CN114626092A - Desensitization method, system, device and computer storage medium for multi-field data with incidence relation - Google Patents
Desensitization method, system, device and computer storage medium for multi-field data with incidence relation Download PDFInfo
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Abstract
The application relates to the technical field of information security, in particular to a desensitization method, a desensitization system, a desensitization device and a computer storage medium for multi-field data with an incidence relation, wherein the desensitization method for the multi-field data with the incidence relation comprises the following steps: setting the same target desensitization rule for the fields with the incidence relation, and setting the incidence relation of the desensitization rule according to the incidence relation between the fields by the target desensitization rule of the fields with the incidence relation; respectively generating desensitized target desensitization data corresponding to each field based on the target desensitization rules and the incidence relation among the desensitization rules; and updating the desensitized target desensitization data to a target file or a target database. According to the method and the device, the same desensitization rule is adopted for the target sensitive data with the incidence relation based on the incidence relation among the fields in the target sensitive data, so that the function of keeping the original incidence relation after desensitization of the multiple fields is realized.
Description
Technical Field
The application relates to the technical field of information security, in particular to a desensitization method, a desensitization system, a desensitization device and a computer storage medium for multi-field data with an incidence relation.
Background
With the rapid development of big data, an original data set containing a large amount of data is continuously generated, meanwhile, the original data set may contain some privacy data such as user identity card information, bank information and the like, and the original data set is applied to service analysis and development test without processing, and even some outsourcing service scenes may cause privacy disclosure. In order to reduce privacy disclosure, desensitization processing needs to be performed on the original data set, so as to obtain a desensitization data set, and the desensitization data set is used to replace real data in the original data set, so as to hide privacy data in the original data set.
The traditional desensitization mode mainly carries out desensitization processing on a single field, and when a plurality of fields have a certain incidence relation, desensitization on the single field destroys the incidence relation of the incidence field, so that the data relation is destroyed after desensitization to influence the data use of a service system.
Disclosure of Invention
In order to improve the data use that the data relation is destroyed after the desensitization of a plurality of fields of the incidence relation and affects the business system, the application provides a desensitization method, a system, a device and a computer storage medium of multi-field data with the incidence relation.
In a first aspect, the desensitization method for multi-field data with association provided by the application is implemented by the following technical scheme:
the desensitization method of multi-field data with an incidence relation comprises the following steps:
setting the same target desensitization rule for the fields with the incidence relation, and setting the incidence relation of the desensitization rule according to the incidence relation between the fields by the target desensitization rule of the fields with the incidence relation;
respectively generating desensitized target desensitization data corresponding to each field based on the target desensitization rules and the incidence relation among the desensitization rules;
and updating the desensitized target desensitization data to a target file or a target database.
In some embodiments, the setting of the same target desensitization rule for fields having an association relationship, and the setting of the association relationship of desensitization rules by the target desensitization rule for fields having an association relationship according to the association relationship between fields includes:
presetting sensitive types and desensitization rules corresponding to the sensitive types;
analyzing a file to be desensitized, and acquiring target sensitive data in the file to be desensitized from the file to be desensitized based on a preset sensitive type;
acquiring an association relation between fields in target sensitive data;
determining a target desensitization rule corresponding to fields in the target sensitive data based on the sensitive type, wherein a plurality of fields with incidence relations are set as the same target desensitization rule;
and setting the association relationship of the target desensitization rule of the field with the association relationship according to the association relationship between the fields.
In some embodiments, each of the desensitization rules includes at least one desensitization base and a desensitization transformation rule corresponding to each desensitization base.
In some embodiments, the generating desensitized target desensitization data corresponding to each field based on the target desensitization rule and the association relationship between the desensitization rules includes:
in response to desensitization requirements, determining a desensitization base selected by the target desensitization rule;
and desensitizing the target sensitive data according to the target desensitization conversion rule corresponding to the target desensitization base number selected by each target desensitization rule and the incidence relation among desensitization rules.
In some embodiments, the plurality of fields having an association relationship include a condition field and a result field, and the generating desensitized target desensitization data corresponding to each field based on the target desensitization rule and the association relationship between the desensitization rules respectively includes:
the condition field carries out desensitization operation according to a target desensitization conversion rule corresponding to the target desensitization base number selected by the target desensitization rule to obtain a target desensitization condition field;
and generating a target desensitization result field through the target desensitization condition field.
In a second aspect, the desensitization system for multi-field data with association provided by the application is implemented by the following technical solutions:
a desensitization system for multi-field data having associative relationships, comprising:
a desensitization rule model base used for storing preset sensitive types and desensitization rules corresponding to the sensitive types;
the file analysis unit is used for analyzing the file to be desensitized, acquiring target sensitive data in the file to be desensitized from the file to be desensitized based on a preset sensitive type, and acquiring an incidence relation between fields in the target sensitive data;
a desensitization rule association unit for setting an association relationship between desensitization rules according to an association relationship between fields;
a desensitization unit for generating desensitized target desensitization data corresponding to each field based on the target desensitization rules and the association relationship between the desensitization rules;
and the updating unit is used for updating the desensitized target desensitized data to the target file or the target database.
In a third aspect, the desensitization device for multi-field data with association provided by the application is implemented by the following technical scheme:
desensitization device of multi-field data having an associative relationship, comprising:
one or more processors;
a computer storage medium for storing one or more computer readable instructions,
the one or more computer readable instructions, when executed by the one or more processors, cause the one or more processors to implement the method described above.
In a fourth aspect, the present application provides a computer storage medium, which is implemented by the following technical solutions:
a computer storage medium storing one or more computer readable instructions which, when executed by a processor, cause the processor to implement the method described above.
Compared with the prior art, the desensitization method, the desensitization system, the desensitization device and the computer storage medium of the multi-field data with the incidence relation have the advantages that:
based on the incidence relation among the fields in the target sensitive data, the target sensitive data with the incidence relation adopts the same desensitization rule, so that the function of keeping the original incidence relation after desensitization of the multiple fields is realized.
Drawings
FIG. 1 is a flow chart of a desensitization method of multi-field data with associative relations provided herein;
FIG. 2 is a flowchart of step S1 in FIG. 1;
FIG. 3 is a flowchart of step S2 in FIG. 1;
fig. 4 is a block diagram of a desensitization system of multi-field data with association provided in the present application.
In the figure, 1, a desensitization rule model library; 2. a file parsing unit; 3. a desensitization rule association unit; 4. a desensitization unit; 5. and an updating unit.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on".
With the rapid development of big data, original data sets containing a large amount of data are continuously generated without any moment, and the original data sets may contain some private data, for example, in a certain file, a first amount (field a), a floating proportion of the amount (field B) and a second amount (field C) after floating of a product are involved, wherein the field a, the field B and the field C are original private data, and desensitization processing needs to be performed on such original private data sets, so as to obtain desensitization data sets. However, there may be an association relationship between these original private data, for example, in the above example, the association relationship between the a field, the B field, and the C field is the a field × B field = C field, and therefore, it is necessary to ensure that the desensitized a field, B field, and C field can still maintain the original association relationship.
As shown in fig. 1 to fig. 3, the present application first discloses a desensitization method for multi-field data having an association relationship, which can implement that a book after desensitization can still maintain an original association relationship, and is implemented by the following steps:
s11: presetting a sensitivity type and a desensitization rule corresponding to each sensitivity type.
The preset sensitive type aims to define one or more types of information as sensitive data, wherein the preset sensitive type mode comprises but is not limited to a mode of defining and configuring a sensitive type, a built-in sensitive type storage library (such as an address library, a postcode library, an ID card address code library and the like) and the like through a regular expression; after the sensitive types are preset, corresponding desensitization rules are required to be configured for each sensitive type, so that each desensitization rule can be applied to all sensitive data contained in the corresponding sensitive type, one or more types of information can be matched into the sensitive type according to desensitization requirements in the following process, and the corresponding desensitization rule is called for the matched sensitive type, so that the sensitive data under the matched sensitive type can be desensitized directly according to the desensitization rule corresponding to the matched sensitive type.
Each desensitization rule comprises at least one desensitization base number and desensitization conversion rules corresponding to each desensitization base number. In the same desensitization strategy, desensitization conversion rules corresponding to different desensitization base numbers are different, and the same target sensitive data can be controlled to be converted into different desensitization results by selecting different desensitization base numbers. In the data desensitization process, different desensitization tasks exist, namely, multiple desensitization tasks can be performed on the same file to be desensitized, and when the same desensitization strategy exists among different desensitization tasks, if the desensitization base number is not considered, the same desensitization result can be obtained by the different desensitization tasks based on the same desensitization strategy.
S12: analyzing a file to be desensitized, acquiring target sensitive data in the file to be desensitized from the file to be desensitized based on a preset sensitive type, acquiring an incidence relation among fields in the target sensitive data, and determining a target desensitization rule corresponding to the fields in the target sensitive data based on the sensitive type, wherein a plurality of fields with the incidence relation are set as the same target desensitization rule.
The method for analyzing the structure of the file to be desensitized includes, but is not limited to, recursive analysis and the like, the node value and the attribute value corresponding to each node of the file to be desensitized can be traversed by analyzing the structure of the file to be desensitized, and therefore all target sensitive data which may exist in the node value and the attribute value corresponding to each node of the file to be desensitized can be found through analysis; by directly analyzing the node values and the attribute values, sensitive data in the file to be desensitized can be found more accurately.
Taking the above example as an example, based on a preset sensitivity type, the target sensitivity data obtained from the analyzed file to be desensitized includes a product number (D field), a first amount of money of the product (a field), an amount floating proportion (B field), and a second amount of money after floating (C field), and meanwhile, the association relationship among the a field, the B field, and the C field is a field × B field = C field, and based on a preset desensitization rule corresponding to the sensitivity type, the target desensitization rules among the D field, the a field, the B field, and the C field are obtained respectively. Because there is an association relationship among the A field, the B field and the C field, the A field, the B field and the C field are set to be any and the same target desensitization rule.
S13, setting the incidence relation of the target desensitization rule of the fields with the incidence relation according to the incidence relation among the fields;
the fields having an association relationship include a condition field and a result field, for example, the association relationship among the fields a, B and C having an association relationship is the fields a × B = C, where the fields a and B are both condition fields, the field C is the result field, and then the association relationship of the target desensitization rule of the fields having an association relationship is set according to the association relationship among the fields, that is, the association relationship of the target desensitization rule respectively corresponding to the fields a, B and C is set according to the association relationship among the fields a, B and C, if the field a is amount, the field B is amplitude ratio, and the field C is actual amount, then the "amount ratio generation" desensitization rule is set for the fields a, B and C, and the desensitization rule selects setting parameters as original amount field a, floating ratio field B, and C, And the actual amount field C sets the desensitization amount field generation range to be 100-10000, and the floating proportion generation range to be 10% -100%, and then sets and completes the desensitization rule of 'amount proportion generation'.
S2: based on the target desensitization rule and the association relationship between desensitization rules, target desensitization data after desensitization corresponding to each field is generated, as shown in fig. 3, which specifically includes:
s21: in response to desensitization requirements, determining a desensitization base selected by the target desensitization rule;
s22: desensitization operation is carried out on the target sensitive data according to a target desensitization conversion rule corresponding to the target desensitization base number selected by each target desensitization rule and an incidence relation between desensitization rules, and the desensitization operation method specifically comprises the following steps:
s221: and carrying out desensitization operation on the condition field according to a target desensitization conversion rule corresponding to the target desensitization base number selected by the target desensitization rule to obtain a target desensitization condition field, and generating a target desensitization result field through the target desensitization condition field.
As in the above example, the a field and the B field are both condition fields, such as: the original data of the sum field A is 100, the generation range is set to be 100-10000 according to the desensitization rule, the new value after desensitization is 2000, the original value of the floating proportion field B is 10%, the desensitization generation range set according to the desensitization rule is 10% -100%, the value after desensitization is 30%, the target desensitization result field is generated through the target desensitization condition field, the value after actual sum field C is 2000 x 30% =600, and the value after C is 600.
S3: and updating the desensitized target desensitization data to a target file or a target database.
The application also discloses a desensitization system of multi-field data with association relationship, as shown in fig. 4, including:
a desensitization rule model base 1 for storing preset sensitive types and desensitization rules corresponding to the sensitive types;
the file analysis unit 2 is used for analyzing the file to be desensitized, acquiring target sensitive data in the file to be desensitized from the file to be desensitized based on a preset sensitive type, and acquiring an incidence relation between fields in the target sensitive data;
a desensitization rule association unit 3 for setting an association relationship between desensitization rules according to an association relationship between fields;
a desensitization unit 4 for generating desensitized target desensitization data corresponding to each field based on the target desensitization rules and the association relationship between the desensitization rules;
and the updating unit 5 is used for updating the desensitized target desensitized data to the target file or the target database.
The application also discloses a desensitization device for multi-field data with an association relationship, comprising:
one or more processors;
a computer storage medium storing one or more computer readable instructions,
the one or more computer readable instructions, when executed by the one or more processors, cause the one or more processors to implement the method described above.
The present application also discloses a computer storage medium having stored thereon one or more computer readable instructions which, when executed by a processor, cause the processor to implement the method described above. The computer storage media may include volatile memory in a computer-readable medium, and examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present application and its embodiments are described above, the description is not limited, and what is shown in the drawings is only one of the embodiments of the present application, and the actual structure is not limited thereto. In summary, those skilled in the art should appreciate that they can readily use the disclosed conception and specific embodiments as a basis for designing or modifying other structures for carrying out the same purposes of the present invention without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. A desensitization method of multi-field data having an associative relationship, comprising:
setting the same target desensitization rule for the fields with the incidence relation, and setting the incidence relation of the desensitization rule for the target desensitization rule of the fields with the incidence relation according to the incidence relation among the fields;
respectively generating desensitized target desensitization data corresponding to each field based on the target desensitization rules and the incidence relation among the desensitization rules;
and updating the desensitized target desensitization data to a target file or a target database.
2. The desensitization method of multi-field data with association according to claim 1, wherein said setting the same target desensitization rule for fields with association, and the target desensitization rule for fields with association setting the association of desensitization rules according to the association between fields comprises:
presetting sensitive types and desensitization rules corresponding to the sensitive types;
analyzing a file to be desensitized, and acquiring target sensitive data in the file to be desensitized from the file to be desensitized based on a preset sensitive type;
acquiring an association relation between fields in target sensitive data;
determining a target desensitization rule corresponding to fields in the target sensitive data based on the sensitive type, wherein a plurality of fields with incidence relations are set as the same target desensitization rule;
and setting the association relationship of the target desensitization rule of the field with the association relationship according to the association relationship between the fields.
3. The desensitization method of multi-field data having associative relationships according to claim 2, wherein each of said desensitization rules includes at least one desensitization base and desensitization conversion rules corresponding to each of said desensitization base.
4. The desensitization method of multi-field data with association relationship according to claim 3, wherein the generating desensitized target desensitization data corresponding to each field based on the target desensitization rules and the association relationship among the desensitization rules respectively comprises:
in response to desensitization requirements, determining a desensitization base selected by the target desensitization rule;
and desensitizing the target sensitive data according to the target desensitization conversion rule corresponding to the target desensitization base number selected by each target desensitization rule and the incidence relation among desensitization rules.
5. The desensitization method of multi-field data with association relationship according to claim 4, wherein several fields with association relationship include condition fields and result fields, and the generating desensitized target desensitization data corresponding to each field based on the target desensitization rule and the association relationship between desensitization rules respectively includes:
the condition field carries out desensitization operation according to a target desensitization conversion rule corresponding to the target desensitization base number selected by the target desensitization rule to obtain a target desensitization condition field;
and generating a target desensitization result field through the target desensitization condition field.
6. A desensitization system for multi-field data having associative relationships, comprising:
a desensitization rule model base (1) for storing preset sensitive types and desensitization rules corresponding to the sensitive types;
the file analysis unit (2) is used for analyzing the file to be desensitized, acquiring target sensitive data in the file to be desensitized from the file to be desensitized based on a preset sensitive type, and acquiring an association relation between fields in the target sensitive data;
a desensitization rule association unit (3) for setting an association relationship between desensitization rules according to an association relationship between fields;
a desensitization unit (4) used for generating desensitized target desensitization data corresponding to each field based on the target desensitization rules and the incidence relation among the desensitization rules;
and the updating unit (5) is used for updating the desensitized target desensitized data to the target file or the target database.
7. Desensitization device of multi-field data having an associative relationship, comprising:
one or more processors;
a computer storage medium storing one or more computer readable instructions,
the one or more computer readable instructions, when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-5.
8. Computer storage medium, characterized in that one or more computer readable instructions are stored which, when executed by a processor, cause the processor to carry out the method according to any one of claims 1 to 5.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115952547A (en) * | 2023-02-15 | 2023-04-11 | 北京景安云信科技有限公司 | Database desensitization device and method based on protocol analysis |
| CN116776351A (en) * | 2023-06-21 | 2023-09-19 | 中国民用航空总局第二研究所 | Preserving format encryption method and system for personal information to resist statistical analysis attack |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115952547A (en) * | 2023-02-15 | 2023-04-11 | 北京景安云信科技有限公司 | Database desensitization device and method based on protocol analysis |
| CN115952547B (en) * | 2023-02-15 | 2024-04-19 | 北京景安云信科技有限公司 | Database desensitizing device and method based on protocol analysis |
| CN116776351A (en) * | 2023-06-21 | 2023-09-19 | 中国民用航空总局第二研究所 | Preserving format encryption method and system for personal information to resist statistical analysis attack |
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