Updating method and device of data classification and grading standard, equipment, medium and product

Abstract

The invention relates to a data classification and grading standard updating method and device, equipment, a medium and a product, in particular to the technical field of data retrieval. Comprising the steps of monitoring business data and policy and regulation files in real time; analyzing the business data according to the initial classification and grading standard to obtain an analysis result; executing a preset analysis operation on the policy and regulation file, and calculating an evaluation index of the initial classification and grading standard in combination with an analysis result; and according to the analysis result and the evaluation index, adjusting the initial classification and grading standard. The embodiment of the invention is used for solving the problem of poor adaptability of static data classification and grading standards.

Description

Technical Field

[0001] The present application relates to the technical field of data classification and grading, and in particular to a method, device, equipment, medium and product for updating data classification and grading standards. Background Art

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

[0003] Traditional methods often use static data classification and grading standards, but the business and data conditions of enterprises will change over time, such as launching new products, entering new markets, adopting new technologies, etc. For example, when an enterprise begins to expand overseas markets and involves cross-border data transmission, it may be necessary to re-evaluate the sensitivity and classification level of certain data to comply with the laws and regulations of different countries and regions. However, static data classification and grading standards lack a mechanism for continuous improvement and iteration, making it difficult for data classification and grading standards to adapt to the rapidly changing data environment, business needs and regulatory environment. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a method, device, equipment, medium and product for updating data classification and grading standards.

[0005] In a first aspect, the present application provides a method for updating data classification and grading standards, the method comprising: 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 evaluation indicators of the initial classification and grading standards based on the analysis results; adjusting the initial classification and grading standards based on the analysis results and the evaluation indicators.

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

[0007] As an optional implementation method provided by the implementation of the present 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 in combination with the analysis results, the method also includes: extracting key information from the policy and regulatory documents, the key information including at least one of file attributes, file content, release time, effective time and implementation status; determining the amount of change in the policy and regulatory documents based on the key information; issuing an alarm when the amount of change in the policy and regulatory documents meets the trigger condition; wherein the trigger condition includes at least one of the following: the increase in the number of policy and regulatory documents exceeds a preset number threshold; the file attributes of the policy and regulatory documents change; the file content of the policy and regulatory documents changes.

[0008] As an optional implementation method provided by the present 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 the business data to analyze the growth trend of the business data volume; parsing and classifying the business data to analyze the attribute changes of the business data; monitoring the operation log of the business data, counting the access frequency, access duration and access users of the business data to analyze the usage of the business data; detecting the data sensitivity and potential risks of the business data.

[0009] As an optional implementation provided for the implementation of the present 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 for classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards for classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards for grading business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and the data sensitivity of business data; periodicity 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 provided in the present application, the initial classification and grading standards are adjusted according to the analysis results and evaluation indicators, including: adjusting the data category and level; and / or, re-dividing the data sensitivity.

[0011] In a second aspect, the present application provides a device for updating a data classification and grading standard, the device comprising:

[0012] Real-time monitoring module, used to monitor business data and policy and regulatory documents in real time;

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

[0014] An 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] An adjustment module is used to adjust the initial classification and grading standards according to the analysis results and the evaluation indicators.

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

[0017] As an optional implementation provided for the implementation of the present application, the real-time monitoring module is also used to: extract key information from policy and regulatory documents, the key information including at least one of file attributes, file content, release time, effective time and implementation status; determine the amount of change in the policy and regulatory documents based on the key information; issue an alarm when the amount of change in the policy and regulatory documents meets the trigger condition; wherein the trigger condition includes at least one of the following: the number of policy and regulatory documents increases by more than a preset number threshold; the file attributes of the policy and regulatory documents change; the file content of the policy and regulatory documents changes.

[0018] As an optional implementation mode provided by the present application, the analysis module is specifically used to: calculate the data volume or growth rate of business data to analyze the growth trend of the business data volume; parse and classify business data to analyze the attribute changes of business data; monitor the operation log of business data, count the access frequency, access duration and accessing users of business data to analyze the usage of business data; detect the data sensitivity and potential risks of business data.

[0019] As an optional implementation provided for the implementation of the present 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 for classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards for classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards for grading business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and the data sensitivity of business data; periodicity 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 provided in the present application, the adjustment module is specifically used to: adjust data categories and levels; and / or, reclassify data sensitivity.

[0021] In a third aspect, the present application provides an electronic device comprising: 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, the method for updating the data classification and grading standards as described in the first aspect or any one of its optional embodiments is implemented.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium, comprising: a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements the method for updating the data classification and grading standards as described in the first aspect or any one of its optional embodiments.

[0023] In a fifth aspect, the present application provides a computer program product, comprising: the computer program product comprises a computer program, and when the computer program runs on a computer, the computer implements the method for updating the data classification and grading standards as described in the first aspect or any one of its optional embodiments.

[0024] Compared with the prior art, the technical solution provided by the embodiments of the present application has the following advantages:

[0025] The disclosed embodiment provides a method for updating data classification and grading standards, which monitors business data and policy and regulatory documents in real time, first analyzes the business data according to the initial classification and grading standards to obtain analysis results, then performs preset analysis operations on the policy and regulatory documents, and calculates the evaluation indicators of the initial classification and grading standards in combination with the analysis results; and then adjusts the initial classification and grading standards according to the analysis results and the evaluation indicators. In this way, the application adapts to changes in business needs and policy and regulatory documents, dynamically updates and adjusts the classification and grading standards of business data, ensures the compliance of the data classification and grading standards, and improves the efficiency and accuracy of data classification and grading work. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0027] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0028] Figure 1 A flowchart of a method for updating data classification and grading standards provided in an embodiment of the present application;

[0029] Figure 2 A schematic diagram of the structure of a device for updating data classification and grading standards provided in an embodiment of the present application;

[0030] Figure 3 A schematic diagram of the structure of an electronic device described in an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the scheme of the present application will be further described below. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0032] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only part of the embodiments of the present application, rather than all of the embodiments.

[0033] Data classification and grading play a vital role in the field of data element governance. It can not only improve the manageability and security of data, but also enhance the value of data, providing a strong guarantee for the digital transformation and sustainable development of enterprises. Traditional methods often adopt static data classification and grading standards. When formulating data classification and grading standards, there may be a lack of timely understanding and compliance with the latest regulations, and these standards are rarely updated or adjusted after they are formulated. The lack of a mechanism for continuous improvement and iteration makes it difficult for data classification and grading standards to adapt to the rapidly changing data environment, business needs, and regulatory environment.

[0034] In order to solve some or all of the technical problems existing in the related technologies, the embodiments of the present application provide a method, device, equipment, medium and product for updating data classification and grading standards, wherein the method monitors business data and policy and regulatory documents in real time, first analyzes the business data according to the initial classification and grading standards to obtain analysis results, then performs preset analysis operations on the policy and regulatory documents, and calculates the evaluation indicators of the initial classification and grading standards in combination with the analysis results; and then adjusts the initial classification and grading standards according to the analysis results and the evaluation indicators. In this way, the present application adapts to changes in business needs and policy and regulatory documents, dynamically updates and adjusts the classification and grading standards of business data, ensures the compliance of the data classification and grading standards, and improves the efficiency and accuracy of data classification and grading work.

[0035] A method for updating a data classification and grading standard provided in an embodiment of the present application can be implemented by an updating device or electronic device for the data classification and grading standard, and the electronic device includes but is not limited to a vehicle terminal, a server, a personal computer, a laptop computer, a tablet computer, a smart phone, etc. The operating system of the electronic device may include Android, a mobile operating system (iOS) developed by Apple, an operating system (Windows) developed by Microsoft Corporation of the United States, etc., and the embodiment of the present application does not limit this. The electronic device can be run alone to implement the present application, or it can be connected to a network and implement the present application through interactive operations with other computer devices in the network. Among them, the network in which the electronic device is located includes but is not limited to the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN) network, etc.

[0036] It should be noted that the protection scope of the method for updating data classification and grading standards described in the embodiment of the present application is not limited to the execution order of the steps listed in this embodiment. All solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present application are included in the protection scope of the present application.

[0037] like Figure 1 As shown, Figure 1 The following is a flow chart of a method for updating a data classification and grading standard according to an embodiment of the present application. The method can be executed by a device for updating a data classification and grading standard, wherein the device can be implemented by software and / or hardware and can generally be integrated in 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 by an enterprise during its operation, and is an important basis for enterprise decision-making and operation. Business data usually includes user information, transaction records, product usage, etc. Among them, user information includes user ID, name, contact information, registration time, etc. Transaction records include transaction ID, transaction time, transaction amount, transaction goods, etc. Product usage includes product ID, user feedback, usage frequency, fault records, etc.

[0040] Policy and regulatory documents include policy documents, legal documents, industry standard documents, technical specification documents, safety standard documents, etc., which are in text form. Different industries have different legal and regulatory requirements. For example, the financial industry is subject to the Basel Agreement, and the medical industry is subject to medical data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA). Enterprises need to identify these data subject to regulations, such as customer fund transaction records of financial institutions and patient medical records of medical institutions. These data are usually of high importance and sensitivity and must be strictly classified and protected in accordance with regulatory requirements.

[0041] In some embodiments, a real-time monitoring system may be called to execute step S101, and the real-time monitoring system may be Flink. As a highly available, high-performance distributed computing engine with streams as the core, Flink has the characteristics of stream-batch integration, high throughput, low latency, and fault tolerance, and is very suitable for processing large-scale complex computing tasks. Through Flink, we can monitor the changes in the amount of business data, changes in data attributes, data access and usage, and updates to relevant laws, regulations, and industry standards in real time.

[0042] In some embodiments, when monitoring policy and regulatory documents in real time, crawler technology can be used to crawl policy and regulatory documents from policy and regulatory related websites corresponding to business data. After that, key information is extracted from the policy and regulatory documents, and the key information and the policy and regulatory documents can be stored in a database corresponding to the key information, and the change in the policy and regulatory documents is monitored based on the extracted key information. Among them, the key information includes at least one of the following: file attributes, file content, release time, effective time and implementation status, etc. When the change in the policy and regulatory documents meets at least one of the following trigger conditions, an alarm is issued: the number of files of the policy and regulatory files increases by more than a preset number threshold, the file attributes of the policy and regulatory files change, and the file content of the policy and regulatory files changes. It should be noted that the setting of the trigger conditions needs to be adjusted and optimized according to specific business needs and monitoring objectives, and this application is not specifically limited here.

[0043] The above-mentioned embodiments pay close attention to changes in the regulatory environment, so as to promptly incorporate the latest regulatory requirements into the data classification and grading standards to ensure compliance with the standards. When it is detected that the amount of change in policy and regulatory documents meets any triggering condition, an alarm is issued immediately, thereby greatly shortening the time interval from the change in policies and regulations to the discovery, so that relevant personnel can respond quickly and take measures. Alarms are issued based on pre-set reasonable and scientific triggering conditions, reducing false alarms and missed reports. The entire process does not require manual continuous observation and judgment. The system automatically monitors whether the amount of change in policy and regulatory documents meets the triggering conditions and issues an alarm. When the alarm is triggered, the amount of change in policy and regulatory documents is recorded at the same time. This information can help relevant personnel quickly understand the changes in policy and regulatory documents.

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

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

[0046] In some embodiments, when executing step S102, it includes: calculating the data volume or growth rate of business data to analyze the growth trend of business data volume; parsing and classifying business data to analyze the attribute changes of business data; monitoring the operation log of business data, counting the access frequency, access duration and access users of business data to analyze the usage of business data; 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 called to analyze the business data according to the initial classification and grading standards. Optionally, Flink records or calculates the data volume (such as MB, GB) or data growth rate in real time to analyze the growth trend of the business data volume. For example, when analyzing the business volume data, it is found that the business data volume shows a rapid growth trend over a period of time. By drawing a business data volume trend chart, the growth rate and fluctuation of the business data volume can be clearly seen. If an abnormal point appears, it indicates that the business may be at risk and its data classification and grading settings need to be adjusted.

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

[0049] By monitoring the operation logs of business data through Flink, the access frequency, access duration and access users of business data are counted to analyze the usage of business data. The usage of business data includes operations such as reading, writing and querying business data.

[0050] Optionally, when detecting potential risks in business data, it can be implemented in any of the following ways: determine the fields that each data record should contain through data dictionaries and business rules, and then write scripts or use data quality tools to scan missing values ​​in the data set; compare the consistency of the same business data between different data sources through data reconciliation tools or write SQL queries to identify inconsistent data records; you can also observe the changing trend of business data over time to discover potential risks; by calculating the ratio between different business indicators (such as gross profit margin, inventory turnover rate, debt-paying ability ratio, etc.), and comparing with industry standards or target values ​​set by the enterprise itself, determine whether there is potential risk; you can use statistical software or data analysis tools to calculate the correlation coefficient between data, determine the strength and direction of correlation between variables, and then identify combinations of factors that may affect each other and cause risks; you can use association rule mining algorithms to discover frequent item sets and association rules in the data to reveal potential risk associations; you can collect historical business data, including various factors related to risk events (such as customer credit scores, project budget overruns, etc.) as independent variables, and take whether a risk event occurs as the dependent variable to build a logistic regression model. After training and validation, the model can predict the probability of risk events based on new business data inputs.

[0051] The above analysis results are obtained by analyzing the business data according to the initial classification and grading standards, thereby achieving in-depth analysis and effective use of the business data.

[0052] S103. Perform preset analysis operations on the policy and regulatory documents, and calculate evaluation indicators of 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. The association analysis includes but is not limited to association rule mining and cluster analysis.

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

[0055] 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, the compliance index and adaptability index of the initial classification standard are calculated, and the security index of the initial classification standard is calculated. The initial classification standard divides the business data into categories and identifies the sensitivity of the business data. The initial classification standard divides the levels of the business data.

[0057] When calculating the compliance indicators of the initial classification standards, a data classification tool is used to identify and label business data, and compliance checking software is applied to calculate the compliance indicators of the initial classification standards to verify the compliance of the initial classification standards. The data classification tool can be the IBM InfoSphere Guardium Data Classification tool (IBM InfoSphere Guardium Data Classification), which is used to identify, classify and protect sensitive data. The compliance checking software can be the RSA Archer Governance, Risk and Compliance Platform (RSA Archer GRC), which is used to manage and monitor risk, compliance and enterprise governance.

[0058] When calculating the adaptability index of the initial classification standard, use data analysis and visualization tools to analyze the growth trend and attribute changes of the business data to determine whether the initial classification standard is suitable for the growth trend and attribute changes of the business data, and obtain the adaptability index of the initial classification standard. The data analysis and visualization tools can be PowerBI data analysis tools (Microsoft Power BI) and Tableau. Microsoft Power BI is a set of business analysis tools, a collection of software services, applications, and connectors that work together to transform unrelated data sources into interactive insights with continuous, immersive visual experiences. Tableau is a simple business intelligence tool software for desktop systems that can help 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 to generate easy-to-understand charts, graphs, maps, dashboards, and stories.

[0059] Alternatively, when calculating the adaptability index of the initial classification standard, the patterns and characteristics of the business data are identified through a machine learning algorithm, and the adaptability index of the initial classification standard is calculated based on the patterns and characteristics of the business data, thereby evaluating the adaptability of the initial classification standard.

[0060] When calculating the security indicators of the initial classification standards, the sensitivity and potential risks of the monitored business data are quantified using risk assessment tools to calculate the security indicators of the initial classification standards. This can evaluate the security of the initial classification standards. Risk assessment tools can be risk assessment matrices, RSA Archer GRC, etc. The risk assessment matrix is ​​a tool used to classify and evaluate risks according to their probability and impact. It usually consists of two dimensions: the probability dimension represents the possibility of a risk event occurring, and the impact dimension represents the potential impact of the risk event on the organization or project. By dividing these two dimensions into different levels or ranges, a risk assessment matrix can be constructed to intuitively compare and sort different risks.

[0061] In some embodiments, in the process of performing preset analysis operations on policy and regulatory documents, the correlation index between business data and policy and regulatory documents is calculated through association rule mining and cluster analysis, etc., to discover potential business rules and policy and regulatory impacts; correlation analysis is performed by calculating the correlation coefficients between different policies and regulations to calculate the correlation index between the sensitivity of policies and regulations and business data, and analyze the correlation between policies and regulations and data sensitivity; by analyzing the changing trend of policy and regulatory documents over time, the periodicity index and trend index of policies and regulations are calculated. If the trend characteristics indicate that the policies and regulations are becoming more and more stringent, the sensitivity of the business data corresponding to the policies and regulations 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-making support method that considers multiple criteria (or standards, attributes) to evaluate and compare different alternatives.

[0063] An optional implementation of the above embodiment includes: first obtaining the preset weights of each evaluation indicator, and calculating the comprehensive indicator according to the evaluation indicator and the corresponding preset weights. Comprehensively considering multiple evaluation criteria, assigning preset weights to each evaluation criterion, scoring and ranking to obtain a comprehensive indicator. By comprehensively considering multiple evaluation indicators through a multi-criteria decision analysis method, the evaluation result is more scientific and reasonable.

[0064] By analyzing and evaluating business data and policy and regulatory documents, we can timely understand the changing trends and potential risks of data, thereby providing a scientific basis for the adjustment and optimization of 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, the initial classification and grading standards are adjusted.

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

[0067] In some embodiments, adjusting the initial classification and grading standards includes: adjusting the data category and level; and / or reclassifying the data sensitivity. Optionally, the data category is reclassified using automated classification software; and the data sensitivity is reclassified using risk assessment software. This allows the business data to be automatically classified into the corresponding category or level.

[0068] For example, if new data categories or attributes are added, they will be promptly incorporated into the classification system; if data categories or attributes are no longer applicable, they will be removed or merged. User names, ID numbers, and mobile phone numbers are classified as highly sensitive data; home addresses and shopping records are classified as medium-sensitive data; and public information is classified as low-sensitive data. This will strengthen security protection measures for highly sensitive data; and appropriately relax usage restrictions for low-sensitive data.

[0069] In some embodiments, when adjusting the initial classification and grading standards, project management software is used to track and manage the implementation progress and effect of the adjustment measures, thereby ensuring the effective implementation of the adjustment measures. The project management software can be Microsoft Project (MS Project), which is a project management software developed by Microsoft Corporation to assist 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 classification and grading 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. After the data classification and grading standards are revised and improved, they can be released and implemented, which is conducive to improving the compliance, security and effectiveness of data management, and provides a strong guarantee for the data governance and decision support of enterprises.

[0071] After review and revision, the revised data classification and grading standards are officially released, and relevant personnel are organized for training and implementation. Relevant personnel are trained on data classification and grading standards to improve their data awareness and compliance awareness. Through training, ensure that relevant personnel can accurately understand and implement the new standards. Strengthen the publicity and promotion of data classification and grading standards through internal announcements, brochures, etc. Improve the attention of all employees to data management and create a good data management atmosphere.

[0072] In summary, the embodiment of the present application provides a method for updating data classification and grading standards, which monitors business data and policy and regulatory documents in real time, first analyzes the business data according to the initial classification and grading standards to obtain analysis results, then performs preset analysis operations on the policy and regulatory documents, and calculates the evaluation indicators of the initial classification and grading standards in combination with the analysis results; and then adjusts the initial classification and grading standards according to the analysis results and the evaluation indicators. In this way, the present application adapts to changes in business needs and policy and regulatory documents, dynamically updates and adjusts the classification and grading standards of business data, ensures the compliance of the data classification and grading standards, and improves the efficiency and accuracy of data classification and grading work.

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

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

[0075] An analysis module 202 is used to analyze the business data according to the initial classification and grading standard to obtain an analysis result;

[0076] Evaluation index calculation module 203, 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 standard according to the analysis result and the evaluation index.

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

[0079] As an optional implementation provided for the implementation of the present application, the real-time monitoring module 201 is also used to: extract key information from policy and regulatory documents, the key information including at least one of file attributes, file content, release time, effective time and implementation status; determine the amount of change in the policy and regulatory documents based on the key information; issue an alarm when the amount of change in the policy and regulatory documents meets the trigger condition; wherein the trigger condition includes at least one of the following: the number of policy and regulatory documents increases by more than a preset number threshold; the file attributes of the policy and regulatory documents change; the file content of the policy and regulatory documents changes.

[0080] As an optional implementation provided for the implementation of the present application, the analysis module 202 is specifically used to: calculate the data volume or growth rate of business data to analyze the growth trend of the business data volume; parse and classify business data to analyze the attribute changes of business data; monitor the operation log of business data, count the access frequency, access duration and access users of business data to analyze the usage of business data; detect the data sensitivity and potential risks of business data.

[0081] As an optional implementation provided for the implementation of the present 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 for classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards for classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards for grading business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and the data sensitivity of business data; periodicity 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 provided in the present application, the adjustment module 204 is specifically used to: adjust the data category and level; and / or, reclassify the data sensitivity.

[0083] For the specific definition of the updating device of the data classification and grading standard, please refer to the definition of the updating method of the data classification and grading standard in the above text, which will not be repeated here. Each module in the above-mentioned updating device of the data classification and grading standard can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0084] In one embodiment, the present 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, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for updating a data classification and grading standard is implemented. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a button, a trackball or a touch pad set on the housing of the electronic device, or an external keyboard, touch pad or mouse, etc.

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

[0086] In one embodiment, the data classification and grading standard updating device provided by the present application can be implemented in the form of a computer program. Figure 3 The memory of the electronic device may store various program modules constituting the updating device of the data classification and grading standard, for example, Figure 2The real-time monitoring module 201, the analysis module 202, the evaluation index calculation module 203 and the adjustment module 204 are shown. The computer program composed of each program module enables the processor to execute the steps in the method for updating the data classification and grading standard of each embodiment of the present application described in this specification.

[0087] For example, Figure 3 The electronic device shown can be Figure 2 In the device for updating the data classification and grading standards shown, the real-time monitoring module 201 performs real-time monitoring of business data and policy and regulatory documents; the electronic device can analyze the business data according to the initial classification and grading standards through the analysis module 202 to obtain analysis results; the electronic device can perform preset analysis operations on the policy and regulatory documents through the evaluation index calculation module 203, and calculate the evaluation index of the initial classification and grading standards based on the analysis results; the electronic device can adjust the initial classification and grading standards according to the analysis results and the evaluation index through the adjustment module 204.

[0088] In one embodiment, the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0089] Monitor business data and policy and regulatory documents in real time; analyze business data according to the initial classification and grading standards to obtain analysis results; perform preset analysis operations on policy and regulatory documents, and calculate evaluation indicators of the initial classification and grading standards based on the analysis results; adjust the initial classification and grading standards based on the analysis results and evaluation indicators.

[0090] In one embodiment, the processor further implements the following steps when executing the computer program: real-time monitoring of business data and policy and regulatory documents includes: calling the implementation monitoring system Flink to monitor business data; using crawler technology to crawl policy and regulatory documents from relevant websites corresponding to the business data.

[0091] In one embodiment, the processor also implements the following steps when executing the computer program: 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 in combination with the analysis results, the method also includes: extracting key information from the policy and regulatory documents, the key information including at least one of file attributes, file content, release time, effective time and implementation status; determining the amount of change in the policy and regulatory documents based on the key information; issuing an alarm when the amount of change in the policy and regulatory documents meets the trigger condition; wherein the trigger condition includes at least one of the following: the increase in the number of policy and regulatory documents exceeds a preset number threshold; the file attributes of the policy and regulatory documents change; the file content of the policy and regulatory documents changes.

[0092] In one embodiment, the processor also implements the following steps when executing the computer program: analyzing the business data according to the initial classification and grading standards 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 and classifying the business data to analyze the attribute changes of the business data; monitoring the operation log of the business data, counting the access frequency, access duration and access users of the business data to analyze the usage of the business data; detecting the data sensitivity and potential risks of the business data.

[0093] In one embodiment, the processor also implements the following steps when executing the computer program: 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 for classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards for classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards for grading business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and data sensitivity of business data; periodicity 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.

[0094] In one embodiment, when the processor executes the computer program, the following steps are also implemented: adjusting the initial classification and grading standards based on the analysis results and evaluation indicators, including: adjusting the data category and level; and / or, reclassifying the data sensitivity.

[0095] When the processor in the electronic device provided by the present application executes a computer program, it monitors business data and policy and regulatory documents in real time, first analyzes the business data according to the initial classification and grading standards to obtain analysis results, then performs preset analysis operations on the policy and regulatory documents, and calculates the evaluation indicators of the initial classification and grading standards in combination with the analysis results; and then adjusts the initial classification and grading standards according to the analysis results and the evaluation indicators. In this way, the present application adapts to changes in business needs and policy and regulatory documents, dynamically updates and adjusts the classification and grading standards of business data, ensures the compliance of the data classification and grading standards, and improves the efficiency and accuracy of data classification and grading work.

[0096] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by the computer program, the following steps are implemented:

[0097] Monitor business data and policy and regulatory documents in real time; analyze business data according to the initial classification and grading standards to obtain analysis results; perform preset analysis operations on policy and regulatory documents, and calculate evaluation indicators of the initial classification and grading standards based on the analysis results; adjust the initial classification and grading standards based on the analysis results and evaluation indicators.

[0098] In one embodiment, the computer program also implements the following steps when executed by the computer program: real-time monitoring of business data and policy and regulatory documents includes: calling the implementation monitoring system Flink to monitor business data; using crawler technology to crawl policy and regulatory documents from relevant websites corresponding to the business data.

[0099] In one embodiment, the computer program also implements the following steps when executed by the computer program: 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 in combination with the analysis results, the method also includes: extracting key information from the policy and regulatory documents, the key information including at least one of file attributes, file content, release time, effective time and implementation status; determining the amount of change in the policy and regulatory documents based on the key information; issuing an alarm when the amount of change in the policy and regulatory documents meets the trigger condition; wherein the trigger condition includes at least one of the following: the number of policy and regulatory documents increases by more than a preset number threshold; the file attributes of the policy and regulatory documents change; the file content of the policy and regulatory documents changes.

[0100] In one embodiment, the computer program also implements the following steps when executed by the computer program: analyzing the business data according to the initial classification and grading standards 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 and classifying the business data to analyze the attribute changes of the business data; monitoring the operation log of the business data, counting the access frequency, access duration and access users of the business data to analyze the usage of the business data; detecting the data sensitivity and potential risks of the business data.

[0101] In one embodiment, the computer program also implements the following steps when executed by the computer program: preset analysis operations include: correlation analysis, relevance analysis and time series analysis; evaluation indicators of the initial classification and grading standards include: compliance indicators, used to evaluate the compliance of the initial classification and grading standards for classifying business data; adaptability indicators, used to evaluate the adaptability of the initial classification and grading standards for classifying business data; security indicators, used to evaluate the security of the initial classification and grading standards for grading business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and business data; correlation indicators, used to evaluate the correlation between policy and regulatory documents and data sensitivity of business data; periodicity 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.

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

[0103] When the computer program in the computer-readable storage medium provided by the present application executes the computer program, it monitors the business data and policy and regulatory documents in real time, first analyzes the business data according to the initial classification and grading standards to obtain the analysis results, then performs the preset analysis operation on the policy and regulatory documents, and calculates the evaluation index of the initial classification and grading standards in combination with the analysis results; and then adjusts the initial classification and grading standards according to the analysis results and the evaluation index. In this way, the present application adapts to the changes in business needs and policy and regulatory documents, dynamically updates and adjusts the classification and grading standards of business data, ensures the compliance of the data classification and grading standards, and improves the efficiency and accuracy of data classification and grading work.

[0104] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media that include computer-usable program code.

[0105] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0106] In the present application, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

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

[0108] In this application, computer-readable media includes permanent and non-permanent, removable and non-removable storage media. Storage media can be implemented by any method or technology to store information, and the information can be computer-readable instructions, data structures, modules of programs 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 technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. According to the definition in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0109] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0110] The above is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for updating a data classification and grading standard, characterized in that: include: Real-time monitoring of business data and policy and regulatory documents; Analyze the business data according to the initial classification and grading standards to obtain analysis results; Performing preset analysis operations on policy and regulatory documents, and calculating evaluation indicators of the initial classification and grading standards based on the analysis results; The initial classification and grading standards are adjusted according to the analysis results and the evaluation indicators.

2. The method according to claim 1, characterized in that The real-time monitoring business data and policy and regulatory documents include: Call the monitoring system Flink to monitor the business data; The policy and regulatory documents are crawled from the relevant websites corresponding to the business data using crawler technology.

3. The method according to claim 1, characterized in that After the real-time monitoring of the business data and the policy and regulatory documents, and before the performing of the preset analysis operation on the policy and regulatory documents and calculating the evaluation index of the initial classification and grading standard in combination with the analysis result, the method further includes: Extract key information from the policy and regulation document, wherein the key information includes at least one of document attributes, document content, release time, effective time, and implementation status; Determine the amount of change in the policy and regulatory documents based on the key information; When the amount of change in the policy and regulation document meets the trigger condition, an alarm is issued; The trigger condition includes at least one of the following: the number of the policy and regulation files increases by more than a preset number threshold; the file attribute of the policy and regulation files changes; the file content of the policy and regulation files changes.

4. The method according to claim 1, characterized in that: The business data is analyzed according to the initial classification and grading standard to obtain analysis results, including: Calculate the data volume or growth rate of the business data to analyze the growth trend of the business data volume; Parsing and classifying the business data to analyze changes in attributes of the business data; Monitoring the operation log of the business data, counting the access frequency, access duration and access users of the business data, so as to analyze the usage of the business data; Detect the data sensitivity and potential risks of the business data.

5. The method according to claim 1, characterized in that The preset analysis operations include: relevance analysis, correlation 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 the business data; An adaptability index, used to evaluate the adaptability of the initial classification and grading standard to classify the business data; A security indicator used to evaluate the security of grading the business data using the initial classification and grading standards; A relevance index, used to evaluate the relevance between the policy and regulatory documents and the business data; A correlation index, used to evaluate the correlation between the policy and regulatory documents and the data sensitivity of the business data; a periodicity index, used to evaluate the update frequency of the policy and regulatory documents; Trend indicators, used to evaluate the strictness of the policy and regulatory documents; And, a comprehensive index calculated by combining the above indicators using a multi-criteria decision analysis strategy.

6. The method according to claim 5, characterized in that The adjusting the initial classification and grading standards according to the analysis results and the evaluation indicators includes: Adjust data categories and levels; and / or, reclassify data sensitivity.

7. A device for updating data classification and grading standards, characterized in that: include: Real-time monitoring module, used to monitor business data and policy and regulatory documents in real time; An analysis module is used to analyze the business data according to the initial classification and grading standards to obtain analysis results; An evaluation index calculation module is used to perform a preset analysis operation on the 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 standards according to the analysis results and the evaluation indicators.

8. 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 a method for updating a data classification and grading standard as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: include: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for updating the data classification and grading standard according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that include: The computer program product comprises a computer program, and when the computer program is executed on a computer, the computer is enabled to implement the method for updating the data classification and grading standard according to any one of claims 1 to 6.

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