CN114611077A - Self-adaptive selection method, system and device for digital watermarks of database and storage medium - Google Patents
Self-adaptive selection method, system and device for digital watermarks of database and storage medium Download PDFInfo
- Publication number
- CN114611077A CN114611077A CN202210288467.5A CN202210288467A CN114611077A CN 114611077 A CN114611077 A CN 114611077A CN 202210288467 A CN202210288467 A CN 202210288467A CN 114611077 A CN114611077 A CN 114611077A
- Authority
- CN
- China
- Prior art keywords
- algorithm
- database
- watermark
- mapping relation
- database table
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000010187 selection method Methods 0.000 title claims abstract description 19
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 199
- 238000013507 mapping Methods 0.000 claims abstract description 121
- 238000003066 decision tree Methods 0.000 claims abstract description 29
- 238000012549 training Methods 0.000 claims abstract description 19
- 238000000605 extraction Methods 0.000 claims abstract description 14
- 238000001514 detection method Methods 0.000 claims abstract description 11
- 230000003044 adaptive effect Effects 0.000 claims description 26
- 238000004590 computer program Methods 0.000 claims description 13
- 238000013480 data collection Methods 0.000 claims description 4
- 238000000034 method Methods 0.000 abstract description 30
- 230000008569 process Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 6
- 230000006872 improvement Effects 0.000 description 3
- 238000005457 optimization Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/10—Protecting distributed programs or content, e.g. vending or licensing of copyrighted material ; Digital rights management [DRM]
- G06F21/16—Program or content traceability, e.g. by watermarking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Multimedia (AREA)
- Artificial Intelligence (AREA)
- Technology Law (AREA)
- Computer Hardware Design (AREA)
- Computer Security & Cryptography (AREA)
- Life Sciences & Earth Sciences (AREA)
- Editing Of Facsimile Originals (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a self-adaptive selection method, a system, a device and a storage medium of a database digital watermark, wherein the method comprises the following steps: s1, importing the watermark algorithm, detection and extraction algorithm supported by the database digital watermark system into an algorithm library; s2, reading the attributes of each tuple in the database table to be embedded with the watermark, and constructing the mapping relation of the attributes, the data application and the watermark algorithm; s3, reading the attribute characteristics of the database table, and according to the data usage, priority or usage proportion of different usage inputted by the user, after reading the watermark algorithm mapping relation in the mapping relation base, constructing a training set to form a decision tree, and using the decision tree to judge the type of the watermark embedding algorithm that the database table should select in the current service scene, and outputting the type as the algorithm to be embedded; and S4, according to the algorithm to be embedded, calling the corresponding watermark algorithm in the algorithm library to embed the watermark in the database table. The characteristics of the database table and the business requirements are automatically judged, and an embedding algorithm is selected, so that the usability and the configuration efficiency are improved.
Description
Technical Field
The invention relates to the field of data security, in particular to a method, a system, a device and a storage medium for adaptively selecting a digital watermark of a database.
Background
The database digital watermarking technology proves the ownership of the database by adding some secret information in the database, and does not affect the normal use of users. The technology can play a certain role in determining the ownership, data distribution, data leakage traceability and judging whether tampering exists in the circulation process of the database, and is an important technology in the aspects of determining the authority and tracking traceability of the database at present.
The database digital watermark technology comprises three processes of digital watermark embedding, detection and watermark extraction. There are many kinds of current database digital watermark embedding algorithms, such as pseudo-row algorithm, pseudo-column algorithm, some distortion algorithm for modifying data, etc.
Each algorithm has some impact on the application of the database tables. If the watermark of the pseudo line is not generally used as an object to be inquired, other lines of data are inquired normally, and the data statistics purpose is influenced; the pseudo column watermark has no influence on the data statistical purpose, but can influence the accurate query of the data; the distorted watermark has no influence on the table structure, and by inserting some special characters in a specific cell or modifying some data, the accurate query of the watermark column has influence, and the fuzzy query has no influence.
In practical application, a corresponding database digital watermarking algorithm needs to be selected according to the service scene or attribute of the database. At present, technicians manually configure a database table to select which database digital watermark embedding algorithm and extracting algorithm are used, which is troublesome in some comprehensive scenes, and operation and maintenance personnel or software installation personnel sometimes do not know which watermark embedding algorithm is more appropriate.
Disclosure of Invention
The invention aims to provide a self-adaptive selection method, a system, a device and a storage medium for a database digital watermark.
In order to solve the above technical problem, an embodiment of the present invention provides a database digital watermark adaptive selection method, including:
s1, importing the watermark algorithm, detection and extraction algorithm supported by the database digital watermark system into an algorithm library;
s2, reading the attributes of each tuple in the database table to be embedded with the watermark, and constructing the mapping relation of the attributes, the data application and the watermark algorithm;
s3, reading the attribute characteristics of the database table, and according to the data usage, the priority of usage or the usage proportion of different usage input by the user, after reading the watermark algorithm mapping relation in the mapping relation base, constructing a training set to form a decision tree, and using the decision tree to judge the watermark embedding algorithm type to be selected by the database table under the current service scene and outputting the watermark embedding algorithm type as the algorithm to be embedded;
and S4, calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table according to the algorithm to be embedded.
Wherein the S2 includes:
according to historical data, making relevant mapping relation correspondence on the attribute characteristics, the use scene and the applicable watermark algorithm of the database table to form an initial mapping relation database;
performing feature learning on the attribute features of the database table, and outputting the predetermined type features of the database table;
and after data collection is carried out on the purpose of the database table, a database digital watermarking algorithm which can be selected by the database is deduced by learning the initial mapping relation database according to the attribute characteristics and the purpose scene of the database table, and is used for perfecting the initial mapping relation database.
Wherein after the S2, the method further comprises:
after the database attributes of which the mapping relation is not established in the database table are obtained, the characteristics of database data and data purposes corresponding to the database attributes are learned, and a training set of the data attributes, the data purposes and the watermark algorithm is constructed by combining the historical preference of the watermark algorithm, so that the inferred mapping relation is formed.
Wherein, after the S2, the method further comprises:
and manually correcting the mapping relation.
The watermark algorithm comprises a pseudo-row algorithm, a pseudo-column algorithm, a distortion algorithm based on effective bits, a distortion algorithm based on invisible characters, a simulation watermark algorithm and a document database watermark algorithm.
In addition, an embodiment of the present application further provides a database digital watermark adaptive selection system, including:
the watermark algorithm library module is used for importing a watermark algorithm and a detection and extraction algorithm supported by a database digital watermark system into an algorithm library;
the mapping relation library module is used for reading the attributes of each tuple in the database table to be embedded with the watermark and constructing the mapping relation among the attributes, the data application and the watermark algorithm;
the decision judging module is used for reading the attribute characteristics of the database table, constructing a training set after reading the watermark algorithm mapping relation in the mapping relation base according to the data use, the priority of the use or the use proportion of different uses input by a user, forming a decision tree, judging the type of the watermark embedding algorithm which is to be selected by the database table in the current service scene by using the decision tree, and outputting the type as the algorithm to be embedded;
and the watermark embedding and extracting module is used for calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table according to the algorithm to be embedded.
The mapping relation library module comprises an initial mapping relation library unit, a feature learning unit and a mapping relation perfecting unit;
the initial mapping relation library unit is used for making relevant mapping relation correspondence to the attribute characteristics, the purpose scene and the applicable watermark algorithm of the database table according to historical data to form an initial mapping relation library;
the characteristic learning unit is used for performing characteristic learning on the attribute characteristics of the database table and outputting the characteristics of the preset type of the database table;
and the mapping relation perfecting unit is used for deducing a database digital watermarking algorithm which can be selected by the database according to the attribute characteristics and the use scene of the database table by learning the initial mapping relation database after collecting the data of the use of the database table, and is used for perfecting the initial mapping relation database.
The system also comprises a mapping relation deductibility module connected with the mapping relation library module and used for learning database data and data use characteristics corresponding to the database attributes after acquiring the database attributes of which the mapping relation is not established in the database table, and establishing a training set of the data attributes, the data use and the watermark algorithm by combining the historical preference of the watermark algorithm to form the deductibility mapping relation.
In addition, an embodiment of the present application further provides a device of a database digital watermark adaptive selection system, including:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of the database digital watermark adaptive selection method as described in any one of the above items.
Besides, the embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, where the computer program is executed by a processor to implement the steps of the database digital watermark adaptive extracting method as described in any one of the above.
Compared with the prior art, the self-adaptive selection method, the system, the device and the storage medium for the digital watermarks of the database provided by the embodiment of the invention have the following advantages:
the self-adaptive selection method, the system, the device and the storage medium of the database digital watermark are characterized in that a watermark algorithm and a detection and extraction algorithm supported by a database digital watermark system are firstly led into an algorithm library for subsequent calling, then the attributes of each tuple in a database table are read, and the mapping relation of the attributes, data purposes and the watermark algorithm is constructed. And then, reading the attribute characteristics of the database table, constructing a training set after reading the watermark algorithm mapping relation in the mapping relation base according to the data use, the priority of the use or the use proportion of different uses input by a user, forming a decision tree, judging the type of the watermark embedding algorithm which is to be selected by the database table under the current service scene by using the decision tree, and outputting the type of the watermark embedding algorithm as the algorithm to be embedded. And finally, according to the algorithm to be embedded, calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table, and automatically selecting the digital watermark embedding algorithm through automatic database table characteristic identification and service requirement judgment in the whole process, thereby greatly reducing the workload of manual configuration, improving the usability of a database digital watermark system and improving the use efficiency and accuracy of the database digital watermark.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flowchart illustrating steps of an embodiment of a method for adaptively selecting a database digital watermark according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an overall component in an embodiment of an adaptive selection method for a database digital watermark provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of an embodiment of a system of a database digital watermark adaptive selection method according to an embodiment of the present application,
fig. 4 is a schematic decision tree judgment diagram in an embodiment of a system of a database digital watermark adaptive selection method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Referring to fig. 1 to 4, fig. 1 is a schematic flowchart illustrating a procedure of an embodiment of a method for adaptively selecting a digital watermark in a database according to an embodiment of the present disclosure; fig. 2 is a schematic structural diagram of an overall component in an embodiment of an adaptive selection method for a database digital watermark according to an embodiment of the present invention; fig. 3 is a schematic structural diagram of a specific implementation of a system of a method for adaptively selecting a digital watermark in a database according to an embodiment of the present application, and fig. 4 is a schematic decision tree determination diagram in an embodiment of a system of a method for adaptively selecting a digital watermark in a database according to an embodiment of the present application.
In a specific embodiment, the method for adaptively selecting the database digital watermark includes:
s1, importing the watermark algorithm, detection and extraction algorithm supported by the database digital watermark system into an algorithm library; after all the watermarking algorithms supported by the database digital watermarking system and the like are added into the algorithm library, convenience is provided for subsequent calling and a selection range is provided.
S2, reading the attributes of each tuple in the database table to be embedded with the watermark, and constructing a mapping relation database of the attributes, the data use and the watermark algorithm; and reading and constructing a mapping relation according to the attributes to form a mapping relation library, so that the decision-making efficiency and accuracy can be improved when the decision-making is performed according to the needs of the user in the follow-up process.
The mapping relationship is not particularly limited in the present application. In one embodiment, the user name, identification number, mobile phone number, and the like are generally used for query service, and the pseudo-line algorithm is generally adopted for query, so that the mapping relationship between the user name, the query and the pseudo-line algorithm is established; data attributes such as money amount and achievement are often used for statistics or inquiry, and the pseudo-column algorithm is generally adopted for statistics, so that the mapping relation between money amount, statistics and the pseudo-column algorithm is constructed.
It should be noted that, in the present application, attribute features of statistics and query may also be simultaneously provided, and statistics and query services are simultaneously required, so that a watermarking algorithm having such a function is either adopted, or a user is requested to provide more scenes to be queried or more scenes to be counted, and a priority is listed to solve a selection problem of the watermarking algorithm, for example, accurate statistics is suitable for using a pseudo-column algorithm, while rough statistics and pseudo-columns in pseudo rows can be listed as such a priority.
S3, reading the attribute characteristics of the database table, and according to the data usage, the priority of usage or the usage proportion of different usage input by the user, after reading the watermark algorithm mapping relation in the mapping relation library, constructing a training set to form a decision tree, and judging the type of the watermark embedding algorithm to be selected by the database table in the current service scene by using the decision tree and outputting the type as the algorithm to be embedded; after the attribute characteristics of the database table are read, a training set is constructed according to the acquired user requirements to form a decision tree, and then the finally required algorithm type is determined and output for the final embedding requirement.
And S4, calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table according to the algorithm to be embedded. In the process, a matching mode can be adopted, namely the algorithm obtained in the previous step is matched with the possible algorithm in the current step, and then the watermark is embedded according to the matching result. The method may further include, after obtaining an algorithm to be embedded, calling from an algorithm library and then embedding a watermark in the database table, or embedding a watermark in other manners, which is not limited in this application.
The method comprises the steps of firstly importing a watermarking algorithm and a detection and extraction algorithm supported by a database digital watermarking system into an algorithm library for subsequent calling, then reading the attribute of each tuple in a database table, and constructing the mapping relation of the attribute, the data application and the watermarking algorithm. And then, reading the attribute characteristics of the database table, acquiring the requirements of the user according to the data application, application priority or use proportion of different applications input by the user, constructing a training set after reading the watermark algorithm mapping relation in the mapping relation base, forming a decision tree, judging the type of the watermark embedding algorithm to be selected by the database table in the current service scene by using the decision tree, and outputting the type of the watermark embedding algorithm to be used as the algorithm to be embedded. And finally, according to the algorithm to be embedded, calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table, and automatically selecting the digital watermark embedding algorithm through automatic database table characteristic identification and service requirement judgment in the whole process, thereby greatly reducing the workload of manual configuration, improving the usability of a database digital watermark system and improving the use efficiency and accuracy of the database digital watermark.
The application is not limited to the formation of the specific mapping relation library, and in an embodiment, the S2 includes:
according to historical data, making relevant mapping relation correspondence on the attribute characteristics, the use scene and the applicable watermark algorithm of the database table to form an initial mapping relation database;
performing feature learning on the attribute features of the database table, and outputting the predetermined type features of the database table;
and after data collection is carried out on the purpose of the database table, a database digital watermarking algorithm which can be selected by the database is deduced by learning the initial mapping relation database according to the attribute characteristics and the purpose scene of the database table, and is used for perfecting the initial mapping relation database.
The method comprises the steps of firstly forming an initial mapping relation library, then carrying out feature learning to obtain the feature type of a database table, finally carrying out learning inference on the initial mapping relation library after data collection on the purpose of the database, and selecting an algorithm, so that the improvement of the initial mapping relation library is realized, the relation library can be optimized after being improved for many times, the optimization can be carried out periodically, or the optimization can be carried out before watermark embedding every time, or other optimization modes and the like.
In an actual application, a mapping relationship may not be established, and in order to facilitate the subsequent formation and decision of the decision tree, in an embodiment, after the step S2, the method further includes:
after the database attributes of which the mapping relation is not established in the database table are obtained, the characteristics of database data and data purposes corresponding to the database attributes are learned, and a training set of the data attributes, the data purposes and the watermark algorithm is constructed by combining the historical preference of the watermark algorithm, so that the inferred mapping relation is formed.
After the mapping relation cannot be directly obtained, the characteristics of database data and data purposes corresponding to the database attributes are adopted for learning, a training set of the data attributes, the data purposes and the watermark algorithm is constructed, the inferred mapping relation is realized, and the mapping relation is obtained for all database tables.
Due to the mapping relationship, errors may occur, and in order to improve the accuracy, in an embodiment, after the step S2, the method further includes:
and manually correcting the mapping relation.
The inferred mapping relation is corrected and modified regularly and manually, so that a mapping relation library is continuously perfected, and the accuracy of subsequent decisions is improved.
The type of the watermarking algorithm is not specifically limited in the present application, and the watermarking algorithm includes a pseudo-row algorithm, a pseudo-column algorithm, a distortion algorithm based on an effective bit, a distortion algorithm based on an invisible character, a simulation watermarking algorithm, a document database watermarking algorithm, and may also include other algorithms, which are not limited in the present application.
The general implementation of the invention comprises a database digital watermarking system server, a user terminal and an original database server, and the specific architecture is as shown in figure 2 and the business process is as follows.
In the device structure and the service flow in an embodiment of the application, a specific service flow of a user requesting to embed a database digital watermark is as follows:
firstly, a user sends a request to a database digital watermark server through terminal equipment, and requires to embed a watermark into a certain table of an original database, and explains the usage scene of the database table, and if a plurality of usage scenes exist, explains the priority of usage.
Secondly, after receiving the request, the database digital watermark server sends a request for reading the database table to the source database;
thirdly, the source database feeds back the requested database table;
and fourthly, the database digital watermarking server performs characteristic learning on the database table fed back, acquires attribute information and scene use information of the user, performs decision judgment by adopting a decision tree algorithm according to the mapping relation between the attribute and the use in the relational mapping library and the watermarking algorithm, calls a corresponding algorithm in the watermarking algorithm library to perform watermarking embedding operation on the database table after outputting the watermarking algorithm to be adopted, and performs embedding algorithm identification on the database table.
And fifthly, the database digital watermark server feeds back the database table which finishes executing the watermark embedding to the user terminal equipment.
In addition, an embodiment of the present application further provides a database digital watermark adaptive selection system, including:
the watermark algorithm library module 10 is used for importing the watermark algorithm and the detection and extraction algorithm supported by the database digital watermark system into an algorithm library;
the mapping relation library module 20 is used for reading the attributes of each tuple in the database table to be embedded with the watermark and constructing the mapping relation among the attributes, the data application and the watermark algorithm;
a decision judging module 30, configured to read attribute features of a database table, and according to data usage input by a user, priority of usage, or usage proportion of different usage, construct a training set after reading a watermark algorithm mapping relationship in the mapping relationship library, form a decision tree, judge a watermark embedding algorithm type that the database table should select in a current service scene by using the decision tree, and output the watermark embedding algorithm type as a to-be-embedded algorithm;
and the watermark embedding and extracting module 40 is used for calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table according to the algorithm to be embedded. The watermark embedding and extracting module is an auxiliary module of the application, judges the selected watermark algorithm according to the decision tree, calls a related algorithm in an algorithm library, executes the embedding or extracting operation of the watermark, and completes the task of loading the watermark or extracting the watermark for the database table.
The database digital watermark self-adaptive selection system is a system corresponding to the database digital watermark self-adaptive selection method, and has the same beneficial effects, and the details are not repeated in the application.
The method is mainly used for forming a subsequent decision tree and realizing efficient automatic decision, and in one embodiment, the mapping relation library module comprises an initial mapping relation library unit, a feature learning unit and a mapping relation perfecting unit;
the initial mapping relation library unit is used for making relevant mapping relation correspondence to the attribute characteristics, the purpose scene and the applicable watermark algorithm of the database table according to historical data to form an initial mapping relation library;
the characteristic learning unit is used for performing characteristic learning on the attribute characteristics of the database table and outputting the characteristics of the preset type of the database table;
and the mapping relation perfecting unit is used for deducing a database digital watermarking algorithm which can be selected by the database according to the attribute characteristics and the use scene of the database table by learning the initial mapping relation database after collecting the data of the use of the database table, and is used for perfecting the initial mapping relation database.
The mapping relation library module is one of core modules of the application, and a mapping relation among the three is formed mainly by a module developer according to the existing database development experience, common use scenes of different databases and a corresponding proper watermarking algorithm.
However, in some cases, a mapping relationship may not be directly formed, and in an embodiment, the database digital watermark adaptive selection system further includes a mapping relationship inference module connected to the mapping relationship library module, and configured to, after obtaining a database attribute of a mapping relationship that is not established in the database table, learn features of database data and data usage corresponding to the database attribute, and construct a training set of the data attribute, the data usage, and the watermark algorithm in combination with a history preference of using the watermark algorithm to form an inference mapping relationship.
The mapping relations of some attributes, purposes and the watermark algorithm are automatically formed by learning and deducing the attribute characteristics of database data and the characteristics of data purposes and the prior watermark algorithm preference, and can be corrected manually when necessary.
And then, deducing a database digital watermarking algorithm which can be selected by the database through learning the configured mapping relation according to the table attribute characteristics and the table use scene so as to continuously perfect the mapping relation database. The module can be automatically generated when the database digital watermarking system is deployed in an actual environment.
Table 1 below is an example of a mapping table.
TABLE 1
The decision-making judgment module in the application is a core module of the module and is a key step selected by a self-adaptive watermarking algorithm. After a user sends a watermark embedding instruction (including database table information, database table usage scene information, priority information of usage scenes, special requirements and the like) to a database digital watermark system, the system makes a decision of selecting a watermark algorithm through the module, and the specific implementation method of the module is as follows:
the module reads and intelligently learns the database table characteristic information fed back, collects information such as table use scenes, priorities, special requirements and the like in the user instruction information, reads related mapping relations in the mapping relation library according to the information, and constructs a training set based on the table characteristic information, the table use scene information, the use priority information, the special requirements and the mapping relations to form a decision tree. The decision of the watermark algorithm selection is made according to a decision tree, and a specific example is shown in fig. 3.
In addition, an embodiment of the present application further provides a device of a database digital watermark adaptive selection system, including:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of the database digital watermark adaptive selection method as described in any one of the above items.
The type of the device of the database digital watermark self-adaptive selection system is not limited in the application,
Besides, the embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, where the computer program is executed by a processor to implement the steps of the database digital watermark adaptive extracting method as described in any one of the above.
Similarly, the computer program in the computer-readable storage medium is executed by a processor to implement the steps of the database digital watermark adaptive selection method as described in any one of the above items, which has the same beneficial effects, and the present application does not limit this.
In summary, the method, system, device and storage medium for adaptively selecting a database digital watermark provided in the embodiments of the present invention introduce a watermark algorithm, a detection and extraction algorithm supported by a database digital watermark system into an algorithm library for subsequent retrieval, then read attributes of each tuple in a database table, and construct a mapping relationship between the attributes, data usage and the watermark algorithm. And then reading the attribute characteristics of the database table, acquiring the requirements of the user according to the data use, the priority of the use or the use proportion of different uses input by the user, constructing a training set after reading the watermark algorithm mapping relation in the mapping relation library, forming a decision tree, judging the type of the watermark embedding algorithm which is to be selected by the database table in the current service scene by using the decision tree, and outputting the type as the algorithm to be embedded. And finally, according to the algorithm to be embedded, calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table, and automatically selecting the digital watermark embedding algorithm through automatic database table characteristic identification and service requirement judgment in the whole process, thereby greatly reducing the workload of manual configuration, improving the usability of a database digital watermark system and improving the use efficiency and accuracy of the database digital watermark.
The foregoing describes a method, system, apparatus and storage medium for adaptive selection of digital watermarks in a database according to the present invention. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (10)
1. A self-adaptive selection method for digital watermarks of a database is characterized by comprising the following steps:
s1, importing the watermark algorithm, detection and extraction algorithm supported by the database digital watermark system into an algorithm library;
s2, reading the attributes of each tuple in the database table to be embedded with the watermark, and constructing the mapping relation of the attributes, the data application and the watermark algorithm;
s3, reading the attribute characteristics of the database table, and according to the data usage, the priority of usage or the usage proportion of different usage input by the user, after reading the watermark algorithm mapping relation in the mapping relation library, constructing a training set to form a decision tree, and judging the type of the watermark embedding algorithm to be selected by the database table in the current service scene by using the decision tree and outputting the type as the algorithm to be embedded;
and S4, calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table according to the algorithm to be embedded.
2. The adaptive database digital watermark extraction method of claim 1, wherein the S2 includes:
according to historical data, making relevant mapping relation correspondence on the attribute characteristics, the use scene and the applicable watermark algorithm of the database table to form an initial mapping relation database;
performing feature learning on the attribute features of the database table, and outputting the predetermined type features of the database table;
and after data collection is carried out on the purpose of the database table, a database digital watermarking algorithm which can be selected by the database is deduced by learning the initial mapping relation database according to the attribute characteristics and the purpose scene of the database table, and is used for perfecting the initial mapping relation database.
3. The adaptive database digital watermark extraction method of claim 2, further comprising, after the step S2:
after the database attributes of which the mapping relation is not established in the database table are obtained, the characteristics of database data and data purposes corresponding to the database attributes are learned, and a training set of the data attributes, the data purposes and the watermark algorithm is constructed by combining the historical preference of the watermark algorithm, so that the inferred mapping relation is formed.
4. The adaptive database digital watermark extraction method of claim 3, further comprising, after the step of S2:
and manually correcting the mapping relation.
5. The adaptive database digital watermark selection method according to claim 4, wherein the watermark algorithm comprises a pseudo-row algorithm, a pseudo-column algorithm, a distortion algorithm based on significant bits, a distortion algorithm based on invisible characters, an artificial watermark algorithm, and a document database watermark algorithm.
6. A database digital watermark adaptive selection system, comprising:
the watermark algorithm library module is used for importing a watermark algorithm and a detection and extraction algorithm supported by a database digital watermark system into an algorithm library;
the mapping relation library module is used for reading the attributes of each tuple in the database table to be embedded with the watermark and constructing the mapping relation among the attributes, the data application and the watermark algorithm;
the decision judging module is used for reading the attribute characteristics of the database table, constructing a training set after reading the watermark algorithm mapping relation in the mapping relation base according to the data use, the priority of the use or the use proportion of different uses input by a user, forming a decision tree, judging the type of the watermark embedding algorithm which is to be selected by the database table in the current service scene by using the decision tree, and outputting the type as the algorithm to be embedded;
and the watermark embedding and extracting module is used for calling a corresponding watermark algorithm in the algorithm library to embed the watermark in the database table according to the algorithm to be embedded.
7. The database digital watermark adaptive selection system of claim 6, wherein the mapping relation library module comprises an initial mapping relation library unit, a feature learning unit and a mapping relation perfecting unit;
the initial mapping relation library unit is used for making relevant mapping relation correspondence to the attribute characteristics, the purpose scene and the applicable watermark algorithm of the database table according to historical data to form an initial mapping relation library;
the characteristic learning unit is used for performing characteristic learning on the attribute characteristics of the database table and outputting the characteristics of the preset type of the database table;
and the mapping relation perfecting unit is used for deducing a database digital watermarking algorithm which can be selected by the database according to the attribute characteristics and the use scene of the database table by learning the initial mapping relation database after collecting the data of the use of the database table, and is used for perfecting the initial mapping relation database.
8. The database digital watermark adaptive selection system according to claim 7, further comprising a mapping relationship deductibility module connected to the mapping relationship database module, and configured to learn database data and data usage characteristics corresponding to the database attributes after acquiring database attributes for which mapping relationships are not established in the database table, and construct a training set of data attributes, usage and watermark algorithm in combination with historical preferences of the watermark algorithm to form deductive mapping relationships.
9. An apparatus for a database digital watermark adaptive selection system, comprising:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of the database digital watermark adaptive selection method according to any one of claims 1 to 5.
10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and the computer program is executed by a processor to implement the steps of the database digital watermark adaptive selection method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210288467.5A CN114611077A (en) | 2022-03-23 | 2022-03-23 | Self-adaptive selection method, system and device for digital watermarks of database and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210288467.5A CN114611077A (en) | 2022-03-23 | 2022-03-23 | Self-adaptive selection method, system and device for digital watermarks of database and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114611077A true CN114611077A (en) | 2022-06-10 |
Family
ID=81864729
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210288467.5A Pending CN114611077A (en) | 2022-03-23 | 2022-03-23 | Self-adaptive selection method, system and device for digital watermarks of database and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114611077A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115455383A (en) * | 2022-11-14 | 2022-12-09 | 北京奕之宣科技有限公司 | Method, device and equipment for processing watermark information of database |
| CN116975246A (en) * | 2023-08-03 | 2023-10-31 | 深圳市博锐高科科技有限公司 | Data acquisition method, device, chip and terminal |
-
2022
- 2022-03-23 CN CN202210288467.5A patent/CN114611077A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115455383A (en) * | 2022-11-14 | 2022-12-09 | 北京奕之宣科技有限公司 | Method, device and equipment for processing watermark information of database |
| CN116975246A (en) * | 2023-08-03 | 2023-10-31 | 深圳市博锐高科科技有限公司 | Data acquisition method, device, chip and terminal |
| CN116975246B (en) * | 2023-08-03 | 2024-04-26 | 深圳市博锐高科科技有限公司 | Data acquisition method, device, chip and terminal |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114611077A (en) | Self-adaptive selection method, system and device for digital watermarks of database and storage medium | |
| CN112527972A (en) | Intelligent customer service chat robot implementation method and system based on deep learning | |
| CN108366052A (en) | Verify the processing method and system of short message | |
| CN112765473B (en) | Data processing system for acquiring target associated equipment | |
| US20060224777A1 (en) | System and method for creating test data for data driven software systems | |
| CN112182021B (en) | User data query method, device and system | |
| CN106202456A (en) | Send the method and device of picture | |
| CN116132589A (en) | Optimization method and system for voice feedback menu of electric power customer service system | |
| CN114757805A (en) | Block chain-based convenient government affair service system | |
| CN115438054A (en) | Incremental calculation updating method based on expert statistical characteristics, electronic equipment and medium | |
| CN111639478B (en) | Automatic data auditing method and system based on EXCEL document | |
| CN114387429A (en) | Vehicle property right processing method, device, equipment and medium based on RPA and AI | |
| US8380690B2 (en) | Automating form transcription | |
| CN109977992B (en) | Electronic device, method for identifying batch registration behaviors and storage medium | |
| CN113282384A (en) | Cooperative office management method and device based on Internet and cooperative management platform | |
| CN109753599A (en) | The method and apparatus of recommendation business | |
| CN110517010A (en) | A kind of data processing method, system and storage medium | |
| CN115883260B (en) | Digital collection traceability system based on steganography technology | |
| CN112597157B (en) | Method and system for storing and managing submission information | |
| CN112347522A (en) | UTXO architecture-based third-party data uplink realization method | |
| CN112766312B (en) | User information acquisition method, electronic equipment and medium | |
| CN114327294B (en) | Data reading system for multilevel storage | |
| CN111581514B (en) | Information distribution method and device | |
| CN111414467A (en) | Question-answer dialogue method and device, electronic equipment and computer readable storage medium | |
| CN115983910A (en) | Method, system, device and medium for realizing comparison of elevator advertisement putting schemes |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |