in classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards in classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards in classifying business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; relevance indicators, used to evaluate the relevance between the data sensitivity of policy and regulatory documents and business data; periodic indicators, used to evaluate the update frequency of policy and regulatory documents; trend indicators, used to evaluate the strictness of policy and regulatory documents; and a comprehensive indicator calculated by combining the above indicators using a multi-criteria decision analysis strategy.

[0010] As an optional implementation method provided in this application, the initial classification and grading standards are adjusted based on the analysis results and evaluation indicators, including: adjusting the data categories and levels; and / or, reclassifying data sensitivity.

[0011] Secondly, this application provides a data classification and grading standard updating device, the device comprising:

[0012] The real-time monitoring module is used to monitor business data and policy and regulatory documents in real time.

[0013] The analysis module is used to analyze the business data according to the initial classification and grading standards to obtain analysis results;

[0014] The evaluation index calculation module is used to perform preset analysis operations on policy and regulatory documents and calculate the evaluation index of the initial classification and grading standard based on the analysis results.

[0015] The adjustment module is used to adjust the initial classification and grading standards based on the analysis results and the evaluation indicators.

[0016] As an optional implementation method provided in this application, the real-time monitoring module is specifically used to: call the Flink monitoring system to monitor business data; and use web crawling technology to crawl policy and regulatory documents from relevant websites corresponding to the business data.

[0017] As an optional implementation method provided in this application, the real-time monitoring module is further configured to: extract key information from policy and regulatory documents, the key information including at least one of document attributes, document content, publication time, effective time, and implementation status; determine the amount of change in policy and regulatory documents based on the key information; and issue an alarm when the amount of change in policy and regulatory documents meets the triggering conditions; wherein the triggering conditions include at least one of the following: the number of policy and regulatory documents increases beyond a preset threshold; the document attributes of policy and regulatory documents change; or the document content of policy and regulatory documents change.

[0018] As an optional implementation method provided in this application, the analysis module is specifically used for: calculating the size or growth rate of business data to analyze the growth trend of business data; parsing and classifying business data to analyze the attribute changes of business data; monitoring the operation logs of business data, and statistically analyzing the access frequency, access duration and access users of business data to analyze the usage of business data; and detecting the data sensitivity and potential risks of business data.

[0019] As an optional implementation method provided in this application, the preset analysis operations include: correlation analysis, relevance analysis, and time series analysis; the evaluation indicators of the initial classification and grading standards include: compliance indicators, used to evaluate the compliance of the initial classification and grading standards in classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards in classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards in classifying business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; relevance indicators, used to evaluate the relevance between the data sensitivity of policy and regulatory documents and business data; periodic indicators, used to evaluate the update frequency of policy and regulatory documents; trend indicators, used to evaluate the strictness of policy and regulatory documents; and a comprehensive indicator calculated by combining the above indicators using a multi-criteria decision analysis strategy.

[0020] As an optional implementation method provided in this application, the adjustment module is specifically used for: adjusting data categories and levels; and / or, reclassifying data sensitivity.

[0021] Thirdly, this application provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, it implements the data classification and grading standard update method as described in the first aspect or any of its optional embodiments.

[0022] Fourthly, this application provides a computer-readable storage medium, comprising: storing a computer program on the computer-readable storage medium, wherein when the computer program is executed by a processor, it implements a method for updating a data classification and grading standard as described in the first aspect or any of its optional embodiments.

[0023] Fifthly, this application provides a computer program product, comprising: the computer program product including a computer program that, when the computer program is run on a computer, causes the computer to implement the data classification and grading standard update method as described in the first aspect or any of its optional embodiments.

[0024] The technical solution provided in this application has the following advantages compared with the prior art:

[0025] This disclosure provides a method for updating data classification and grading standards. It involves real-time monitoring of business data and policy / regulatory documents. First, the business data is analyzed according to an initial classification and grading standard to obtain analysis results. Then, preset analysis operations are performed on the policy / regulatory documents, and evaluation indicators for the initial classification and grading standards are calculated based on the analysis results. Finally, the initial classification and grading standards are adjusted according to the analysis results and the evaluation indicators. In this way, this application adapts to changes in business needs and policy / regulatory documents, dynamically updating and adjusting the classification and grading standards for business data, ensuring the compliance of the data classification and grading standards, and improving the efficiency and accuracy of data classification and grading work. Attached Figure Description

[0026] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0027] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 A flowchart illustrating a method for updating data classification and grading standards provided in this application embodiment;

[0029] Figure 2 A schematic diagram of a data classification and grading standard update device provided in this application embodiment;

[0030] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0031] To better understand the above-mentioned objectives, features, and advantages of this application, the solution of this application will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0032] Many specific details are set forth in the following description in order to provide a full understanding of this application, but this application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of this application, and not all embodiments.

[0033] Data classification and grading play a crucial role in data element governance. It not only improves data manageability and security but also enhances data value, providing strong support for enterprises' digital transformation and sustainable development. Traditional methods often employ static data classification and grading standards. When developing these standards, there may be a lack of timely understanding and compliance with the latest regulations, and these standards are rarely updated or adjusted after their initial formulation. The lack of a mechanism for continuous improvement and iteration makes it difficult for data classification and grading standards to adapt to rapidly changing data environments, business needs, and regulatory environments.

[0034] To address some or all of the technical problems existing in related technologies, embodiments of this application provide a method, apparatus, device, medium, and product for updating data classification and grading standards. The method monitors business data and policy and regulatory documents in real time. First, it analyzes the business data according to an initial classification and grading standard to obtain analysis results. Then, it performs preset analysis operations on the policy and regulatory documents and calculates the evaluation indicators of the initial classification and grading standard based on the analysis results. Finally, it adjusts the initial classification and grading standard based on the analysis results and the evaluation indicators. Thus, this application adapts to changes in business needs and policy and regulatory documents, dynamically updating and adjusting the classification and grading standards for business data, ensuring the compliance of the data classification and grading standards, and improving the efficiency and accuracy of data classification and grading work.

[0035] This application provides a method for updating a data classification and grading standard, which can be implemented using a data classification and grading standard updating device or electronic device. Electronic devices include, but are not limited to, vehicle-mounted terminals, servers, personal computers, laptops, tablets, and smartphones. The operating system of the electronic device can include Android, Apple's iOS, Microsoft's Windows operating system, etc., and this application does not limit this. The electronic device can operate independently to implement this application, or it can connect to a network and implement this application through interactive operation with other computer devices on the network. The network where the electronic device is located includes, but is not limited to, the Internet, wide area networks, metropolitan area networks, local area networks, and virtual private networks (VPNs).

[0036] It should be noted that the scope of protection of the data classification and grading standard update method described in this application embodiment is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting or replacing steps in the prior art based on the principles of this application is included within the scope of protection of this application.

[0037] like Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for updating a data classification and grading standard according to an embodiment of this application. This method can be executed by a data classification and grading standard updating device, which can be implemented in software and / or hardware, and is generally integrated into an electronic device. Figure 1 As shown, the method mainly includes the following steps S101 to S104:

[0038] S101. Real-time monitoring of business data and policy and regulatory documents.

[0039] Business data refers to business-related data generated during a company's operations, serving as a crucial basis for decision-making and operations. Business data typically includes user information, transaction records, and product usage data. User information includes user ID, name, contact information, and registration time. Transaction records include transaction ID, transaction time, transaction amount, and traded goods. Product usage data includes product ID, user feedback, usage frequency, and fault records.

[0040] Policy and regulatory documents, including policy documents, legal documents, industry standard documents, technical specification documents, and security standard documents, are in text form. Different industries have different legal and regulatory requirements. For example, the financial industry is bound by the Basel Accords, while the healthcare industry is governed by medical data protection regulations, such as the Health Insurance Portability and Accountability Act (HIPAA). Companies need to identify this regulated data, such as customer transaction records of financial institutions and patient medical records of medical institutions. This data is usually of high importance and sensitivity and must be strictly classified and protected in accordance with regulatory requirements.

[0041] In some embodiments, step S101 can be executed by invoking a real-time monitoring system, which can be Flink. Flink, as a highly available and high-performance distributed computing engine centered on streaming, features integrated streaming and batch processing, high throughput, low latency, and fault tolerance, making it ideal for handling large-scale and complex computing tasks. Through Flink, we can monitor in real time changes in the volume of business data, changes in data attributes, data access and usage, as well as updates to relevant laws, regulations, and industry standards.

[0042] In some embodiments, when monitoring policy and regulatory documents in real time, web crawling technology can be used to crawl policy and regulatory documents from websites related to the business data. Afterwards, key information is extracted from the policy and regulatory documents, and this key information can be stored in a database along with the corresponding policy and regulatory documents. Based on the extracted key information, the changes in policy and regulatory documents are monitored. The key information includes at least one of the following: document attributes, document content, publication time, effective time, and implementation status. An alarm is issued when the changes in policy and regulatory documents meet at least one of the following triggering conditions: the number of policy and regulatory documents exceeds a preset threshold, the document attributes of the policy and regulatory documents change, or the document content of the policy and regulatory documents changes. It should be noted that the setting of the triggering conditions needs to be adjusted and optimized according to specific business needs and monitoring objectives; this application does not impose specific limitations on them.

[0043] The above embodiments closely monitor changes in the regulatory environment, promptly incorporating the latest regulatory requirements into the data classification and grading standards to ensure compliance. An alert is issued immediately upon detecting changes in policy and regulatory documents that meet any triggering condition, significantly shortening the time interval between policy and regulatory changes and their discovery, enabling relevant personnel to respond quickly and take action. Alerts based on pre-set, reasonable, and scientific triggering conditions reduce false alarms and missed alarms. The entire process requires no continuous manual observation or judgment; the system automatically monitors whether changes in policy and regulatory documents meet the triggering conditions and issues alerts. When an alert is triggered, the changes in policy and regulatory documents are simultaneously recorded, providing relevant personnel with information to quickly understand the changes.

[0044] S102. Analyze the business data according to the initial classification and grading standards to obtain the analysis results.

[0045] In some embodiments, a preprocessing step is included before performing step S102. Specifically, preprocessing operations such as cleaning, deduplication, and format conversion are performed on the business data. The preprocessing step ensures the accuracy and consistency of the business data.

[0046] In some embodiments, step S102 includes: calculating the size or growth rate of the business data to analyze the growth trend of the business data; parsing and classifying the business data to analyze the attribute changes of the business data; monitoring the operation logs of the business data and counting the access frequency, access duration and access users of the business data to analyze the usage of the business data; and detecting data sensitivity and potential risks.

[0047] In some embodiments, when analyzing business data according to the initial classification and grading standards, the implementation monitoring system is invoked to analyze the business data according to the initial classification and grading standards. Optionally, Flink can be used to record or calculate the data volume (e.g., MB, GB) or data growth rate in real time to analyze the growth trend of business data volume. For example, if a rapid growth trend in business data is found during the analysis of business volume data, a business data volume trend chart can be drawn to clearly show the growth rate and fluctuation of business data volume. If anomalies occur, it indicates that the business may have risks and its data classification and grading settings need to be adjusted.

[0048] Flink is used to parse categorized business data to analyze changes in its attributes. These attributes include nominal attributes, binary attributes, ordinal attributes, and numerical attributes. Nominal attributes include user status (active, inactive). Binary attributes include whether a user has purchased a product (yes / no). Ordinal attributes include user satisfaction levels (very satisfied, satisfied, neutral, dissatisfied, very dissatisfied). Numerical attributes include user age and transaction amount.

[0049] By monitoring the operation logs of business data through Flink, we can statistically analyze the access frequency, access duration, and accessing users of business data to understand how the data is used. This usage includes operations such as reading, writing, and querying of business data.

[0050] Optionally, when detecting potential risks in business data, it can be done in any of the following ways: Determine the fields each data record should contain using a data dictionary and business rules, then write scripts or use data quality tools to scan for missing values ​​in the dataset; use data reconciliation tools or write SQL queries to compare the consistency of the same business data across different data sources and identify inconsistent data records; observe the trend of business data over time to discover potential risks; calculate ratios between different business indicators (such as gross profit margin, inventory turnover rate, solvency ratio, etc.) and compare them with industry standards or the company's own target values ​​to determine if potential risks exist; use statistical software or data analysis tools to calculate correlation coefficients between data, determine the strength and direction of correlation between variables, and then identify combinations of factors that may influence each other and lead to risks; use association rule mining algorithms to discover frequent itemsets and association rules in the data to reveal potential risk associations; or collect historical business data, including various factors related to risk events (such as customer credit scores, project budget overruns, etc.) as independent variables, and the occurrence of risk events as the dependent variable, to construct a logistic regression model. After training and validation, the model can predict the probability of risk events occurring based on new business data inputs.

[0051] The above analysis of business data according to the initial classification and grading standards yields the analysis results, enabling in-depth analysis and effective utilization of business data.

[0052] S103. Perform a preset analysis on policy and regulatory documents, and calculate the evaluation indicators for the initial classification and grading standards based on the analysis results.

[0053] The preset analysis operations include association analysis, correlation analysis, and time series analysis. Association analysis includes, but is not limited to, association rule mining and cluster analysis.

[0054] The initial classification and grading standards' evaluation indicators include: compliance indicators, adaptability indicators, security indicators, relevance indicators, correlation indicators, periodicity indicators, trend indicators, and comprehensive indicators. Among these, compliance indicators evaluate the compliance of the initial classification and grading standards in classifying business data; adaptability indicators evaluate the adaptability of the initial classification and grading standards in classifying business data; security indicators evaluate the security of the initial classification and grading standards in classifying business data; relevance indicators evaluate the relevance between policy and regulatory documents and business data; correlation indicators evaluate the correlation between the sensitivity of policy and regulatory documents and business data; and periodicity and trend indicators evaluate the update frequency and stringency of policy and regulatory documents. The comprehensive indicator is calculated by combining the above indicators using a multi-criteria decision analysis strategy.

[0055] The comprehensive indicators can evaluate at least one of the following: the accuracy of the initial classification and grading standards in reflecting the sensitivity of business data; the risk of leakage of business data by the initial classification and grading standards; the coverage of business needs by the initial classification and grading standards; the adaptability of the initial classification and grading standards to business scenarios; the adaptability of the initial classification and grading standards to changes in policies and regulations; and the adaptability of the initial classification and grading standards to regulatory requirements.

[0056] In some embodiments, compliance and adaptability indicators of the initial classification criteria are calculated, and security indicators of the initial grading criteria are calculated. The initial classification criteria divide business data into categories and identify the sensitivity of business data. The initial grading criteria classify business data into levels.

[0057] When calculating compliance metrics for the initial classification criteria, data classification tools are used to identify and label business data, and compliance verification software is applied to calculate these metrics to verify the compliance of the initial classification criteria. The data classification tool can be IBM InfoSphere Guardium Data Classification, used to identify, classify, and protect sensitive data. The compliance verification software can be RSA Archer Governance, Risk, and Compliance Platform (RSA Archer GRC), used to manage and monitor risk, compliance, and corporate governance.

[0058] When calculating the fitness index of the initial classification criteria, data analysis and visualization tools are used to analyze the growth trends and attribute changes of business data to determine whether the initial classification criteria are suitable for these trends and changes, thus obtaining the fitness index of the initial classification criteria. Data analysis and visualization tools can include Power BI (Microsoft Power BI) and Tableau. Microsoft Power BI is a suite of business analytics tools—a collection of interoperable software services, applications, and connectors—that transforms disparate data sources into interactive insights with a continuous, immersive visual experience. Tableau is a simple desktop business intelligence tool that helps users quickly analyze, visualize, and share information to support business decisions. With Tableau, users can easily extract, analyze, and visualize data from various data sources, generating easy-to-understand charts, graphs, maps, dashboards, and stories.

[0059] Alternatively, when calculating the fitness index of the initial classification criteria, machine learning algorithms can be used to identify patterns and characteristics of business data, and fitness index of the initial classification criteria can be calculated based on the patterns and characteristics of business data, thereby evaluating the fitness of the initial classification criteria.

[0060] When calculating the security indicators for the initial grading criteria, risk assessment tools are used to quantify the sensitivity and potential risks of the monitored business data to calculate the security indicators for the initial grading criteria. This assesses the security of the initial grading criteria. Risk assessment tools can include risk assessment matrices, RSA Archer GRC, etc. A risk assessment matrix is ​​a tool used to classify and assess risks according to their probability and impact. It typically consists of two dimensions: a probability dimension representing the likelihood of a risk event occurring, and an impact dimension representing the potential impact of the risk event on an organization or project. By dividing these two dimensions into different levels or ranges, a risk assessment matrix can be constructed, allowing for a visual comparison and ranking of different risks.

[0061] In some embodiments, during the pre-defined analysis of policy and regulatory documents, correlation indicators between business data and policy and regulatory documents are calculated through association rule mining and cluster analysis to discover potential business patterns and the impact of policies and regulations. Correlation analysis is performed by calculating correlation coefficients between different policies and regulations to calculate the correlation indicator between the sensitivity of policies and regulations and business data, analyzing the correlation between policies and regulations and data sensitivity. Periodic and trend indicators of policies and regulations are calculated by analyzing the changing trends of policy and regulatory documents over time. If the trend indicates that policies and regulations are becoming increasingly stringent, the sensitivity of the corresponding business data is also increasing.

[0062] In some embodiments, various evaluation results are comprehensively considered based on the above embodiments. Optionally, a multi-criteria decision analysis (MCDA) strategy is used to comprehensively calculate multiple evaluation indicators. MCDA is a decision-aiding method that considers multiple criteria (or standards, attributes) to evaluate and compare different alternatives.

[0063] An optional implementation of the above embodiments includes: first, obtaining the preset weights of each evaluation indicator, and calculating a comprehensive indicator based on the evaluation indicator and its corresponding preset weight. Then, considering multiple evaluation criteria, assigning preset weights to each evaluation criterion, scoring and ranking them to obtain the comprehensive indicator. By comprehensively considering multiple evaluation indicators through a multi-criteria decision analysis method, the evaluation results become more scientific and reasonable.

[0064] By analyzing and evaluating business data and policy and regulatory documents, we can promptly understand data trends and potential risks, thereby providing a scientific basis for adjusting and optimizing data classification and grading standards, and ensuring the compliance, security, and effectiveness of data classification and grading.

[0065] S104. Based on the analysis results and evaluation indicators, adjust the initial classification and grading standards.

[0066] The analysis results include: the scale, growth trend, attribute changes, usage, data sensitivity, and potential risks of business data.

[0067] In some embodiments, adjusting the initial classification and grading criteria includes: adjusting data categories and levels; and / or, reclassifying data sensitivity. Optionally, automated classification software is applied to readjust data categories; risk assessment software is applied to reclassify data sensitivity, so that business data is automatically categorized into the appropriate category or level.

[0068] For example, if a new data category or attribute is added, it will be promptly incorporated into the classification system; if a data category or attribute is no longer applicable, it will be removed or merged. User names, ID card numbers, and mobile phone numbers are classified as highly sensitive data; home addresses and shopping records are classified as moderately sensitive data; and publicly available information is classified as low-sensitivity data. This allows for strengthened security measures for highly sensitive data and more relaxed usage restrictions for low-sensitivity data.

[0069] In some embodiments, when adjusting the initial classification and grading criteria, project management software is used to track and manage the implementation progress and effects of the adjustment measures, thereby ensuring the effective execution of the adjustment measures. The project management software may be Microsoft Project (MS Project), a project management software developed by Microsoft Corporation that assists project managers in developing plans, allocating resources, tracking progress, managing budgets, and analyzing workloads.

[0070] In some embodiments, after adjusting the initial classification and grading standards, the new standards can be submitted to relevant departments and experts for review, feedback can be collected, and the data classification and grading standards can be further revised and improved. Once revised and improved, the data classification and grading standards can be released and implemented, which helps improve the compliance, security, and effectiveness of data management, providing strong support for enterprise data governance and decision support.

[0071] After review and revision, the revised data classification and grading standards were officially released, and relevant personnel were trained and implemented. Training on the data classification and grading standards was conducted to improve the data awareness and compliance awareness of relevant personnel. Through training, it was ensured that relevant personnel could accurately understand and implement the new standards. The data classification and grading standards were promoted and publicized through internal announcements, brochures, and other means. This aimed to increase the importance that all employees attach to data management and foster a positive data management environment.

[0072] In summary, this application provides a method for updating data classification and grading standards. This method monitors business data and policy / regulatory documents in real time. First, it analyzes the business data according to an initial classification and grading standard to obtain analysis results. Then, it performs preset analysis operations on the policy / regulatory documents and calculates the evaluation indicators of the initial classification and grading standard based on the analysis results. Finally, it adjusts the initial classification and grading standard based on the analysis results and the evaluation indicators. Thus, this application adapts to changes in business needs and policy / regulatory documents, dynamically updating and adjusting the classification and grading standards for business data, ensuring the compliance of the data classification and grading standards, and improving the efficiency and accuracy of data classification and grading work.

[0073] like Figure 2 As shown, Figure 2 A schematic diagram of a data classification and grading standard update device provided in this application embodiment, the device comprising:

[0074] Real-time monitoring module 201 is used for real-time monitoring of business data and policy and regulatory documents;

[0075] Analysis module 202 is used to analyze the business data according to the initial classification and grading standards to obtain analysis results;

[0076] The evaluation index calculation module 203 is used to perform preset analysis operations on policy and regulatory documents and calculate the evaluation index of the initial classification and grading standard based on the analysis results.

[0077] The adjustment module 204 is used to adjust the initial classification and grading standards based on the analysis results and the evaluation indicators.

[0078] As an optional implementation method provided in this application, the real-time monitoring module 201 is specifically used to: call the implementation monitoring system Flink to monitor business data; and use web crawling technology to crawl policy and regulatory documents from relevant websites corresponding to the business data.

[0079] As an optional implementation method provided in this application, the real-time monitoring module 201 is further configured to: extract key information from policy and regulatory documents, the key information including at least one of document attributes, document content, release time, effective time, and implementation status; determine the amount of change in policy and regulatory documents based on the key information; and issue an alarm when the amount of change in policy and regulatory documents meets the triggering conditions; wherein the triggering conditions include at least one of the following: the number of policy and regulatory documents increases beyond a preset threshold; the document attributes of policy and regulatory documents change; or the document content of policy and regulatory documents changes.

[0080] As an optional implementation provided in this application, the analysis module 202 is specifically used for: calculating the size or growth rate of business data to analyze the growth trend of business data; parsing and classifying business data to analyze the attribute changes of business data; monitoring the operation logs of business data, and statistically analyzing the access frequency, access duration and access users of business data to analyze the usage of business data; and detecting the data sensitivity and potential risks of business data.

[0081] As an optional implementation method provided in this application, the preset analysis operations include: correlation analysis, relevance analysis, and time series analysis; the evaluation indicators of the initial classification and grading standards include: compliance indicators, used to evaluate the compliance of the initial classification and grading standards in classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards in classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards in classifying business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; relevance indicators, used to evaluate the relevance between the data sensitivity of policy and regulatory documents and business data; periodic indicators, used to evaluate the update frequency of policy and regulatory documents; trend indicators, used to evaluate the strictness of policy and regulatory documents; and a comprehensive indicator calculated by combining the above indicators using a multi-criteria decision analysis strategy.

[0082] As an optional implementation of this application, the adjustment module 204 is specifically used for: adjusting data categories and levels; and / or, reclassifying data sensitivity.

[0083] Specific limitations regarding the data classification and grading standard update device can be found in the above description of the update method for data classification and grading standards, and will not be repeated here. Each module in the aforementioned data classification and grading standard update device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0084] In one embodiment, this application provides an electronic device, which may be a terminal, and its internal structure diagram may be as follows. Figure 3 As shown, the electronic device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for updating a data classification and grading standard. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0085] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. Specifically, the electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0086] In one embodiment, the data classification and grading standard updating device provided in this application can be implemented as a computer program, which can be implemented as follows: Figure 3 The electronic device shown operates on this device. The memory of the electronic device can store the various program modules that make up the updating device for this data classification and grading standard, for example, Figure 2The diagram shows a real-time monitoring module 201, an analysis module 202, an evaluation index calculation module 203, and an adjustment module 204. The computer program comprised of these modules causes the processor to execute the steps in the data classification and grading standard update method described in the various embodiments of this application.

[0087] For example, Figure 3 The electronic device shown can be used as follows Figure 2 The data classification and grading standard update device shown includes a real-time monitoring module 201 that monitors business data and policy and regulatory documents in real time; an electronic device can perform analysis on the business data according to the initial classification and grading standards through an analysis module 202 to obtain analysis results; an electronic device can perform preset analysis operations on policy and regulatory documents through an evaluation index calculation module 203 and calculate the evaluation index of the initial classification and grading standards based on the analysis results; and an electronic device can adjust the initial classification and grading standards according to the analysis results and the evaluation indexes through an adjustment module 204.

[0088] In one embodiment, this application provides an electronic device including a memory and a processor, the memory storing a computer program, the processor executing the computer program to perform the following steps:

[0089] Real-time monitoring of business data and policy and regulatory documents; analysis of business data according to the initial classification and grading standards to obtain analysis results; execution of preset analysis operations on policy and regulatory documents, and calculation of evaluation indicators for the initial classification and grading standards based on the analysis results; adjustment of the initial classification and grading standards based on the analysis results and evaluation indicators.

[0090] In one embodiment, the processor, when executing the computer program, also performs the following steps: real-time monitoring of business data and policy and regulatory documents, including: invoking the Flink monitoring system to monitor business data; and using web crawling technology to crawl policy and regulatory documents from relevant websites corresponding to the business data.

[0091] In one embodiment, when the processor executes the computer program, it further implements the following steps: after real-time monitoring of business data and policy and regulatory documents, and before performing a preset analysis operation on the policy and regulatory documents and calculating the evaluation indicators of the initial classification and grading standards based on the analysis results, the method further includes: extracting key information from the policy and regulatory documents, the key information including at least one of document attributes, document content, release time, effective time, and implementation status; determining the amount of change in the policy and regulatory documents based on the key information; and issuing an alarm when the amount of change in the policy and regulatory documents meets the triggering conditions; wherein the triggering conditions include at least one of the following: the number of policy and regulatory documents increases beyond a preset number threshold; the document attributes of the policy and regulatory documents change; or the document content of the policy and regulatory documents changes.

[0092] In one embodiment, when the processor executes the computer program, it further performs the following steps: analyzing business data according to an initial classification and grading standard to obtain analysis results, including: calculating the data volume or growth rate of the business data to analyze the growth trend of the business data volume; parsing the classified business data to analyze the attribute changes of the business data; monitoring the operation logs of the business data, and statistically analyzing the access frequency, access duration and access users of the business data to analyze the usage of the business data; and detecting the data sensitivity and potential risks of the business data.

[0093] In one embodiment, when the processor executes the computer program, it further implements the following steps: Preset analysis operations include: correlation analysis, relevance analysis, and time series analysis; evaluation indicators for the initial classification and grading criteria include: compliance indicators, used to evaluate the compliance of the initial classification and grading criteria in classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading criteria in classifying business data; security indicators, used to evaluate the security of the initial classification and grading criteria in grading business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; relevance indicators, used to evaluate the relevance between the data sensitivity of policy and regulatory documents and business data; periodic indicators, used to evaluate the update frequency of policy and regulatory documents; trend indicators, used to evaluate the strictness of policy and regulatory documents; and a comprehensive indicator calculated using a multi-criteria decision analysis strategy by combining the above indicators.

[0094] In one embodiment, the processor, when executing the computer program, also performs the following steps: adjusting the initial classification and grading criteria based on the analysis results and evaluation indicators, including: adjusting the data categories and levels; and / or, reclassifying data sensitivity.

[0095] The electronic device provided in this application, when its processor executes a computer program, monitors business data and policy and regulatory documents in real time. First, it analyzes the business data according to an initial classification and grading standard to obtain analysis results. Then, it performs preset analysis operations on the policy and regulatory documents and calculates the evaluation indicators of the initial classification and grading standard based on the analysis results. Subsequently, it adjusts the initial classification and grading standard based on the analysis results and the evaluation indicators. In this way, this application adapts to changes in business needs and policy and regulatory documents, dynamically updating and adjusting the classification and grading standards for business data, ensuring the compliance of the data classification and grading standards, and improving the efficiency and accuracy of data classification and grading work.

[0096] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, wherein when executed by the computer program, the following steps are performed:

[0097] Real-time monitoring of business data and policy and regulatory documents; analysis of business data according to the initial classification and grading standards to obtain analysis results; execution of preset analysis operations on policy and regulatory documents, and calculation of evaluation indicators for the initial classification and grading standards based on the analysis results; adjustment of the initial classification and grading standards based on the analysis results and evaluation indicators.

[0098] In one embodiment, when the computer program is executed, it further performs the following steps: real-time monitoring of business data and policy and regulatory documents, including: calling the Flink monitoring system to monitor business data; and using web crawling technology to crawl policy and regulatory documents from relevant websites corresponding to the business data.

[0099] In one embodiment, when the computer program is executed, it further implements the following steps: after real-time monitoring of business data and policy and regulatory documents, and before performing a preset analysis operation on the policy and regulatory documents and calculating the evaluation indicators of the initial classification and grading standards based on the analysis results, the method further includes: extracting key information from the policy and regulatory documents, the key information including at least one of document attributes, document content, release time, effective time, and implementation status; determining the amount of change in the policy and regulatory documents based on the key information; and issuing an alarm when the amount of change in the policy and regulatory documents meets the triggering conditions; wherein the triggering conditions include at least one of the following: the number of policy and regulatory documents increases beyond a preset number threshold; the document attributes of the policy and regulatory documents change; or the document content of the policy and regulatory documents changes.

[0100] In one embodiment, when the computer program is executed, it further performs the following steps: analyzing business data according to an initial classification and grading standard to obtain analysis results, including: calculating the size or growth rate of the business data to analyze the growth trend of the business data; parsing the classified business data to analyze the attribute changes of the business data; monitoring the operation logs of the business data, and statistically analyzing the access frequency, access duration, and accessing users of the business data to analyze the usage of the business data; and detecting the data sensitivity and potential risks of the business data.

[0101] In one embodiment, when the computer program is executed, it further implements the following steps: Preset analysis operations include: correlation analysis, relevance analysis, and time series analysis; evaluation indicators for the initial classification and grading standards include: compliance indicators, used to evaluate the compliance of the initial classification and grading standards in classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards in classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards in grading business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; relevance indicators, used to evaluate the relevance between the data sensitivity of policy and regulatory documents and business data; periodic indicators, used to evaluate the update frequency of policy and regulatory documents; trend indicators, used to evaluate the strictness of policy and regulatory documents; and a comprehensive indicator calculated using a multi-criteria decision analysis strategy by combining the above indicators.

[0102] In one embodiment, when the computer program is executed, it further performs the following steps: adjusting the initial classification and grading criteria based on the analysis results and evaluation indicators, including: adjusting the data categories and levels; and / or, reclassifying data sensitivity.

[0103] When the computer program in the computer-readable storage medium provided in this application executes the computer program, it monitors business data and policy and regulatory documents in real time. First, it analyzes the business data according to an initial classification and grading standard to obtain analysis results. Then, it performs preset analysis operations on the policy and regulatory documents and calculates the evaluation indicators of the initial classification and grading standard based on the analysis results. Subsequently, it adjusts the initial classification and grading standard based on the analysis results and the evaluation indicators. In this way, this application adapts to changes in business needs and policy and regulatory documents, dynamically updating and adjusting the classification and grading standards for business data, ensuring the compliance of the data classification and grading standards, and improving the efficiency and accuracy of data classification and grading work.

[0104] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0105] It should be understood, in the several embodiments provided in this application, that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; 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.

[0106] In this application, the processor can be a Central Processing Unit (CPU), or 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.

[0107] In this application, memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0108] In this application, computer-readable media includes both permanent and non-permanent, removable and non-removable storage media. Storage media can implement information storage using any method or technology; the information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient media, such as modulated data signals and carrier waves.

[0109] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0110] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for updating data classification and grading standards, characterized in that, include: Real-time monitoring of business data and policy / regulatory documents; The business data was analyzed according to the initial classification and grading standards to obtain the analysis results; Perform a pre-defined analysis on policy and regulatory documents, and calculate the evaluation indicators of the initial classification and grading standards based on the analysis results; Based on the analysis results and the evaluation indicators, the initial classification and grading standards are adjusted. After the real-time monitoring of business data and policy and regulatory documents, and before the pre-defined analysis operation on the policy and regulatory documents is performed and the evaluation indicators of the initial classification and grading standards are calculated based on the analysis results, the method further includes: Extract key information from the policy and regulatory documents, including at least one of the following: document attributes, document content, publication date, effective date, and implementation status; Based on the aforementioned key information, determine the amount of change in the policy and regulatory documents; An alarm is issued when the changes in the policy and regulatory documents meet the triggering conditions; The triggering conditions include at least one of the following: the number of policy and regulatory documents exceeds a preset threshold; the document attributes of the policy and regulatory documents change; or the document content of the policy and regulatory documents changes.

2. The method according to claim 1, characterized in that, The real-time monitoring business data and policy and regulatory documents include: The Flink monitoring system is invoked to monitor the aforementioned business data. Using web scraping technology, the policy and regulatory documents are crawled from relevant websites corresponding to the business data.

3. The method according to claim 1, characterized in that, The analysis of the business data according to the initial classification and grading standards yields the following results: Calculate the size or growth rate of the business data to analyze the growth trend of the business data volume; Analyze the categorized business data to analyze changes in its attributes; Monitor the operation logs of the business data, and count the access frequency, access duration, and accessing users of the business data in order to analyze the usage of the business data; The data sensitivity and potential risks of the business data are detected.

4. The method according to claim 1, characterized in that, The preset analysis operations include: correlation analysis, correlation analysis, and time series analysis; The evaluation indicators for the initial classification and grading criteria include: Compliance metrics are used to evaluate the compliance of the initial classification and grading criteria in classifying the business data. Adaptability metrics are used to evaluate the adaptability of the initial classification and grading criteria to classify the business data; Security indicators are used to evaluate the security of the business data according to the initial classification and grading criteria. Relevance indicators are used to evaluate the correlation between the policy and regulatory documents and the business data; Relevance metrics are used to evaluate the relevance between the policy and regulatory documents and the data sensitivity of the business data. Periodic indicators are used to evaluate the update frequency of the aforementioned policy and regulatory documents; Trend indicators are used to evaluate the stringency of the aforementioned policy and regulatory documents; And, the comprehensive index calculated using a multi-criteria decision analysis strategy by combining the above indicators.

5. The method according to claim 4, characterized in that, The adjustment of the initial classification and grading criteria based on the analysis results and the evaluation indicators includes: Adjust data categories and levels; And / or, redistribute data sensitivity.

6. A device for updating data classification and grading standards, characterized in that, include: The real-time monitoring module is used to monitor business data and policy and regulatory documents in real time. The analysis module is used to analyze the business data according to the initial classification and grading standards to obtain analysis results; The evaluation index calculation module is used to perform preset analysis operations on policy and regulatory documents and calculate the evaluation index of the initial classification and grading standard based on the analysis results. An adjustment module is used to adjust the initial classification and grading criteria based on the analysis results and the evaluation indicators. The real-time monitoring module is also used to extract key information from the policy and regulatory documents, the key information including at least one of the following: document attributes, document content, publication time, effective time, and implementation status; Based on the aforementioned key information, determine the amount of change in the policy and regulatory documents; An alarm is issued when the changes in the policy and regulatory documents meet the triggering conditions; The triggering conditions include at least one of the following: the number of policy and regulatory documents exceeds a preset threshold; the document attributes of the policy and regulatory documents change; or the document content of the policy and regulatory documents changes.

7. An electronic device, characterized in that, include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the method for updating the data classification and grading standard as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, include: A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the method for updating the data classification and grading standard as described in any one of claims 1 to 5.

9. A computer program product, characterized in that, include: The computer program product includes a computer program that, when run on a computer, causes the computer to implement the data classification and grading standard update method as described in any one of claims 1 to 5.

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