CN112241543A - Sensitive data combing method based on data middling stage - Google Patents
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- 238000002360 preparation method Methods 0.000 claims abstract description 10
- 238000005516 engineering process Methods 0.000 claims abstract description 7
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- 238000000586 desensitisation Methods 0.000 claims description 13
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
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Abstract
The invention discloses a sensitive data combing method based on a data center, which comprises the following steps: s1, a carding preparation stage, which is used for ensuring smooth and efficient implementation of the current carding work of the platforms in the data; s2, analyzing and discussing, and summarizing combing results; and S3, a combing summary and analysis stage, wherein the current situation of the stations in the data is summarized and analyzed according to the combing information combed by the stages S1 and S2. In the existing access control and authority management strategy, a development route of a security protection technology for clearing sensitive data is researched to study whether Maxcomputer and Dataworks have authorization control based on a data sensitive label mode and authorization control based on a sensitive data grade mode, or whether Maxcomputer and Dataworks have authorization control based on a data sensitive label mode and authorization control based on a sensitive data grade mode or whether Maxcomputer and Dataworks are supported by a third-party tool, authorization access control based on a sensitive label or a sensitive grade is realized through clearing sensitive data distribution conditions and classification grading conditions in a data center, and sensitive data is combed and integrated.
Description
Technical Field
The invention belongs to the technical field of big data middleboxes, and particularly relates to a sensitive data combing method based on a data middlebox.
Background
In recent years, digital economy is developed vigorously, and data not only become national basic strategic resources, but also are key production elements for promoting the innovative development of the economy and the society of enterprises. In the big data era, the types of massive original data in the data comprise personal privacy information (including information types such as customer names, identification card numbers, contact phones, bank card numbers, electric charge records, unit names, jobs and the like) of customers existing in key core systems of enterprises such as finance, marketing and the like, the user needs to be rapidly mined and guided in massive data, and services such as data assets, data monitoring, data analysis and the like are provided.
However, due to the aggregation of mass data, the transformation of data assets, and the efficient utilization of data analysis and mining, the value of company data has prompted brand-new industrial forms and business models, and the data creates great value for companies and faces severe data safety risks. With the prominent commercial value of data resources, the attacks of the data resources, such as lasso, stealing, abuse, tampering and the like, are continuously inundated, and the characteristics of industrialization, high-tech, transnational and the like are presented, so that a brand-new challenge is provided for the operation safety of national key information infrastructure and the enterprise data safety management capability. Important data security events of various industries occur frequently, the destructive power is extremely strong, and the method becomes an important security issue concerned by the whole society.
With the continuous promulgation of relevant policies, laws and the like in the aspect of data security in China and various industries, the attention degree of data security is continuously upgraded, and the data security is relevant to national security and enterprise security. The importance of data security as the "last mile" of cyberspace security tasks has been recognized by countries and enterprises. With the continuous expansion of the data in the company data and the continuous increase of data security threats, the company needs to combine the overall architecture and the current security protection situation of the data center, form the scientifically used 'systematic data security protection and security management capability' by using the sensitive data protection core and surrounding the sensitive data security key technology on the basis of the analysis and the security management of the sensitive data in the data center, and ensure that the sensitive data security continuously reaches the known, controllable, manageable and searchable construction target.
Disclosure of Invention
The invention aims to provide a sensitive data combing method based on a data center station, which aims to solve the problems in the prior art in the background technology.
In order to achieve the purpose, the invention adopts the following technical scheme:
a sensitive data combing method based on a data center comprises the following steps:
s1, a carding preparation stage, wherein in order to ensure smooth and efficient implementation of the current carding work of the platform in the data, the related current situation and requirements in the carding implementation process are comprehensively known and mastered, the project carding work is better implemented, and the starting, preparation and other works of the carding work are required before the carding work is comprehensively implemented, and the carding preparation stage comprises the following steps:
s1.1, firstly, determining a carding group, and confirming the carding range and time;
s1.2, implementing a carding mode, deeply discussing a carding group, determining a method for forming a research result by taking the carding of the basic condition of the data center as an objective basis and combining the safety situation of data inside and outside the industry and expert discussion opinions;
s1.3, thirdly, forming a data center station current situation carding table through the discussion and the perfection of the carding group, and developing the comprehensive discussion and carding work of the special subjects on the site of the user by the carding group;
s1.4, recovering, sorting and analyzing a carding table, and extracting conclusive information from a carding result through statistics and analysis by a carding group;
s2, in the analysis and discussion phase, the combing results are collected to form conclusive opinions, the key points of data security of a data center station are concerned, the data security situation in the industry is integrated, and the combing group experts discuss, analyze and summarize together with the experience, information and the like of users and the inside and outside of the industry in the aspects of data security management and data security protection technical measures;
and S3, a combing summarizing and analyzing stage, wherein the current situation of the data center station is summarized and analyzed according to combing information combed in the stages S1 and S2, combing feedback is collected, threats and risks are found, data security threats and risks are evaluated, sensitive data management key technical research indexes are obtained by combining the security requirements of the data center station, combing results are summarized and analyzed, a combing analysis report is formed, and suggestions are provided for the data security key problems in the data center station.
Preferably, the data center station comprises data access: various kinds of business data outside the data center station are converged to a data center station source layer through technical tools such as data replication (DTS), ETL (ETL) (dataworks), a data bus (DataHub) and the like, the data mainly comprise structured data, unstructured data, collected measurement data, format files and message data of specific protocols, and the source end can be various business systems, an internet of things platform, ubiquitous terminal equipment and an external third-party service provider
Preferably, the data center station comprises data storage computing: the storage computing capability is a data center data core processing engine, data generated by various source end systems are stored in the data center to form global data, the global data are processed, arranged and extracted into various subject data through a big data computing technology and a data model, and scenes such as data computing scene separation line computing, real-time computing, unstructured processing and the like are obtained.
Preferably, the data center station comprises data analysis: various analysis models and analysis algorithms are provided, and a tool set is provided for data reports, label portraits and visual display.
Preferably, the data center station includes data asset management: the method is used for comprehensively controlling models, catalogues, data labels, data quality and the like of a data asset system.
Preferably, the data center station comprises data operation management: the method provides various management support components for the use process of a data center station, performs parameter configuration on data service, desensitization rules and the like, performs safety monitoring and scheduling measurement on links, provides an online interaction function for data development, and is a basic component set for realizing the monitoring of the full life cycle of data.
Preferably, the data center station comprises a data service: the safe, friendly and controllable unified access to internal and external data services is realized through the data service directory, and the unified registration, management and scheduling of API service interfaces in various forms such as Restful are provided.
Preferably, the interface for externally providing data sharing for the data center is realized by a cloud shield-data security component, so that the external service Restful API is ensured to be called by a third party, the security of interface calling is ensured through API authentication and authentication, a secure transmission channel is provided, and the integrity requirement after data transmission is ensured.
The invention has the technical effects and advantages that: compared with the prior art, the sensitive data combing method based on the data center has the following advantages that:
in the existing access control and authority management strategy, a development route of a security protection technology for clearing sensitive data is researched to study whether Maxcomputer and Dataworks have authorization control based on a data sensitive label mode and authorization control based on a sensitive data grade mode, or whether Maxcomputer and Dataworks have authorization control based on a data sensitive label mode and authorization control based on a sensitive data grade mode or whether Maxcomputer and Dataworks are supported by a third-party tool, authorization access control based on a sensitive label or a sensitive grade is realized through clearing sensitive data distribution conditions and classification grading conditions in a data center, and sensitive data is combed and integrated.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. The specific embodiments described herein are merely illustrative of the invention and do not delimit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a sensitive data combing method based on a data center, which comprises the following steps:
s1, a carding preparation stage, wherein in order to ensure smooth and efficient implementation of the current carding work of the platform in the data, the related current situation and requirements in the carding implementation process are comprehensively known and mastered, the project carding work is better implemented, and the starting, preparation and other works of the carding work are required before the carding work is comprehensively implemented, and the carding preparation stage comprises the following steps:
s1.1, firstly, determining a carding group, and confirming the carding range and time;
s1.2, implementing a carding mode, deeply discussing a carding group, determining a method for forming a research result by taking the carding of the basic condition of the data center as an objective basis and combining the safety situation of data inside and outside the industry and expert discussion opinions;
s1.3, thirdly, forming a data center station current situation carding table through the discussion and the perfection of the carding group, and developing the comprehensive discussion and carding work of the special subjects on the site of the user by the carding group;
s1.4, recovering, sorting and analyzing a carding table, and extracting conclusive information from a carding result through statistics and analysis by a carding group;
s2, in the analysis and discussion phase, the combing results are collected to form conclusive opinions, the key points of data security of a data center station are concerned, the data security situation in the industry is integrated, and the combing group experts discuss, analyze and summarize together with the experience, information and the like of users and the inside and outside of the industry in the aspects of data security management and data security protection technical measures;
and S3, a combing summarizing and analyzing stage, wherein the current situation of the data center station is summarized and analyzed according to combing information combed in the stages S1 and S2, combing feedback is collected, threats and risks are found, data security threats and risks are evaluated, sensitive data management key technical research indexes are obtained by combining the security requirements of the data center station, combing results are summarized and analyzed, a combing analysis report is formed, and suggestions are provided for the data security key problems in the data center station.
Defining the range of sensitive data assets, defining sensitive level auditing and warning strategies for equipment such as database auditing and the like, considering the deployment of a data security situation perception platform, collecting data security equipment logs and warning information which mainly comprise data asset access and operation, and analyzing the attack trend and situation analysis in the aspect of data security based on the dimensionality of the data assets.
The external API interface on the data center platform realizes the calling and sharing of a data layer, if data is not desensitized, data leakage can be caused, for the API of the interface, the specification is recommended to carry out real-time desensitization on the sensitive data accessed by the API according to desensitization rules, and meanwhile, auditing and monitoring are carried out on the data access behavior of the API, so that abnormality can be found in time.
The data center station comprises data access: various kinds of business data outside the data center station are converged to a data center station source layer through technical tools such as data replication (DTS), ETL (ETL) (dataworks), a data bus (DataHub) and the like, the data mainly comprise structured data, unstructured data, collected measurement data, format files and message data of specific protocols, and the source end can be various business systems, an internet of things platform, ubiquitous terminal equipment and an external third-party service provider
The data center station comprises data storage calculation: the storage computing capability is a data center data core processing engine, data generated by various source end systems are stored in the data center to form global data, the global data are processed, arranged and extracted into various subject data through a big data computing technology and a data model, and scenes such as data computing scene separation line computing, real-time computing, unstructured processing and the like are obtained.
The data center station comprises data analysis: various analysis models and analysis algorithms are provided, and a tool set is provided for data reports, label portraits and visual display.
The data center station comprises data asset management: the method is used for comprehensively controlling models, catalogues, data labels, data quality and the like of a data asset system.
The data center station comprises data operation management: the method provides various management support components for the use process of a data center station, performs parameter configuration on data service, desensitization rules and the like, performs safety monitoring and scheduling measurement on links, provides an online interaction function for data development, and is a basic component set for realizing the monitoring of the full life cycle of data.
The data center station comprises data service: the safe, friendly and controllable unified access to internal and external data services is realized through the data service directory, and the unified registration, management and scheduling of API service interfaces in various forms such as Restful are provided.
The interface for externally providing data sharing by the console in the data is realized by a cloud shield-data security component, the calling of a third party is ensured in a mode of externally serving a Restful API, the safety of the interface calling is ensured through API authentication and authentication, a secure transmission channel is provided, and the integrity requirement after data transmission is ensured.
In this embodiment, the general level has the specification and control on data flow, but the monitoring on sensitive data flow is not used, and the data flow mainly involves data flow of several levels, and the following aspects are mainly implemented:
the first is data interface: the data interface provided by the data center station to the application layer is realized by a data works component data service module. The interface calls the unsafe data input to carry out the operations of escape, filtration and the like; recording all access behaviors to the data interface, wherein the provided interface uses an encryption channel;
secondly, batch data sharing: the interface shared by external batch is realized by a cloud shield-data security component;
thirdly, data management and operation use: and the permission control and monitoring of data operation are realized by the components such as Maxcomputer, and the access quantity, the access trend, the derived quantity, the derived details and the like of the sensitive data configured based on the rules are displayed in real time.
And fourthly, data desensitization uses a data protection umbrella desensitization component to mainly provide sensitive information identification and sensitive information desensitization functions.
The desensitization specification of the sensitive data is determined, a third-party desensitization component is promoted or deployed to achieve desensitization processing of the sensitive data, and data desensitization in the flow can be achieved in a desensitization API interface sharing mode.
The data security situation perception platform can be considered to be deployed, data security equipment logs and alarm information which mainly comprise data asset access and operation are collected, and attack trends and situation analysis in the aspect of data security are analyzed based on dimensionality of the data assets, so that process detection of sensitive data flowing is achieved.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.
Claims (8)
1. A sensitive data combing method based on a data center station is characterized in that: the method comprises the following steps:
s1, a carding preparation stage, wherein in order to ensure smooth and efficient implementation of the current carding work of the platform in the data, the related current situation and requirements in the carding implementation process are comprehensively known and mastered, the project carding work is better implemented, and the starting, preparation and other works of the carding work are required before the carding work is comprehensively implemented, and the carding preparation stage comprises the following steps:
s1.1, firstly, determining a carding group, and confirming the carding range and time;
s1.2, implementing a carding mode, deeply discussing a carding group, determining a method for forming a research result by taking the carding of the basic condition of the data center as an objective basis and combining the safety situation of data inside and outside the industry and expert discussion opinions;
s1.3, thirdly, forming a data center station current situation carding table through the discussion and the perfection of the carding group, and developing the comprehensive discussion and carding work of the special subjects on the site of the user by the carding group;
s1.4, recovering, sorting and analyzing a carding table, and extracting conclusive information from a carding result through statistics and analysis by a carding group;
s2, in the analysis and discussion phase, the combing results are collected to form conclusive opinions, the key points of data security of a data center station are concerned, the data security situation in the industry is integrated, and the combing group experts combine the experience and information of users and the inside and outside of the industry in the aspects of data security management and data security protection technical measures to jointly discuss, analyze and summarize;
and S3, a combing summarizing and analyzing stage, wherein the current situation of the data center station is summarized and analyzed according to combing information combed in the stages S1 and S2, combing feedback is collected, threats and risks are found, data security threats and risks are evaluated, sensitive data management key technical research indexes are obtained by combining the security requirements of the data center station, combing results are summarized and analyzed, a combing analysis report is formed, and suggestions are provided for the data security key problems in the data center station.
2. The sensitive data combing method based on the data center station as claimed in claim 1, characterized in that: the data center station comprises data access: various kinds of business data outside the data center station are converged to a data center station source layer through data replication (DTS), ETL (ETL) (data works) and data bus (DataHub) technical tools, the data mainly comprise structured data, unstructured data, collected measurement data, format files and message data of specific protocols, and the source end can be various business systems, an internet of things platform, ubiquitous terminal equipment and an external third-party service provider.
3. The sensitive data combing method based on the data center station as claimed in claim 1, characterized in that: the data center station comprises data storage calculation: the storage computing capability is a data center data core processing engine, data generated by various source end systems are stored in the data center to form global data, the global data are processed, arranged and extracted into various subject data through a big data computing technology and a data model, and a data computing scene is subjected to split line computing, real-time computing and unstructured processing scenes.
4. The sensitive data combing method based on the data center station as claimed in claim 1, characterized in that: the data center station comprises data analysis: various analysis models and analysis algorithms are provided, and a tool set is provided for data reports, label portraits and visual display.
5. The sensitive data combing method based on the data center station as claimed in claim 1, characterized in that: the data center station comprises data asset management: the method is used for comprehensively controlling the model, the catalogue, the data label and the data quality of a data asset system.
6. The sensitive data combing method based on the data center station as claimed in claim 1, characterized in that: the data center station comprises data operation management: the method provides various management support components for the use process of a data center station, performs parameter configuration on data service and desensitization rules, performs safety monitoring and scheduling measurement on links, provides an online interaction function for data development, and is a basic component set for realizing the monitoring of the full life cycle of data.
7. The sensitive data combing method based on the data center station as claimed in claim 1, characterized in that: the data center station comprises data service: the safe, friendly and controllable unified access to internal and external data services is realized through the data service directory, and the unified registration, management and scheduling of API service interfaces in various forms of Restful are provided.
8. The sensitive data combing method based on the data center station as claimed in claim 1, characterized in that: the interface for externally providing data sharing by the console in the data is realized by a cloud shield-data security component, the calling of a third party is ensured in a mode of externally serving a Restful API, the safety of the interface calling is ensured through API authentication and authentication, a secure transmission channel is provided, and the integrity requirement after data transmission is ensured.
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| CN114866532A (en) * | 2022-04-25 | 2022-08-05 | 安天科技集团股份有限公司 | Method, device, equipment and medium for uploading security check result information of endpoint file |
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| CN116541382A (en) * | 2023-02-23 | 2023-08-04 | 广东东联信创信息技术有限公司 | Data management method and system based on data security identification level |
| CN116541382B (en) * | 2023-02-23 | 2023-11-14 | 邵阳学院 | Data management method and system based on data security identification level |
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