Power plant data full life cycle management method, system and device and storage medium

Abstract

The embodiment of the invention provides a power plant data full life cycle management method, system and device and a storage medium. Firstly, asset carding is performed on power plant data, data assets are comprehensively and clearly clarified, then an enforceable data security classification and grading method is formed, and finally protection management is performed on the whole life cycle of the data according to a classification and grading result. According to the embodiment of the invention, by adopting a small sample sampling mode, the data protection construction cost, the maintenance cost and the labor cost are reduced, and a new thought is provided for providing low-cost and landing data full-life-cycle safety protection for the industry; an automatic classification and grading method is provided, and standardized grading and classification are carried out on power plant data; a set of complete and feasible scheme is provided for realizing classification and grading of power plant data in the power generation industry for the first time, theoretical support and technical support are provided for developing systems related to power plant data safety work, and the safety of the data in the whole life cycle is guaranteed.

Description

Technical Field

[0001] The embodiments of the present disclosure belong to the technical field of power plant data management, and specifically relate to a power plant data full life cycle management method, system, device and storage medium. Background Art

[0002] With the rapid development of information networks, various data security issues have continued to emerge. How to deal with the data and asset losses caused by information security and provide thorough security protection for data assets and information security has become the most concerning issue for power plants.

[0003] At present, the data protection scenarios of power generation enterprises mainly face the following problems: 1) There is no industry standard for the classification and grading of power plants. At present, there is no classification and grading solution and specification specifically for power plant data, which makes it difficult to effectively carry out data leakage prevention, tampering prevention, data classification protection, etc., which mainly focuses on power plant data security, and there is a risk of causing power system failures or major safety accidents; 2) Fragmentation of data security capabilities. Various production data, management data, operation data, personal data, etc. generated in the process of power production management are scattered in a large number of different information systems, office computers, operation and maintenance equipment, and mobile terminals. The business systems of each power plant are isolated, and the management of protective equipment is decentralized, resulting in unclear distribution of data assets, lack of linkage between equipment, and inability to effectively manage data; 3) Unclear data access and flow. The data transferred from the information system to the physical world lacks access control mechanisms, data flow and access lack effective records, and it is impossible to judge and track the historical path of data access; 4) Power companies have not yet had a system suitable for the security protection of power production and management data. Power plants lack data classification and grading capabilities, and there is no suitable tool support. They are mostly based on traditional IT asset management methods, lacking effective visualization, tracking, encryption, identity authentication, desensitization and other technical monitoring and protection. Summary of the invention

[0004] The embodiments of the present disclosure aim to solve at least one of the technical problems existing in the prior art and provide a method, system, device and storage medium for the full life cycle management of power plant data.

[0005] One aspect of the present disclosure provides a method for managing power plant data throughout its life cycle, the method comprising:

[0006] Sampling and collecting power plant data; wherein the power plant data includes general data and core data;

[0007] Encrypt power plant data for transmission, monitor abnormalities during data transmission, and generate data flow diagrams;

[0008] Distribute and store power plant data in corresponding storage media terminals, establish a data storage media management account, regularly verify the use of storage media, track and record removable storage media, and generate data distribution maps;

[0009] Desensitize the core data, handle emergencies caused by desensitization, and block the corresponding data interfaces;

[0010] Establish a data provision ledger, issue warnings for overdue usage of provided data, and track and record data asset transfers;

[0011] Establish a data destruction ledger, adopt overwrite-type clearing for general data, adopt physical destruction-type clearing for core data, and record and supervise the destruction process.

[0012] Furthermore, before the sampling and collection of power plant data, the method further includes:

[0013] Sorting out the power plant data, generating data asset management ledgers, and establishing data asset management views;

[0014] Semi-supervised learning is used to automatically classify and grade power plant data to obtain general data and core data.

[0015] Furthermore, the automatic classification and grading of power plant data using semi-supervised learning includes:

[0016] Get the power plant dataset;

[0017] Manually label a portion of the power plant data, extract the field features and similar column features of the remaining power plant data through unsupervised learning, and establish a classification and grading label feature model;

[0018] The classification and grading label feature model is used to automatically classify and grade power plant data.

[0019] Furthermore, the power plant data full life cycle management method also includes:

[0020] Conduct security assessment on power plant data, establish a data security compliance baseline, establish a data security privacy baseline, generate a data security assessment report, and generate a problem list based on the data security assessment report.

[0021] Another aspect of the present disclosure provides a power plant data full life cycle management system, the system comprising:

[0022] A data collection module, used for sampling and collecting power plant data; wherein the power plant data includes general data and core data;

[0023] Data transmission module, used to encrypt and transmit power plant data, monitor abnormalities in the data transmission process, and generate a data flow diagram;

[0024] The data storage module is used to store the power plant data in a dispersed manner in the corresponding storage medium terminal, establish a data storage medium management account, regularly verify the use of storage media, track and record removable storage media, and generate a data distribution map;

[0025] The data processing module is used to desensitize the core data, handle emergencies caused by desensitization, and block the corresponding data interface;

[0026] The data provision module is used to establish a data provision ledger, issue an alarm for overdue usage of the provided data, and track and record the transfer of data assets;

[0027] The data destruction module is used to establish a data destruction ledger, adopt overwrite-type clearing for general data, adopt physical destruction-type clearing for core data, and record and supervise the destruction process.

[0028] Furthermore, the power plant data life cycle management system also includes:

[0029] The asset sorting module is used to sort out the power plant data, generate data asset management ledgers, and establish data asset management views;

[0030] The classification and grading module is used to automatically classify and grade power plant data using semi-supervised learning to obtain general data and core data.

[0031] Furthermore, the classification and grading module is specifically used for:

[0032] Get the power plant dataset;

[0033] Manually label a portion of the power plant data, extract the field features and similar column features of the remaining power plant data through unsupervised learning, and establish a classification and grading label feature model;

[0034] The classification and grading label feature model is used to automatically classify and grade power plant data.

[0035] Furthermore, the power plant data life cycle management system also includes:

[0036] The security assessment module is used to conduct security assessments on power plant data, establish a data security compliance baseline, establish a data security privacy baseline, generate a data security assessment report, and generate a problem list based on the data security assessment report.

[0037] Another aspect of the present disclosure provides an electronic device, comprising:

[0038] at least one processor; and,

[0039] The memory communicatively connected to the at least one processor is used to store one or more programs, and when the one or more programs are executed by the at least one processor, the at least one processor can implement the power plant data full life cycle management method described above.

[0040] Another aspect of the present disclosure provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the power plant data full life cycle management method described above.

[0041] The disclosed embodiments provide a method, system, device and storage medium for managing the entire life cycle of power plant data. By adopting a small sample sampling method, the costs of data protection construction, maintenance costs and labor costs are reduced, providing the industry with a new way of thinking for low-cost and feasible data security protection throughout the entire life cycle. An automated classification and grading method is proposed to standardize the grading and classification of power plant data. For the first time, a complete and feasible solution is provided for the power generation industry to implement the classification and grading of power plant data, providing theoretical and technical support for the development of systems related to power plant data security work, and ensuring the security of data throughout its entire life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of a process of a method for managing the entire life cycle of power plant data according to an embodiment of the present disclosure;

[0043] Figure 2 This is a schematic diagram of the structure of a power plant data full life cycle management system according to another embodiment of the present disclosure;

[0044] Figure 3 The figure is a schematic diagram of the structure of an electronic device according to another embodiment of the present disclosure. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0046] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0047] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0048] It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another component. Therefore, the first component discussed below can be referred to as the second component without departing from the teachings of the concepts of the present disclosure. As used in this disclosure, the term "and / or" includes any one of the associated listed items and all combinations of one or more.

[0049] Those skilled in the art will appreciate that the drawings are merely schematic diagrams of example embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing the present disclosure, and therefore cannot be used to limit the protection scope of the present disclosure.

[0050] like Figure 1 As shown, an embodiment of the present disclosure provides a method for managing the entire life cycle of power plant data, the method comprising:

[0051] Step S1: sort out the assets of the power plant data.

[0052] Specifically, the structured database, semi-structured interface information, unstructured images and text of the power plant are comprehensively sorted out to form a data asset library, and data assets of different sources and types are merged and organized in a standardized and systematic manner. Data asset information is added through various methods such as automatic scanning of specified IP segments, manual addition by users, and batch import of asset catalogs, and operations such as query, modification, deletion, and export are provided for existing data asset information. A data asset management ledger is generated to clarify the type, source, content, and purpose of data assets, as well as the ownership and application scenarios of data assets, and to clearly display all data asset information in the power plant, making it convenient for power plant business personnel to manage various data assets. A data asset management view is established, and the displayed content may include asset type, asset quantity, asset distribution, etc., to intuitively display the management effect for users.

[0053] Step S2: Use semi-supervised learning to automatically classify and grade the power plant data to obtain general data and core data.

[0054] Specifically, the embodiments of the present disclosure abandon the drawbacks of a large amount of manual labeling in traditional data classification and grading methods, and propose a semi-supervised data classification and grading method based on deep learning to complete the automated classification and grading of massive data in the power plant field.

[0055] First, enter the data source to be scanned. Mainstream databases such as DAMO, Hailiang, PostgreSQL, and MySQL can be used. Then, the acquired power plant data set is sent to the semi-supervised learning engine for data asset investigation and labeling. A small amount of data is manually labeled, and similar field analysis of the remaining large amount of data is realized through unsupervised learning. Database field features and similar column features are automatically extracted to achieve batch labeling, thereby establishing a classification and grading label feature model. This model uses a multi-layer convolutional neural network and embeds the Word2Vec algorithm to train word vectors for short sentences, etc., while mining the features of the relationship between samples, learning the correlation between input and output labels, thereby automatically extracting database field features and similar column features, effectively extracting semantic and contextual information, and establishing a classification and grading label feature model to achieve automatic classification and grading of power plant data. This method can not only handle multiple data types such as numbers, dates, and texts, but also process multi-dimensional and complex relationship data. For unstructured data such as text, natural language processing (NLP) technology is used to understand and analyze data with deep learning models, and dynamically realize automatic classification and grading of power plant business data. Power plant data can be divided into general data and core data.

[0056] Step S3: sampling and collecting power plant data.

[0057] Specifically, power plant data collection includes three forms: obtaining data between internal systems of the power plant, obtaining data from outside the system, and obtaining data from the power plant by the management system. This embodiment adopts a sampling collection method to collect the power plant data obtained through the previous steps, including general data and core data. In some processes (such as data access), a certain proportion of the latest small sample data is collected regularly. Since various types of data have the same structure of tables, fields, etc., the management cost and resource saving of subsequent data can be reduced by sampling and regular updating.

[0058] Step S4: encrypt and transmit the power plant data, monitor the data transmission process for abnormalities, and generate a data flow diagram.

[0059] Specifically, the collected small sample data transmission is encrypted and protected, including API encryption, transmission protocol encryption, etc., and differentiated encryption measures are used for core data and important data to prevent the leakage of important information during data transmission; the data transmission process is monitored for abnormalities, including system connection disconnection, malicious traffic requests, etc., to form an alarm list to avoid data transmission due to system failures, network failures or malicious attacks; a data flow diagram is generated to reflect the flow of data between various systems, and can record operational information such as the time and method of data transmission, to help power plant business personnel promptly discover hidden dangers such as illegal data flow and risk flow; establish relevant systems such as identity authentication, data encryption, monitoring and early warning to ensure the security of data transmission links; by formulating data transmission rules for flow comparison, generate alarm notifications for abnormal data flows, and further collect and analyze all data in this period to improve low-cost and feasible data management.

[0060] Step S5: Distribute and store the power plant data in the corresponding storage medium terminals, establish a data storage medium management account, regularly check the use of the storage medium, track and record the removable storage medium, and generate a data distribution map.

[0061] Specifically, the data storage media in the power plant include data servers and data management platforms of various systems, as well as computer terminals, mobile terminals, and mobile disks of power plant employees. Data storage is scattered and management is extremely difficult. The traditional data storage method is to store the collected data in a data lake or data center.

[0062] This embodiment uses an integrated device to store data, and the full amount of data is still stored in each application system. By establishing a data storage media management ledger, the media type, storage method, deployment location, encryption status, business ownership, responsible subject, etc. of the data storage are clarified, and automatic identification and manual entry are supported to uniformly manage the data storage media of the power plant; regularly verify the use of storage media, including user information, usage cycle, copy status, secondment status, etc., and track and record removable storage media; scan the database for vulnerabilities or connect with a third-party vulnerability management platform to achieve unified management of database security; generate a data distribution map to reflect the distribution of data in each storage medium, and be able to count the total number of database tables, total number of fields, total number of files, etc., and support the viewing of single or multiple data distributions; at the same time, formulate data storage system rules, regularly monitor and find abnormalities and generate alarm notifications.

[0063] Step S6: desensitize the core data, handle emergencies caused by desensitization, and block the corresponding data interface.

[0064] Specifically, unlike traditional data processing that analyzes through platform call interfaces, this embodiment adopts the platform-defined processing rules to desensitize core data and important data, and clear sensitive information contained in the data while ensuring that data availability remains unchanged, to prevent leakage of important information during the data processing process; conduct audit tracking of major emergencies in the data processing process, form an alarm list and implement emergency response, and promptly isolate and block the data interfaces of the corresponding systems to avoid the expansion of the impact of data security incidents; establish relevant systems such as data access control, data desensitization, and operation auditing to ensure the safety of the data processing environment and process.

[0065] Step S7: Establish a data provision ledger, issue an alarm for overdue usage of the provided data, and track and record the transfer of data assets.

[0066] Specifically, data provision involves the transmission of data between internal systems or from internal systems to external organizations and individuals. Possible risks include lack of approval management for data provision matters, insufficient regulatory records of data interaction processes, and insufficient security assessments of submitted data.

[0067] This embodiment adopts the method of establishing a data provision ledger to clarify the content, scope, and usage period of the provided data, and can issue an alarm for situations such as overdue use of the provided data, so as to facilitate the power plant business personnel to manage the data provision; encrypt and protect the provided data, support domestic encryption, and implement one password and one key to avoid excessive sharing and forwarding of the provided data; desensitize the core data and important data to prevent the leakage of important information during the data provision process; realize the tracking and recording of data asset transfer, and synchronously update the data asset ledger when the ownership of the data asset is changed to ensure that the account, person, object and other information of the data asset are consistent; establish a data provision management system, clarify the principles, conditions, implementation methods, approval process, filing process, security responsibilities and other contents of data provision, compare the process through the system data asset map, issue an alarm in time if there is abnormal data, and formulate a security protection plan for high-risk sensitive operations such as data sharing, publishing, transfer, and downloading.

[0068] Step S8: Establish a data destruction ledger, adopt overwrite-type clearing for general data, adopt physical destruction-type clearing for core data, and record and supervise the destruction process.

[0069] Specifically, by establishing a data destruction ledger, the type, source, content, purpose, ownership, application scenario, etc. of the destroyed data can be clarified, and the data asset ledger can be updated in a linked manner to manage data assets that meet the conditions for destruction or need to be destroyed; a data destruction tool ledger is established to clarify the type, method, deployment location, business ownership, responsible party, etc. of the destruction tools, so that the destruction tools can be managed in a unified manner; appropriate destruction measures are selected for data of different levels, including overwrite-type clearing for general data and physical destruction-type clearing for core data and important data to ensure that the destroyed data cannot be recovered; a dedicated person is appointed or a service provider with certified qualifications is designated to destroy data assets, and the destruction process is recorded and supervised; a data destruction management system is established to clarify the conditions, method, approval process, destruction process, archiving process, etc. for data destruction to form a closed-loop confirmation; for other system data, management is carried out from aspects such as approval system and process through access forms such as API to strengthen the effective management of data assets by power plant business personnel.

[0070] Exemplarily, in the process of steps S1 to S8 above, a method for managing the entire life cycle of power plant data of an embodiment of the present disclosure also includes: performing a security assessment on power plant data, establishing a data security compliance baseline, establishing a data security privacy baseline, generating a data security assessment report, and generating a problem list based on the data security assessment report.

[0071] Specifically, establish a data security compliance baseline, clarify the content and boundaries of data compliance, support multi-dimensional baseline definition, support free combination and personalized configuration of baselines, and provide a benchmark for data access control, illegal operations, etc.; establish a data security privacy baseline, clarify the objects and methods of data privacy protection, support multi-dimensional baseline definition, support free combination and personalized configuration of baselines, and provide a benchmark for data leakage prevention and privacy protection; generate a data security assessment report, which can comprehensively display information related to data security risks from different perspectives such as management personnel, operation and maintenance personnel, and users, and support the export of reports in multiple formats to help power plant safety managers discover problems early and rectify deficiencies in a timely manner, thereby reducing the serious harm caused to the power plant by hidden risks; can generate a problem list based on the data security assessment report, including the number of problems, problem status, handling time limit, assets involved, handling personnel, etc., and provide a reference for the power plant to grasp the data security protection situation through the distribution of work orders; establish a data security assessment management system, clarify the basis standards, assessment requirements, quantitative indicators, assessment methods, assessment processes, feedback processes, etc. of data security assessments, and ensure the implementation of data security work in the power plant during data asset management, data classification and grading management, and data life cycle management.

[0072] In summary, we first sort out the power plant data assets to comprehensively and clearly clarify the data assets, then form an implementable data security classification and grading method, and finally, based on the classification and grading results, protect and manage the data throughout its life cycle to ensure the security of the data throughout its life cycle.

[0073] A method for managing the entire life cycle of power plant data in an embodiment of the present disclosure reduces the cost of data protection construction, maintenance cost and labor cost by adopting a small sample sampling method, and provides the industry with a new idea for providing low-cost, feasible data life cycle security protection; an automated classification and grading method is proposed to perform standardized grading and classification of power plant data; for the first time, a complete and feasible solution is provided for the power generation industry to implement the classification and grading of power plant data, and theoretical and technical support is provided for the development of systems related to power plant data security work, thereby ensuring the security of data throughout its life cycle.

[0074] like Figure 2 As shown, another embodiment of the present disclosure provides a power plant data full life cycle management system, the system comprising:

[0075] The data collection module 230 is used to sample and collect power plant data; wherein the power plant data includes general data and core data;

[0076] The data transmission module 240 is used to encrypt and transmit the power plant data, monitor the abnormality of the data transmission process, and generate a data flow diagram;

[0077] The data storage module 250 is used to disperse and store the power plant data in the corresponding storage medium terminals, establish a data storage medium management account, regularly verify the use of storage media, track and record the removable storage media, and generate a data distribution map;

[0078] Data processing module 260, used to perform desensitization processing on core data, handle emergencies caused by desensitization processing, and block corresponding data interfaces;

[0079] The data providing module 270 is used to establish a data providing account, issue an alarm for the overdue use of the provided data, and track and record the transfer of data assets;

[0080] The data destruction module 280 is used to establish a data destruction ledger, adopt overwriting to clear general data, adopt physical destruction to clear core data, and record and supervise the destruction process.

[0081] For example, Figure 2 As shown, the power plant data full life cycle management system also includes:

[0082] The asset sorting module 210 is used to sort the power plant data, generate a data asset management ledger, and establish a data asset management view;

[0083] The classification and grading module 220 is used to automatically classify and grade the power plant data using semi-supervised learning to obtain general data and core data.

[0084] For example, Figure 2 As shown, the classification and grading module is specifically used for:

[0085] Get the power plant dataset;

[0086] Manually label a portion of the power plant data, extract the field features and similar column features of the remaining power plant data through unsupervised learning, and establish a classification and grading label feature model;

[0087] The classification and grading label feature model is used to automatically classify and grade power plant data.

[0088] For example, Figure 2 As shown, the power plant data full life cycle management system also includes:

[0089] The security assessment module 290 is used to perform security assessment on power plant data, establish a data security compliance baseline, establish a data security privacy baseline, generate a data security assessment report, and generate a problem list based on the data security assessment report.

[0090] Specifically, a power plant data full life cycle management system in an embodiment of the present disclosure is used to implement the power plant data full life cycle management method described in the above embodiment, and the specific implementation process has been described in detail in the above embodiment.

[0091] As an example, the power plant data life cycle management system can be divided into the data source layer, data processing layer, security measures layer and application layer. The data source layer classifies data according to data source and interface type, including flow probes, application probes, data security logs, network security logs, threat intelligence, etc. The data processing layer uses syslog, JDBC, API and other methods to collect data, and after pre-processing such as data cleaning, data integration, and data conversion, it is stored in databases such as ElasticSearch, MongoDB, and HDFS. The security measures layer adopts corresponding technical measures such as sensitive data identification, indicator calculation, and correlation analysis for each link in the data life cycle to achieve data asset management, threat perception, and research and analysis. The application layer provides users with data security visualization such as data asset screen and data flow screen, as well as event management functions such as event alarm, aggregation and merging, to achieve daily data security operations and realize linkage response when data security incidents occur. The JAVASpring framework can be used as the development framework of the power plant data life cycle management system. The front end uses JSP+AJAX to realize background interaction, and the back end uses SpringMVC. It can be deployed in the power plant. The production environment includes business servers and production libraries, etc. The deployment method is bypass deployment, which only requires network interconnection with the database and does not affect the business network.

[0092] A power plant data life cycle management system of the disclosed embodiment reduces the cost of data protection construction, maintenance cost and labor cost by adopting a small sample sampling method, and provides the industry with a new idea for low-cost and feasible data life cycle security protection; proposes an automatic classification and grading method to standardize the grading and classification of power plant data; for the first time, provides a complete and feasible solution for the power generation industry to realize the classification and grading of power plant data, provides theoretical and technical support for the development of systems related to power plant data security work, and ensures the security of data throughout its life cycle.

[0093] like Figure 3 As shown, another embodiment of the present disclosure provides an electronic device, including:

[0094] At least one processor 301; and a memory 302 communicatively connected to the at least one processor 301, for storing one or more programs, which, when executed by the at least one processor 301, enable the at least one processor 301 to implement the power plant data full life cycle management method described in the above embodiment.

[0095] The memory 302 and the processor 301 are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors 301 and the memory 302 together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor 301 is transmitted on a wireless medium through an antenna, and further, the antenna also receives data and transmits the data to the processor 301.

[0096] The processor 301 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management and other control functions. The memory 302 can be used to store data used by the processor 301 when performing operations.

[0097] Yet another embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the method for managing the entire life cycle of power plant data described in the above embodiment is implemented.

[0098] The computer-readable storage medium may be included in the system or electronic device of the present disclosure, or may exist independently.

[0099] Computer-readable storage media may be any tangible media that contains or stores a program, which may be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, optical fiber, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0100] The computer-readable storage medium may also include a data signal propagated in baseband or as part of a carrier wave, in which the computer-readable program code is carried. Specific examples include but are not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0101] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present disclosure, but the present disclosure is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and substance of the present disclosure, and these modifications and improvements are also considered to be within the scope of protection of the present disclosure.

Claims

1. A method for managing the entire life cycle of power plant data, characterized in that: The method comprises: Sampling and collecting power plant data; wherein the power plant data includes general data and core data; Encrypt and transmit power plant data, monitor abnormalities during data transmission, and generate data flow diagrams; Distribute and store power plant data in corresponding storage media terminals, establish a data storage media management account, regularly verify the use of storage media, track and record removable storage media, and generate data distribution maps; Desensitize the core data, handle emergencies caused by desensitization, and block the corresponding data interfaces; Establish a data provision ledger, issue warnings for overdue usage of provided data, and track and record data asset transfers; Establish a data destruction ledger, adopt overwrite-type clearing for general data, adopt physical destruction-type clearing for core data, and record and supervise the destruction process.

2. The method for managing the entire life cycle of power plant data according to claim 1, characterized in that: Before sampling and collecting the power plant data, the method further includes: Sorting out the power plant data, generating data asset management ledgers, and establishing data asset management views; Semi-supervised learning is used to automatically classify and grade power plant data to obtain general data and core data.

3. The method for managing the entire life cycle of power plant data according to claim 2, characterized in that: The automatic classification and grading of power plant data using semi-supervised learning includes: Get the power plant dataset; Manually label a portion of the power plant data, extract the field features and similar column features of the remaining power plant data through unsupervised learning, and establish a classification and grading label feature model; The classification and grading label feature model is used to automatically classify and grade power plant data.

4. The method for managing the entire life cycle of power plant data according to any one of claims 1 to 3, characterized in that: The method further comprises: Conduct security assessment on power plant data, establish a data security compliance baseline, establish a data security privacy baseline, generate a data security assessment report, and generate a problem list based on the data security assessment report.

5. A power plant data full life cycle management system, characterized in that: The system comprises: A data collection module, used for sampling and collecting power plant data; wherein the power plant data includes general data and core data; Data transmission module, used to encrypt and transmit power plant data, monitor abnormalities in the data transmission process, and generate a data flow diagram; The data storage module is used to store the power plant data in a dispersed manner in the corresponding storage medium terminal, establish a data storage medium management account, regularly verify the use of storage media, track and record removable storage media, and generate a data distribution map; The data processing module is used to desensitize the core data, handle emergencies caused by desensitization, and block the corresponding data interface; The data provision module is used to establish a data provision ledger, issue an alarm for overdue usage of the provided data, and track and record the transfer of data assets; The data destruction module is used to establish a data destruction ledger, adopt overwrite-type clearing for general data, adopt physical destruction-type clearing for core data, and record and supervise the destruction process.

6. The power plant data full life cycle management system according to claim 5 is characterized in that: The system further comprises: The asset sorting module is used to sort out the power plant data, generate data asset management ledgers, and establish data asset management views; The classification and grading module is used to automatically classify and grade power plant data using semi-supervised learning to obtain general data and core data.

7. The power plant data full life cycle management system according to claim 6, characterized in that: The classification and grading module is specifically used for: Get the power plant dataset; Manually label a portion of the power plant data, extract the field features and similar column features of the remaining power plant data through unsupervised learning, and establish a classification and grading label feature model; The classification and grading label feature model is used to automatically classify and grade power plant data.

8. The power plant data full life cycle management system according to any one of claims 5 to 7, characterized in that: The system further comprises: The security assessment module is used to conduct security assessments on power plant data, establish a data security compliance baseline, establish a data security privacy baseline, generate a data security assessment report, and generate a problem list based on the data security assessment report.

9. An electronic device, characterized in that: include: at least one processor; as well as, A memory communicatively connected to the at least one processor, for storing one or more programs, which, when executed by the at least one processor, enables the at least one processor to implement the power plant data full life cycle management method as described in any one of claims 1 to 4.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for managing the entire life cycle of power plant data described in any one of claims 1 to 4 is implemented.

Images