CN115659407A - Data asset processing method, device and medium - Google Patents
Data asset processing method, device and medium Download PDFInfo
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- CN115659407A CN115659407A CN202211610846.8A CN202211610846A CN115659407A CN 115659407 A CN115659407 A CN 115659407A CN 202211610846 A CN202211610846 A CN 202211610846A CN 115659407 A CN115659407 A CN 115659407A
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Abstract
The present disclosure provides a data asset processing method, comprising: determining a general data classification strategy; receiving a sensitive data type designation instruction; determining a target data type and characteristic information of the target data type according to the sensitive data type designation instruction; determining a target data hierarchical classification strategy according to the general data hierarchical classification strategy and the target data type; scanning a plurality of asset components, and determining data corresponding to the asset components, wherein the data corresponding to the asset components are data uploaded by remote equipment; classifying and grading the data corresponding to each asset component according to the target data security grading classification strategy to obtain a corresponding classification result and a corresponding grading result; and generating a display control signal according to the obtained classification result and the obtained grading result. The present disclosure also provides an electronic device and a computer-readable medium.
Description
Technical Field
The present disclosure relates to the field of data security, and in particular, to a data asset processing method, an electronic device, and a computer readable medium.
Background
The classification and classification of data security is an important link for realizing data security, and the commonly used classification and classification method of data security comprises the following steps: reading classification data to be classified from a database; matching keywords according to a classification strategy; and determining the classification and the grade of each item of data. After the data is classified and classified, the data can be managed according to the corresponding category and grade.
How to further improve the data asset security becomes a technical problem to be solved urgently in the field.
Disclosure of Invention
The embodiment of the disclosure provides a data asset processing method, electronic equipment and a computer readable medium.
As a first aspect of the present disclosure, there is provided a data asset processing method including:
determining a general data classification strategy;
receiving a sensitive data type designation instruction;
determining a target data type and characteristic information of the target data type according to the sensitive data type designation instruction;
determining a target data hierarchical classification strategy according to the general data hierarchical classification strategy and the target data type;
scanning a plurality of asset components, and determining data corresponding to the asset components, wherein the data corresponding to the asset components are data uploaded by remote equipment;
classifying and grading the data corresponding to each asset component according to the target data security grading classification strategy to obtain a corresponding classification result and a corresponding grading result;
and generating a display control signal according to the obtained classification result and the obtained grading result.
Optionally, the data asset processing method further includes:
and sending the obtained classification result and the classification result to corresponding remote equipment.
Optionally, the type of the asset component is selected from the following types:
big data component, relational database component, non-relational database component.
Optionally, the data asset processing method further includes:
receiving a modification instruction;
analyzing the modification instruction to obtain a data type carried in the modification instruction and characteristic information corresponding to the data type;
and modifying the existing target data security classification strategy according to the modification instruction to obtain a modified target data security classification strategy.
Optionally, the target data type includes a private data type, and the characteristic information of the target data type includes personal identity information and/or personal service usage information.
Optionally, the classification result includes at least one of the following information:
class name, class code, and security level of the class.
Optionally, the ranking result comprises at least one of the following information:
hierarchical name, hierarchical code, hierarchical color label, management and control rule.
Optionally, the data asset processing method is performed periodically.
As a second aspect of the present disclosure, there is provided an electronic apparatus including:
one or more processors;
a memory having one or more programs stored thereon that, when executed by the one or more processors, cause the one or more processors to implement the data asset processing method.
As a third aspect of the present disclosure, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the data asset processing method.
The general data classification strategy is a data classification strategy uniformly formulated by a security management department of a big data bureau and can be obtained by looking up related files.
The "sensitive data type designation instruction" is determined based on the business type of the data asset, and the specific business scenario.
For example, the sensitive data type may be private data of a business user, such as personal identity information of an individual and/or personal service usage information. Of course, the present disclosure is not so limited.
When the data in each asset assembly is classified by combining a general data classification strategy, a specified sensitive data type and a specified target data classification strategy, the data can be classified and classified accurately, and the sensitive data can be highlighted and emphasized, so that the management of data assets is facilitated.
The classified data to be classified is uploaded by the asset component, so that the corresponding database does not need to be read when the data is classified and classified, and the risk of data leakage caused by reading the data in the database is avoided.
And moreover, the data to be classified are uploaded by the asset component, a database does not need to be logged in, and the risk of leakage of the account number and the password of the database is avoided.
And after the data corresponding to each asset assembly is classified and graded, generating a display control signal. The display device can display the classification result and the classification result according to the display control signal, so that the data assets can be managed more conveniently.
Drawings
FIG. 1 is a flow chart of one embodiment of a data asset processing method provided by a first aspect of the present disclosure;
FIG. 2 is a flow diagram of another embodiment of a data asset processing method provided by the present disclosure;
FIG. 3 is a flow diagram of a portion of yet another embodiment of a data asset processing method provided by the present disclosure;
FIG. 4 is a schematic diagram of an electronic device provided by the present disclosure;
fig. 5 is a schematic diagram of a computer-readable medium provided by the present disclosure.
Detailed Description
In order to make those skilled in the art better understand the technical solutions of the present disclosure, the data asset processing method, the electronic device, and the computer readable medium provided in the present disclosure are described in detail below with reference to the accompanying drawings.
Example embodiments will be described more fully hereinafter with reference to the accompanying drawings, but which may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Embodiments of the disclosure and features of the embodiments may be combined with each other without conflict.
As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," 8230; \8230 "; when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
In the related art, a classification and classification strategy is formulated by a security expert, the security expert needs to use a database account and a password when logging in a system, and the risk of leakage of the database account and the password exists. In addition, there is also a risk of data leakage during the reading of database data.
As a first aspect of the present disclosure, as shown in fig. 1, there is provided a data asset processing method including:
in step S110, a generic data hierarchical classification policy is determined;
in step S120, a sensitive data type specifying instruction is received;
in step S130, determining a target data type and characteristic information of the target data type according to the sensitive data type specifying instruction;
in step S140, determining a target data classification policy according to the general data classification policy and the target data type;
in step S150, scanning a plurality of asset components, and determining data corresponding to the plurality of asset components, where the data corresponding to the asset components is data uploaded by a remote device;
in step S160, classifying and classifying the data corresponding to each asset component according to the target data security classification policy to obtain a corresponding classification result and a corresponding classification result;
in step S170, a display control signal is generated according to the obtained classification result and the obtained classification result.
The general data classification strategy is a data classification strategy uniformly formulated by a security management department of a big data bureau and can be obtained by looking up related files.
The "sensitive data type designation instruction" is determined based on the business type of the data asset, and the specific business scenario.
For example, the sensitive data type may be private data of a business user, such as personal identity information of an individual and/or personal service usage information. Of course, the present disclosure is not so limited.
When the data in each asset component is classified, the data can be classified and classified accurately, and the sensitive data can be highlighted and emphasized, so that the management of the data assets is facilitated.
As described in step S150, the classified data is uploaded by the asset component, and thus, when classifying and classifying the data, the corresponding database does not need to be read, thereby avoiding the risk of data leakage caused by reading the data in the database.
And moreover, the data to be classified are uploaded by the asset component, a database does not need to be logged in, and the risk of leakage of the account number and the password of the database is avoided.
And after the data corresponding to each asset assembly is classified and graded, generating a display control signal. The display device can display the classification result and the classification result according to the display control signal, and management of the data assets is facilitated.
In the present disclosure, how to display the classification result and the classification result is not particularly limited. The results within the taxonomy and the ranking results are presented, for example, in a tree and/or list format.
For convenience of management, optionally, as shown in fig. 2, the data asset processing method further includes:
in step S180, the obtained classification result and classification result are sent to the corresponding remote device.
It should be noted that the "remote device" refers to a user of the asset component, and after issuing the corresponding classification result and the classification result to the remote device, a manager of the remote device may specify the classification result and the classification result of the data reported by the remote device.
As an alternative embodiment, the type of the asset component is selected from the following types:
big data component, relational database component, non-relational database component.
Optionally, the big data component may include at least one of a hadoop, hbase, hive, etc. big data component, the relational database component may include at least one of mysql, postgreSQL, etc. relational database, and the non-relational database component may include a mongoDB, etc. non-relational database.
As an alternative embodiment, as shown in fig. 3, the data asset processing method further includes:
in step S191, a modification instruction is received;
in step S192, the modification instruction is analyzed to obtain a data type carried in the modification instruction and feature information corresponding to the data type;
in step S193, the modification instruction modifies the existing target data security classification policy to obtain a modified target data security classification policy.
In the method and the device, the target data security classification strategy can be modified according to business requirements and management requirements, so that classification results and classification results can meet corresponding requirements.
As an optional implementation, the classification result includes at least one of the following information:
class name, class code, and security level of the class.
As an alternative to whether that dog is, the ranking result includes at least one of the following information:
hierarchical name, hierarchical code, hierarchical color label, management and control rule.
Optionally, the data asset processing method is performed periodically.
Therefore, in the present disclosure, the target data security classification policy may be modified once at intervals, and the data to be classified and classified may be received in real time, so that the requirement of data asset management may be better satisfied.
As a second aspect of the present disclosure, there is provided an electronic apparatus, as shown in fig. 4, including:
one or more processors 101;
a memory 102 having one or more programs stored thereon which, when executed by the one or more processors 101, cause the one or more processors to implement a data asset processing method according to the first aspect of the disclosure.
Optionally, the electronic device may further include one or more I/O interfaces 103 connected between the processor and the memory, and configured to implement information interaction between the processor and the memory.
The processor 101 is a device with data processing capability, which includes but is not limited to a Central Processing Unit (CPU), etc.; memory 102 is a device having data storage capabilities including, but not limited to, random access memory (RAM, more specifically SDRAM, DDR, etc.), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), FLASH memory (FLASH); an I/O interface (read/write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, which includes but is not limited to a data Bus (Bus) and the like.
In some embodiments, the processor 101, memory 102, and I/O interface 103 are interconnected via the bus 104, which in turn connects with other components of the computing device.
As a third aspect of the present disclosure, as shown in fig. 5, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the data asset processing method according to the first aspect of the present disclosure.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted in a generic and descriptive sense only and not for purposes of limitation. In some instances, features, characteristics and/or elements described in connection with a particular embodiment may be used alone or in combination with features, characteristics and/or elements described in connection with other embodiments, unless expressly stated otherwise, as would be apparent to one skilled in the art. Accordingly, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the disclosure as set forth in the appended claims.
Claims (10)
1. A data asset processing method, comprising:
determining a general data classification strategy;
receiving a sensitive data type designation instruction;
determining a target data type and characteristic information of the target data type according to the sensitive data type designation instruction;
determining a target data classification strategy according to the general data classification strategy and the target data type;
scanning a plurality of asset components, and determining data corresponding to the plurality of asset components, wherein the data corresponding to the asset components are data uploaded by remote equipment;
classifying and grading the data corresponding to each asset component according to the target data security grading classification strategy to obtain a corresponding classification result and a corresponding grading result;
and generating a display control signal according to the obtained classification result and the obtained grading result.
2. The data asset processing method of claim 1, wherein the data asset processing method further comprises:
and sending the obtained classification result and classification result to corresponding remote equipment.
3. The data asset processing method of claim 1, wherein the asset component is of a type selected from the following:
big data component, relational database component, non-relational database component.
4. The data asset processing method according to any one of claims 1 to 3, wherein the data asset processing method further comprises:
receiving a modification instruction;
analyzing the modification instruction to obtain a data type carried in the modification instruction and characteristic information corresponding to the data type;
and modifying the existing target data security classification strategy according to the modification instruction to obtain a modified target data security classification strategy.
5. The data asset processing method as claimed in any one of claims 1 to 3, wherein the target data type comprises a private data type, and the characteristic information of the target data type comprises personal identity information and/or personal service usage information.
6. The data asset processing method as claimed in any one of claims 1 to 3, wherein the classification result comprises at least one of the following information:
class name, class code, and security level of the class.
7. The data asset processing method of any of claims 1 to 3, wherein the ranking result comprises at least one of the following information:
hierarchical name, hierarchical code, hierarchical color label, management and control rule.
8. The data asset processing method according to any of claims 1 to 3, wherein the data asset processing method is performed periodically.
9. An electronic device, comprising:
one or more processors;
memory having one or more programs stored thereon that, when executed by the one or more processors, cause the one or more processors to implement the data asset processing method of any of claims 1 to 8.
10. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out a data asset processing method according to any one of claims 1 to 8.
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- 2022-12-15 CN CN202211610846.8A patent/CN115659407A/en active Pending
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| US20130086076A1 (en) * | 2011-09-30 | 2013-04-04 | International Business Machines Corporation | Refinement and calibration mechanism for improving classification of information assets |
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