CN112966299A - Data desensitization system and method based on JSON analysis - Google Patents
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Abstract
The invention provides a data desensitization system and method based on JSON analysis, and relates to the field of data processing. A data desensitization system based on JSON analysis comprises: JSON path scanning module: JSON paths used for respectively analyzing a plurality of documents; a column-wise conversion module: the document data is traversed according to the JSON path, and the same values of the JSON path are combined into a list to obtain column type storage intermediate data; a sensitive scanning module: the JSON path processing unit is used for respectively carrying out sensitive scanning on the JSON path and values corresponding to the JSON path to obtain a sensitive JSON path list; a data desensitization module: the sensitive JSON path is used for performing traversal desensitization on all document data according to the sensitive JSON path; in addition, the invention also provides a MongoDB desensitization method based on JSON analysis, which is realized by the system.
Description
Technical Field
The invention relates to the field of data processing, in particular to a data desensitization system and method based on JSON analysis.
Background
With the popularization of big data application in the information age, huge business values of the big data are gradually mined, and a big data platform fully analyzes and mines the intrinsic values of the data by integrating all data, so that data statistics, analysis, data products and data services are provided for decision makers.
The access data of the large data platform may include privacy and sensitive information of many users, such as mobile phone numbers, addresses and the like of the users, and the data may be leaked at risk. The large data platform generally guarantees data security through technologies such as user authentication, authority management and data encryption, but the data security cannot be guaranteed technically completely. On the other hand, personnel without access to the user data authority may also have the requirement of analyzing and mining the data, and the access restriction of the data greatly limits the range of fully mining the data value. In the actual production process, the application scene is more complicated, the actual requirement cannot be met only by controlling the data access authority, and other desensitization means are required to be combined. The existing desensitization method cannot meet the JSON data use of various complex structures.
Disclosure of Invention
The invention aims to provide a data desensitization system based on JSON analysis, which can support JSON data of various complex structures to be used.
Another object of the present invention is to provide a data desensitization method based on JSON parsing, which can support the use of JSON data with various complex structures.
The embodiment of the invention is realized by the following steps:
in a first aspect, an embodiment of the present application provides a data desensitization system based on JSON analysis, including:
JSON path scanning module: JSON paths used for respectively analyzing a plurality of documents;
a column-wise conversion module: the document data is traversed according to the JSON path, and the same values of the JSON path are combined into a list to obtain column type storage intermediate data;
a sensitive scanning module: the JSON path processing unit is used for respectively carrying out sensitive scanning on the JSON path and values corresponding to the JSON path to obtain a sensitive JSON path list;
a data desensitization module: and the method is used for performing traversal desensitization on all the document data according to the sensitive JSON path.
In some embodiments of the present invention, the JSON path scan module extracts a plurality of documents in a collection.
In some embodiments of the present invention, the JSON path includes array nodes and child nodes.
In some embodiments of the present invention, the values of the JSON path and the JSON path each comprise a null value.
In some embodiments of the present invention, the sensitive scan module is configured to, after the sensitive scan, judge whether a last-stage name, a parent-stage structure, and a sensitive type of a value of the JSON path are the same, and merge values of a plurality of JSON paths having the same last-stage name, parent-stage structure, and sensitive type.
In some embodiments of the invention, the sensitive scan module is configured to merge values of a plurality of said JSON paths having the same last level name, parent structure and sensitive type into a last level name, parent structure and sensitive type.
In some embodiments of the present invention, the data desensitization module is configured to, after analyzing the values of the JSON path and the JSON path, perform desensitization processing on the values when the JSON path and the sensitive JSON path are matched.
In a second aspect, an embodiment of the present application provides a JSON-analysis-based montgodb desensitization method, including the following steps:
JSON path scanning: extracting a plurality of documents in a set, analyzing JSON paths in each document, and combining results;
and (3) column conversion: traversing the document data again according to the JSON path, and combining the same values of the JSON path into a list to obtain column type storage intermediate data;
sensitive scanning: respectively carrying out sensitive scanning on the JSON path and the value corresponding to the JSON path to obtain a sensitive JSON path list;
data desensitization: and traversing desensitization is carried out on all the document data according to the sensitive JSON path.
In some embodiments of the invention, the sensitive scanning comprises: and after the sensitive scanning, judging whether the last-stage name, the parent-stage structure and the sensitive type of the JSON path value are the same, and merging the multiple JSON path values with the same last-stage name, parent-stage structure and sensitive type.
In some embodiments of the invention, the data desensitization comprises: and analyzing the JSON path and the value of the JSON path, and performing desensitization processing on the value when the JSON path is matched with the sensitive JSON path.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
in a first aspect, an embodiment of the present application provides a data desensitization system based on JSON analysis, including: JSON path scanning module: JSON paths used for respectively analyzing a plurality of documents; a column-wise conversion module: the document data is traversed according to the JSON path, and the same values of the JSON path are combined into a list to obtain column type storage intermediate data; by the sensitive scanning module: the JSON path processing unit is used for respectively carrying out sensitive scanning on the JSON path and values corresponding to the JSON path to obtain a sensitive JSON path list; a data desensitization module: and the method is used for performing traversal desensitization on all the document data according to the sensitive JSON path.
With respect to the first aspect: the embodiment of the application provides a data desensitization system based on JSON analysis, which analyzes JSON paths of a plurality of documents through a JSON path scanning module, so that JSON data of the plurality of documents are uniformly managed; traversing document data according to a JSON path through a column type conversion module, merging the same values of the JSON path into a list to obtain column type storage intermediate data, and realizing classified storage of the document data through the column type data; respectively carrying out sensitive scanning on the JSON path and the value corresponding to the JSON path through a sensitive scanning module, thereby traversing each path and the value data under the path to obtain the JSON path and the sensitive information in the JSON path value; and the data desensitization module performs traversal desensitization on all document data according to the sensitive JSON path to prevent sensitive information from being leaked. The method merges the same values of the JSON paths into a list through column-wise conversion, sensitively scans the JSON paths and the values of the JSON paths and then stores the JSON paths, can merge and protect the JSON data with arrays or objects, meets the JSON data use requirement of complex structures, and improves the safety of data information.
In a second aspect, an embodiment of the present application provides a JSON-analysis-based montgodb desensitization method, including the following steps: JSON path scanning: extracting a plurality of documents in a set, analyzing JSON paths in each document, and combining results; and (3) column conversion: traversing the document data again according to the JSON path, and combining the same values of the JSON path into a list to obtain column type storage intermediate data; sensitive scanning: respectively carrying out sensitive scanning on the JSON path and the value corresponding to the JSON path to obtain a sensitive JSON path list; data desensitization: and traversing desensitization is carried out on all the document data according to the sensitive JSON path.
With respect to the second aspect: the same principle and advantageous effects as the first aspect need not be repeated here.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic flow diagram of a data desensitization method based on JSON analysis according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. 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 application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
It is to be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
In the description of the present application, it should be noted that the terms "upper", "lower", "inner", "outer", and the like indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings or orientations or positional relationships conventionally found in use of products of the application, and are used only for convenience in describing the present application and for simplification of description, but do not indicate or imply that the referred devices or elements must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present application.
In the description of the present application, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "disposed" and "connected" are to be interpreted broadly, e.g., as being either fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the individual features of the embodiments can be combined with one another without conflict.
Example 1
The basic flow of the data desensitization system based on JSON analysis provided by the embodiment of the application is shown in fig. 1, which is a schematic flow diagram of a data desensitization method based on JSON analysis.
An embodiment of the present application provides a data desensitization system based on JSON analysis, including: JSON path scanning module: JSON paths used for respectively analyzing a plurality of documents; a column-wise conversion module: the document data is traversed according to the JSON path, and the same values of the JSON path are combined into a list to obtain column type storage intermediate data; a sensitive scanning module: the JSON path processing unit is used for respectively carrying out sensitive scanning on the JSON path and values corresponding to the JSON path to obtain a sensitive JSON path list; a data desensitization module: and the method is used for performing traversal desensitization on all the document data according to the sensitive JSON path.
In detail, the JSON path scanning module can merge results after acquiring JSON paths of a plurality of documents, which is convenient for searching and counting when the column conversion module traverses document data. The merging mode can be selected according to the membership of the path. In detail, the column-type storage intermediate data are classified by using the same value of the JSON path, so that the JSON data of multiple arrays or objects can be conveniently nested, the JSON data of different types of complex structures can be uniformly managed in any level, the similar JSON data of different paths can be conveniently sensitively scanned, the modification history can be reserved, and the effective source data can be conveniently traced. In detail, the sensitive scanning module respectively carries out sensitive scanning on the JSON path and the value corresponding to the JSON path through a list obtained by column type conversion to obtain a scanning result. And the sensitive scanning module simultaneously searches the path and the sensitive information in the value of the path and stores the sensitive information through the sensitive JSON path list, thereby marking the path position or the path value of the sensitive information. In detail, the data desensitization module desensitizes all document data according to the sensitive JSON path, so as to hide sensitive information.
In some embodiments of the present invention, the JSON path scan module extracts a plurality of documents in a collection.
In some embodiments of the present invention, the JSON path includes array nodes and child nodes.
In detail, take a JSON data as an example:
in detail, the following results are obtained by performing path scanning on the JSON data:
| date |
| books[*].book1.authors[*].name |
| books[*].book1.authors[*].phone |
| books[*].book2.category |
| books[*].book2.authors[*].name |
| books[*].book2.authors[*].phone |
wherein the path format is compatible with JSONPath. [] Representing the node as an array node. And [ ] represents all child nodes under the array node. The path format is convenient for the column type conversion module to combine the same values of the JSON paths to obtain column type storage intermediate data.
In some embodiments of the present invention, the values of the JSON path and the JSON path each comprise a null value.
In detail, the columnar transformation module traverses JSON data, merges path-identical values into a list, and stores intermediate data by a column, that is:
| route of travel | Value of |
| date | [“2020-01-01”] |
| books[*].book1.authors[*].name | 'Zhang three' and 'Li four'] |
| books[*].book1.authors[*].phone | [null,”18600001002”] |
| books[*].book2.category | [“fiction”] |
| books[*].book2.authors[*].name | [ "Wangwu"] |
| books[*].book2.authors[*].phone | [”18600001003”] |
The phone node corresponding to zhang san is null, and the path corresponding value may also be null. The advantage of setting the null value is that the positional correspondence between the columnar data can be retained. This functionality is needed when an associative scan needs to be made.
In some embodiments of the present invention, the sensitive scan module is configured to, after the sensitive scan, judge whether a last-stage name, a parent-stage structure, and a sensitive type of a value of the JSON path are the same, and merge values of a plurality of JSON paths having the same last-stage name, parent-stage structure, and sensitive type.
In detail, after the column data is obtained, the sensitive scanning module firstly traverses the value data under each path to perform sensitive scanning, so as to obtain a scanning result. And, since sensitive information appears in the path instead of the value in the individual scene, the path needs to be sensitively scanned. If the book1, book2 are sensitive data, then the path scan results in a book [ ] # key. Where # key represents the key value under this node, rather than the object itself, where the key value may be a key to a reference or a tag to add.
In some embodiments of the invention, the sensitive scan module is configured to merge values of a plurality of said JSON paths having the same last level name, parent structure and sensitive type into a last level name, parent structure and sensitive type.
If the final stage names of the path values in the scanning result are the same, the structures of the parent stages are the same, and the sensitive types of the scanning are also the same, the results can be merged. For example, the final stage of a book1. authors. phone and book2. authors. phone are both phones and the parent stage is the same, and the scan results are all phone types. The results can be merged into books.
In some embodiments of the present invention, the data desensitization module is configured to, after analyzing the values of the JSON path and the JSON path, perform desensitization processing on the values when the JSON path and the sensitive JSON path are matched.
And desensitizing all documents under the set according to the sensitive JSON path, wherein each JSON data is analyzed during desensitization. If the path and the sensitive path are matched, corresponding desensitization processing is carried out on the value, for example, shielding desensitization is carried out on the telephone, and the effects after desensitization are as follows:
example 2
Referring to fig. 1, an embodiment of the present application provides a montodb desensitization method based on JSON analysis, including the following steps: JSON path scanning: extracting a plurality of documents in a set, analyzing JSON paths in each document, and combining results; and (3) column conversion: traversing the document data again according to the JSON path, and combining the same values of the JSON path into a list to obtain column type storage intermediate data; sensitive scanning: respectively carrying out sensitive scanning on the JSON path and the value corresponding to the JSON path to obtain a sensitive JSON path list; data desensitization: and traversing desensitization is carried out on all the document data according to the sensitive JSON path.
In some embodiments of the invention, the sensitive scanning comprises: and after the sensitive scanning, judging whether the last-stage name, the parent-stage structure and the sensitive type of the JSON path value are the same, and merging the multiple JSON path values with the same last-stage name, parent-stage structure and sensitive type.
In some embodiments of the invention, the data desensitization comprises: and analyzing the JSON path and the value of the JSON path, and performing desensitization processing on the value when the JSON path is matched with the sensitive JSON path.
In detail, the above method is the same as the working principle and advantageous effects of embodiment 1, and a repeated description is not necessary here.
In the embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other ways. The system embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
To sum up, the data desensitization system and method based on JSON analysis provided in the embodiments of the present application:
the JSON path scanning module analyzes JSON paths of a plurality of documents, so that JSON data of the plurality of documents are uniformly managed; traversing document data according to a JSON path through a column type conversion module, merging the same values of the JSON path into a list to obtain column type storage intermediate data, and realizing classified storage of the document data through the column type data; respectively carrying out sensitive scanning on the JSON path and the value corresponding to the JSON path through a sensitive scanning module, thereby traversing each path and the value data under the path to obtain the JSON path and the sensitive information in the JSON path value; and the data desensitization module performs traversal desensitization on all document data according to the sensitive JSON path to prevent sensitive information from being leaked. The method merges the same values of the JSON paths into a list through column-wise conversion, sensitively scans the JSON paths and the values of the JSON paths and then stores the JSON paths, can merge and protect the JSON data with arrays or objects, meets the JSON data use requirement of complex structures, and improves the safety of data information.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1.A JSON analysis-based MongoDB desensitization system is characterized by comprising:
JSON path scanning module: JSON paths used for respectively analyzing a plurality of documents;
a column-wise conversion module: the document data is traversed according to the JSON path, and the same values of the JSON path are combined into a list to obtain column type storage intermediate data;
a sensitive scanning module: the JSON path processing unit is used for respectively carrying out sensitive scanning on the JSON path and values corresponding to the JSON path to obtain a sensitive JSON path list;
a data desensitization module: and the method is used for performing traversal desensitization on all the document data according to the sensitive JSON path.
2. The montgodb desensitization system based on JSON parsing of claim 1, wherein the JSON path scan module extracts documents in a collection.
3. The montgodb desensitization system based on JSON parsing of claim 1, wherein the JSON path includes array nodes and child nodes.
4. The montgodb desensitization system based on JSON parsing of claim 1, wherein values of the JSON path and the JSON path each comprise a null value.
5. The MongoDB desensitization system based on JSON resolution of claim 1, wherein the sensitive scan module is configured to determine whether the last level name, the parent level structure, and the sensitive type of the JSON path value are the same after the sensitive scan, and merge the JSON path values having the same last level name, parent level structure, and sensitive type.
6. The MongoDB desensitization system based on JSON parsing of claim 1, wherein the sensitive scan module is to merge values of a plurality of JSON paths with same last level name, parent level structure and sensitive type into last level name, parent level structure and sensitive type.
7. The MongoDB desensitization system based on JSON parsing of claim 1, wherein the data desensitization module is configured to desensitize values when the JSON path and a sensitive JSON path match after parsing the JSON path and the JSON path.
8. A JSON analysis-based MongoDB desensitization method is characterized by comprising the following steps:
JSON path scanning: extracting a plurality of documents in a set, analyzing JSON paths in each document, and combining results;
and (3) column conversion: and traversing the document data again according to the JSON path, and combining the same values of the JSON path into a list to obtain columnar storage intermediate data.
Sensitive scanning: and respectively carrying out sensitive scanning on the JSON path and the value corresponding to the JSON path to obtain a sensitive JSON path list.
Data desensitization: and traversing desensitization is carried out on all the document data according to the sensitive JSON path.
9. The montgodb desensitization method based on JSON parsing of claim 8, wherein the sensitive scan comprises: and after the sensitive scanning, judging whether the last-stage name, the parent-stage structure and the sensitive type of the JSON path value are the same, and merging the multiple JSON path values with the same last-stage name, parent-stage structure and sensitive type.
10. The MongoDB desensitization method based on JSON analysis according to claim 8, wherein the data desensitization comprises: and analyzing the JSON path and the value of the JSON path, and performing desensitization processing on the value when the JSON path is matched with the sensitive JSON path.
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