CN116069952B

CN116069952B - Data processing method, device, computer equipment and storage medium

Info

Publication number: CN116069952B
Application number: CN202310184306.6A
Authority: CN
Inventors: 贾晓元; 方有轩; 郑旭晓; 赖思为; 辛艳双; 龙春华
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Information Technology Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Information Technology Co Ltd
Priority date: 2023-02-20
Filing date: 2023-02-20
Publication date: 2025-09-05
Anticipated expiration: 2043-02-20
Also published as: CN116069952A

Abstract

This application discloses a data processing method, apparatus, computer device, and storage medium. The method includes processing a data visualization request including a business scenario sent by a user; determining an encrypted data table and an encrypted dynamic table corresponding to the business problem based on the business scenario; constructing a dynamic view of encrypted data with N levels based on the encrypted data table and the encrypted dynamic table; drilling down through the N levels using an aggregation algorithm corresponding to the business problem to obtain drilldown results for each of the N levels; and displaying a blockchain data visualization interface based on the encrypted data corresponding to the drilldown results. In this way, when executing the data visualization request, encrypted data authorization is completed without user intervention, enabling the use of encrypted data on the blockchain, thereby ensuring the integrity of the content displayed in the visualization interface.

Description

Data processing method, device, computer equipment and storage medium

Technical Field

The application belongs to the technical field of computers, and particularly relates to a data processing method, a data processing device, computer equipment and a storage medium.

Background

The knowledge graph can conduct data mining, information processing, knowledge metering and graph drawing on the complex knowledge field through data on the blockchain, and reveal the dynamic development rule of the knowledge field. In a blockchain visualization application, a knowledge graph is usually represented as a Multi-relationship graph (Multi-relational Graph) formed by nodes and edges, which is convenient for a user to view and interact in a graphical visualization interface.

In the related technology, because the blockchain visualization system of the knowledge graph is a knowledge graph triplet constructed based on data on the blockchain to show the relationship among the address, the transaction and the node, if the data authorization is not realized, the search of the encrypted data on the blockchain is not supported, so that the content of the multi-relationship graph in the visualization interface is lost, and the integrity of the multi-relationship graph is affected.

Disclosure of Invention

The embodiment of the application provides a data processing method, a data processing device, computer equipment and a storage medium, which can solve the problem that the integrity of a multi-relation diagram is affected due to the fact that the content of the multi-relation diagram in a visual interface is lost because the search of encrypted data on a blockchain is not supported in the prior art.

In a first aspect, an embodiment of the present application provides a data processing method, which may include:

Receiving a data visualization request sent by a user terminal, wherein the data visualization request comprises a service scene corresponding to the user terminal;

According to the service scene, acquiring a service problem of the service scene, an encryption data table and an encryption dynamic table corresponding to the service problem, wherein the encryption data table comprises encryption index keywords and data ownership;

Constructing an encrypted data dynamic view with N layers based on the encrypted data table and the encrypted dynamic table, wherein N is an integer greater than 1;

Drilling N layers in the encrypted data dynamic view through an aggregation algorithm of the service problems to obtain a drilling result of each layer in the N layers;

And displaying the block chain data visualization interface according to the encrypted data corresponding to the drilling result under the condition that the drilling result characterizes the encrypted data owner to allow the user side to use the encrypted data corresponding to the service problem.

In a second aspect, an embodiment of the present application provides a data processing apparatus, which may include:

The receiving module is used for receiving a data visualization request sent by the user terminal, wherein the data visualization request comprises a service scene corresponding to the user terminal;

The system comprises an acquisition module, an encryption dynamic table, a storage node, an encryption data owner and a traceable block of encryption data, wherein the acquisition module is used for acquiring service problems of a service scene, an encryption data table and an encryption dynamic table corresponding to the service problems according to the service scene, and the encryption data table comprises an encryption index keyword and data ownership;

the construction module is used for constructing an encrypted data dynamic view with N layers based on the encrypted data table and the encrypted dynamic table, wherein N is an integer greater than 1;

The processing module is used for carrying out drilling processing on N layers in the encrypted data dynamic view through an aggregation algorithm of the service problems to obtain a drilling result of each layer in the N layers;

And the display module is used for displaying the block chain data visualization interface according to the encrypted data corresponding to the drilling result under the condition that the drilling result characterizes the encrypted data owner to allow the user side to use the encrypted data corresponding to the service problem. In a third aspect, embodiments of the present application provide a computing device comprising a processor and a memory storing computer program instructions;

the processor when executing the computer program instructions implements the data processing method as shown in the first aspect.

In a fourth aspect, embodiments of the present application provide a computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement a data processing method as described in the first aspect.

In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and the processor is configured to execute a program or instructions to implement a data processing method as shown in the first aspect.

In a sixth aspect, embodiments of the present application provide a computer program product stored in a storage medium, the program product being executable by at least one processor to implement a data processing method as shown in the first aspect.

The data processing method, the device, the computer equipment and the storage medium of the embodiment of the application are used for receiving a data visualization request sent by a user side, wherein the data visualization request comprises a service scene corresponding to the user side, acquiring a service problem of the service scene and an encrypted data table and an encrypted dynamic table corresponding to the service problem according to the service scene, wherein the encrypted data table comprises encrypted index keywords and data ownership, the encrypted dynamic table is used for describing a storage node, an encrypted data owner and a traceable block of encrypted data, the encrypted node is provided with the encrypted sealing sector with the encrypted index keywords, an encrypted data dynamic view with N layers is constructed based on the encrypted data table and the encrypted dynamic table, drilling processing is carried out on the N layers in the encrypted data dynamic view through an aggregation algorithm of the service problem to obtain drilling results of each of the N layers, and a block chain data visualization interface is displayed according to the encrypted data corresponding to the drilling results when the drilling results represent the encrypted data owner allows the user side to use the encrypted data corresponding to the service problem. In this way, the service problems corresponding to the service scene are determined according to the data visualization request sent by the user terminal, an encryption data table and an encryption dynamic table are constructed according to the service operator problems, then an encryption data dynamic view with N layers is constructed based on the encryption data table and the encryption dynamic table, in this way, according to the aggregation algorithm of the service problems, multi-layer drilling is carried out on the constructed encryption data dynamic view, namely whether the encryption data owners of the encryption data corresponding to the service problems in each layer allow the user terminal to use the encryption data in the layer, if the encryption data owners allow the user terminal to use the encryption data corresponding to the service problems, the block chain data visualization interface is displayed according to the encryption data corresponding to the drilling result, thereby completing the visual analysis of the block chain data, in the process of executing the data visualization request sent by the user terminal, the user is not required to participate in, the authorization of the encryption data on the block chain is completed, the application of the encryption data on the block chain is realized, the complete data can be obtained for each service problem, and the integrity of the content displayed in the block chain data visualization interface is ensured.

Drawings

In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings that are needed to be used in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.

FIG. 1 is a schematic diagram of a data processing system according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a data analysis process in a data processing method according to an embodiment of the present application;

FIG. 3 is a flowchart of a data processing method according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a data processing apparatus according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present application.

Detailed Description

Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail below with reference to the accompanying drawings and the detailed embodiments. It should be understood that the particular embodiments described herein are meant to be illustrative of the application only and not limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the application by showing examples of the application.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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" does not exclude the presence of additional identical elements in a process, method, article, or apparatus that comprises an element.

In order to better understand the data processing method provided by the application, the technical background related to the application is explained and specifically shown as follows. The block chain address visualization means that by analyzing a shared account book of a block chain, the addresses are labeled, the addresses are analyzed in a traced mode and the monitored addresses are distinguished, and the labels are backed up to a rich label library, so that the readability of the address analysis is higher, for example, transaction exchange marks (logo), contract address icons, celebrity labels and the like are displayed in a visual mode and address details are synchronously displayed. Of course, the user may select different addresses on the display interface, and the address details may change according to the address change selected by the user. The method has the advantages that the address health degree is embedded when the visual analysis is carried out on the blockchain address, and a user can directly know the risk degree of the blockchain address while inquiring the blockchain address. The on-chain data monitoring and transaction behavior analysis model is used for carrying out transaction tracing on the blockchain address, constructing a transaction map and preferentially displaying entity tags and large-amount transactions which are concerned by users. And analyzing the transaction line of the address, displaying details such as intelligent contract, transaction hash, address, token ID and the like, and displaying chart information of transaction data. And monitoring the data on the chain by analyzing the newly generated blocks in real time, and establishing an analysis model for the transaction behavior. And monitoring a block chain address time axis, and displaying a transaction map by adopting a link map mode. The data visualization analysis model is characterized in that a user processes basic data and builds the model, selects data according to requirements, processes the data, performs multidimensional analysis through drag operation based on a self-service data set, and displays the data on a data instrument panel. The user selects required data in the display interface through simple dragging operation, and supports a plurality of chart types and patterns through OLAP multidimensional analysis functions such as drill-down, scroll-up, rotation and linkage, so that the data of the user can be displayed in a more vivid mode, wherein the data is displayed through visual analysis and display, and the data comprises a cylindrical chart, a line graph, a scatter chart, a radar chart, a GIS map, a Gantt chart and the like. And the knowledge graph visualization of the blockchain can display the complex knowledge field through data mining, information processing, knowledge metering and graph drawing on the blockchain, reveal the dynamic development rule of the knowledge field, provide practical and valuable references for discipline research, and is a knowledge base with a directed graph structure. The knowledge graph is expressed as a Multi-relation graph (Multi-relational Graph) in the visual application of the block chain aspect, and can be checked and interacted by a user in a graphical interface.

In the related technology, a knowledge-graph-based blockchain visualization system can construct a knowledge-graph triplet aiming at data on a blockchain to realize the blockchain visualization and display the relationship among addresses, transactions and nodes. However, when the data validation or authorization is not realized, the search of the encrypted data is not supported, so that the visualized content lacks content, and the integrity of the multi-relation graph is affected. And secondly, the graphic expression modes of the 'node' and 'edge' triples of the knowledge graph are not suitable for expressing multi-level data association relations and are not suitable for data mining, so that the visualization processing applicability is low.

Based on this, in order to solve the above-mentioned problems, the data processing method provided in the embodiment of the present application may include three phases, namely, a data authorization phase, a data mining phase, and a display data corresponding interface phase. Specifically, the data processing system may automatically capture user data based on different user scenarios of at least one terminal (a user terminal and a user terminal corresponding to an encrypted data owner), generate an index keyword (or receive an encrypted index keyword set by a user on the data) according to the frequency and weight of occurrence of a word, and sign and encrypt the data thereof by using a user private key of the user terminal, and submit the signed and encrypted data to the distributed encrypted storage system. The distributed encryption storage system mixes, slices, encryption proof computation of data and encryption index keys, generates an encryption sealed sector (256M), and uploads the merck root (256 bytes) of the encryption sealed sector onto the blockchain. The distributed encryption storage system randomly extracts the merck root (256 bytes) on the blockchain at intervals and verifies whether the encrypted sectors of this merck root are stored effectively. Based on this, an encryption data table can be constructed based on the encryption index key and the data ownership to prepare for constructing a multi-layered encryption view.

In this way, when receiving a data visualization request sent by any user side, a service question is acquired for a service person scene in the data visualization request, and the service question is analyzed based on the service scene, so as to obtain service logic corresponding to the service question (for example, front and back calculation logic for answering the service question and data required for calculating the service question each time). An encryption dynamic table is constructed through CryptoSQL statement sets converted by service logic, an encryption data range, a data hierarchy and an aggregation algorithm of data related to service problems of the user side are induced based on the encryption dynamic table and the encryption data table, an encryption data dynamic view is constructed based on the encryption data range, the data hierarchy and the aggregation algorithm of the data related to the service problems of the user side, then the aggregation algorithm such as calculation modes of level calculation, measurement aggregation calculation, dimension aggregation calculation, encryption dynamic table calculation and the like are used for carrying out hierarchical drilling on the encryption data dynamic view, service encryption data corresponding to encryption index keywords are obtained from the encryption sealing sector, the storage node to which the encryption data belong and a traceable block of the encryption data, after the data are decrypted, a data calculation result of the service problems is obtained, the calculation result is summarized to a service data dashboard of a block chain data visual interface, and visual analysis of the block chain data is completed and presented to a user.

An embodiment of the present application provides a data processing system, and in the following, with reference to fig. 1 and fig. 2, the data processing system provided by the embodiment of the present application is described in detail.

As shown in FIG. 1, data processing system 10 may include a traffic side and a storage side, wherein the storage side may include a distributed storage area block chain system module, an encryption seal sector module, and an encryption index and data ownership mapping module. The service side may include an encryption dynamic table module, a service problem decomposition algorithm module, a multi-layer view construction module, and a data dashboard module.

Based on this, the storage side may be configured to receive the encryption index key set by the user on the data, encrypt the data by using the user private key, encapsulate the encrypted data into each encryption seal sector with 256M size, record the calculation process and the storage information of the encryption seal in the blockchain in the form of "proof" character string (proof), and at intervals, the distributed encryption storage network system will randomly check the "proof" character string (proof) on the blockchain, and verify whether the seal sector storing the encrypted data is still effectively stored. On a service side, service problems of a user are converted into service logic through service scene analysis, analysis strategies such as analysis range, hierarchy LOD and field aggregation are generated, an encryption data dynamic view with N layers is constructed according to an encryption data table and an encryption dynamic table through CryptoSQL statement sets, meanwhile, calculation modes such as analysis strategy analysis level calculation, measurement aggregation calculation, dimension aggregation calculation and encryption dynamic table calculation are carried out on the generated encryption data dynamic view, multi-layer drilling is carried out to obtain drilling results of each of the N layers, then a data instrument board is generated according to the drilling results of each of the N layers, and visual analysis on block chain data is completed.

The above modules are respectively described below.

The distributed storage block chain system module is used for receiving data of a user side and carrying out encryption storage based on a block chain, is responsible for encryption sealing calculation on the data, is a distributed encryption storage network, a plurality of peer encryption storage nodes form a network, receives data encryption storage requests from the user side, carries out association mapping on encryption index keywords and the data of the user side, encrypts the data of the user side by adopting a private key of the user side, seals the data of the user side in sealing sectors of certain encryption storage nodes, records the calculation process and storage information of encryption sealing in the block chain in a form of a proof character string (proof), and at intervals, the distributed encryption storage network system randomly checks the proof character string (proof) on the block chain to verify whether the sealing sectors storing the encrypted data are still effectively stored.

The business problem decomposition algorithm module is used for inducing a business scene into a plurality of business problems to form business logic, and is responsible for generating CryptoSQL statement sets for describing the data range, the hierarchy, the aggregation mode and the business problems of the business problems, and is a module for analyzing user data of a business side. The business problem decomposition algorithm module generalizes a business scenario into a plurality of business problems, wherein each business problem comprises two types of fields, one is a description field (classification field) and the other is an aggregation field (quantization field). The classification field describes data differently from each other, describes the kind of data, and is the dimension of the data. The number of the quantized field descriptions is the accurate answer to the question, and is a measure of the data. The business problem decomposition algorithm module can be further used for summarizing business logic according to business scenes, classifying data which can be generated, summarizing data types of the data, determining the data types as dimension data or measurement data, and converting the business logic into CryptoSQL statement sets. The business problem decomposition algorithm module may also be used to, as shown in fig. 2, call the encryption dynamic table module to create an encryption dynamic table according to CryptoSQL statement sets, and parse out data sets (ranges), n layers of LODs (hierarchies), and aggregation algorithms (aggregations) of data in combination with encryption index keywords and data ownership in the encryption data table.

The encryption index and data ownership mapping module is used for establishing an encryption homomorphic mapping relation table aiming at a service scene, and is responsible for realizing the linkage of encryption index keywords, encryption sector identifiers, encryption data owners and encryption sector related blocks of encryption data through CryptoSQL statement sets, and is a calculation module for completing the encryption index and data ownership mapping.

The block chain data visual analysis system of the hierarchical drilling algorithm is used for establishing an encryption homomorphic mapping relation table for encryption index keywords, encryption sector identifiers, encryption data owners and encryption sector related blocks of encryption data, wherein the encryption homomorphic mapping relation table describes storage nodes, owners and traceable blocks to which encryption sectors with the encryption keywords belong. And the block chain data visual analysis system of the hierarchical drilling algorithm can be further used for realizing the linkage of encryption index keywords, encryption sector identifiers, encryption data owners and encryption sector related blocks of the encryption data through CryptoSQL statement sets. The CryptoSQL statement is a SQL statement of a custom additional encryption key index, data ownership, sector ID, hierarchical LOD of the blockchain data visualization analysis system based on a hierarchical drilling algorithm. The CryptoSQL statement supports interactive control of data samples to compute filter data samples and may enable encrypted data view generation and data drill-down computation supporting multi-layer LOD.

The encryption data grammar of CryptoSQL sentences is as follows, wherein the CryptoSQL sentence set in the embodiment of the application includes 1) SELECT DATA _owner create sentences used for selecting the authorization data from the dynamic encryption tables of the distributed encryption database to create the encryption data table. 2) The SELECT DATA _owner WHERE statement is used to select the validation data from the dynamic encryption table of the distributed encryption database. 3) The SELECT DATA _OWNER JOIN statement is used to link different encrypted data tables and encrypted dynamic tables to construct a new encrypted data dynamic view. 4) The SELECT DATA _OWNER CHECK statement is used to encrypt user ownership in a data table or an encrypted dynamic table. And the block chain data visualization analysis system of the hierarchical drilling algorithm is also used for receiving the encrypted data set (range), the n-layer LOD (hierarchy) and the aggregation algorithm (aggregation) from the business problem decomposition algorithm module and generating an encrypted dynamic table according to the encrypted index key words, the encrypted sector identifiers, the encrypted data owners and the encrypted sector related blocks in the existing encrypted data set. The encryption dynamic table is an encryption dataset describing the scope, hierarchy, aggregation, ownership of the encryption data. The blockchain data visualization analysis system of the hierarchical drilling algorithm can also be used for constructing a dynamic view of encrypted data according to an encrypted data set (range), an n-layer LOD (hierarchy) and an aggregation algorithm (aggregation). The encrypted data dynamic view is one of encrypted dynamic data tables, the encrypted data dynamic table with the level of 0 is automatically generated by a block chain data visual analysis system based on a hierarchical drilling algorithm, and the encrypted dynamic data table with the level of 1, 2.

And the encryption dynamic table module is used for generating an encryption dynamic table and is responsible for providing encryption data for the encryption index and data ownership mapping module and is an encryption data supporting module. The encryption sealing sector module is also used for sealing data, is responsible for mixing, slicing and encryption proving calculation of user data and encryption indexes, and is a data encryption processing module. The encryption seal sector module is also used for mixing, slicing, encryption proof calculation of the user data and the encryption index, generating an encryption seal sector (256M), and uploading the merck root (256 bytes) of the encryption seal sector onto the blockchain.

The multi-layer view construction module is used for constructing an encrypted data dynamic view with N layers based on the encrypted data table and the encrypted dynamic table, is responsible for constructing and maintaining the multi-layer view and is an intermediate module for multi-layer drilling of the encrypted data. And the multi-layer view construction module is also used for processing an encrypted data dynamic table with the level of 0 by adopting CryptoSQL sentences in a specific encrypted data set and outputting encrypted dynamic views with the levels of 1 and 2. According to the aggregation algorithm of the service problems, an interactive mode is adopted to control encrypted data samples, a calculation mode is adopted to screen the encrypted data samples, the encrypted data samples are gradually calculated from an n-layer encrypted dynamic view, the encrypted data samples are calculated to a 1-layer encrypted dynamic view, in the n-layer downloading calculation process of the encrypted data, whether the owners of the related encrypted data allow the data to be used or not is continuously inquired, and finally, the calculation result of the service problems is output and transmitted back to a user in the encrypted data mode.

The data dashboard module is used for displaying a visual interface of the blockchain data, wherein the visual interface of the blockchain data comprises a calculation result of a service problem, is responsible for visual display of the calculation result and is a data visual analysis display module. Further, in the process of n-layer drill-down calculation of the business problem, continuously inquiring whether the owner of the related encrypted data allows the data to be used or not, and finally outputting the calculation result of the business problem. And the user performs multidimensional analysis on the calculation result of the service problem through the drag operation, and displays data on a data instrument panel. Through OLAP multidimensional analysis functions such as drill-down, roll-up, rotation and linkage, various chart types and styles are adopted, so that data of a user are displayed in a more vivid mode. The data visual analysis display comprises a column diagram, a line diagram, a scatter diagram, a radar diagram, a GIS map, a Gantt chart and the like.

It should be noted that, the data processing system in the embodiment of the present application may be applied to data scenarios of massive users, data, and terminals, and is capable of fully storing the block chain storage function integration level, data security, data stability, system expandability, performance, and cost. And the method can also be applied to high-performance computing scenes, big data video cloud scenes and big data analysis application scenes. Specifically, the data of the user side can include data in the fields of weather, geological exploration, aerospace, engineering calculation, material engineering and the like, the service scene of the user is required to be a high-performance calculation scene, and the service in the high-performance calculation scene has very high performance requirements on a storage system of the back end, and the high-performance calculation scene comprises unified storage space, high-efficiency file retrieval, high-bandwidth throughput performance, high-reliability data security guarantee and the like. The requirements of large capacity, high read-write performance, high reliability, low delay, expandability and the like are provided for storage equipment in the fields of large data video cloud scenes, video high-definition technologies and ultrahigh-definition technologies, such as safe cities, broadcast media resources, film and television production, video websites and the like, the requirements form large data video cloud scenes, and supporters for back-end data storage with advanced technology and excellent performance are provided for the large data video cloud scenes.

In the high-performance computing scene, the big data video cloud scene and the big data analysis application scene, the needed storage space size (PB), encryption storage reading speed (GB/hour), file retrieval efficiency (GB/hour), service keyword set and other parameters are input to a service problem decomposition algorithm module, the parameters are converted into service logic through service scene analysis, analysis strategies such as analysis range, level of Detail (Detail Level), field aggregation and the like are generated, dynamic encryption data table is constructed into dynamic encryption views through CryptoSQL statement sets, meanwhile, multi-layer drilling is carried out on the generated encryption dynamic views in the calculation modes such as analysis strategy analysis Level calculation, measurement aggregation calculation, dimension aggregation calculation, encryption dynamic table calculation and the like, data calculation results of service problems are obtained, data instrument boards are generated from the data calculation results, and visual analysis on block chain data is completed.

Based on the data processing system and the application scenario, the embodiment of the application provides a data processing method, a device, equipment and a storage medium. The data processing method, apparatus, device and storage medium according to the embodiments of the present application will be described in detail with reference to fig. 3 and 5, and it should be noted that these embodiments are not intended to limit the scope of the present disclosure.

The following describes in detail a data processing method according to an embodiment of the present application with reference to fig. 3.

Fig. 3 is a flowchart of a data processing method according to an embodiment of the present application.

As shown in fig. 3, the data processing method may be applied to the data processing system shown in fig. 1, and the data processing method may specifically include the following steps:

Step 310, receiving a data visualization request sent by a user terminal, wherein the data visualization request comprises a service scene corresponding to the user terminal, step 320, acquiring a service problem of the service scene and an encrypted data table and an encrypted dynamic table corresponding to the service problem according to the service scene, wherein the encrypted data table comprises an encrypted index keyword and data ownership, the encrypted dynamic table is used for describing a storage node, an encrypted data owner and a traceable block of encrypted data, the encrypted data owner is affiliated with the encrypted sealed sector with the encrypted index keyword, the encrypted index keyword is associated with the encrypted data, step 330, constructing an encrypted data dynamic view with N layers based on the encrypted data table and the encrypted dynamic table, N is an integer larger than 1, step 340, performing drilling processing on the N layers in the encrypted data dynamic view through an aggregation algorithm corresponding to the service problem to obtain a drilling result of each of the N layers, and step 350, and displaying a block chain data visualization interface according to the encrypted data corresponding to the drilling result under the condition that the encrypted data owner allows the user terminal to use the encrypted data corresponding to the service problem.

Therefore, multi-layer drilling is carried out on the constructed encrypted data dynamic view according to the aggregation algorithm of the service problems, namely whether an encrypted data owner of the encrypted data corresponding to the service problems in each layer allows a user side to use the encrypted data in the layer is inquired, if the encrypted data owner allows the user side to use the encrypted data corresponding to the service problems, a block chain data visual interface is displayed according to the encrypted data corresponding to the drilling result, so that visual analysis on the block chain data is completed, in the process of executing a data visual request sent by the user side, user participation is not needed, authorization of the encrypted data can be completed, application of the encrypted data on the block chain is realized, more complete data can be obtained aiming at each service problem, and the integrity of content displayed in the block chain data visual interface is ensured.

The above steps are described in detail below, and are specifically described below.

First, referring to step 320, in one or more possible embodiments, step 320 may specifically include:

step 3201, acquiring N service questions corresponding to a service scene according to the service scene, wherein the service questions comprise a description field and an aggregation field, the description field is used for representing the type of data required by the service scene, and the aggregation field is used for representing the quantity of the data required by the service scene;

Step 3202, classifying the N service problems according to the description field and the aggregation field;

step 3203, summarizing service logic between service scenes according to the data types after the service problems are classified;

in step 3204, an encrypted data table and an encrypted dynamic table corresponding to the service problem are determined by the service logic.

Thus, without user participation, a plurality of business problems corresponding to the business scenes can be counted for each business scene, and then the business logic between the business scenes is concluded through analyzing the business logic between the business problems, so that the encryption data table and the encryption dynamic table corresponding to the business problems are determined according to the automatically analyzed business logic

In view of this, the above-described procedure of specifying the encrypted data table and the encrypted dynamic table corresponding to the service problem by the service logic will be described below. Here, the encryption dynamic table in the embodiment of the present application may be a database table formed by a series of encryption fields, and has attributes such as dimension, measurement, aggregation, and data ownership.

Based on the above, the step 3204 may specifically include the following possibilities. In one or more possible embodiments, the process of determining the encrypted data table may be as follows, i.e., the step 3204 may specifically include:

Gradually checking the data ownership of the service encryption data required by each service problem according to service logic, wherein the data ownership is used for representing authority information of an encryption data owner holding the service encryption data on the service encryption data;

Acquiring an encryption index keyword corresponding to the ownership of the data from a distributed storage block chain system according to the association information of a preset user side and a preset encryption index keyword;

an encrypted data table is constructed based on the data ownership and the encryption index key.

Illustratively, after determining the business questions and business logic, the data ownership of the business encryption data required for each business question is progressively queried to determine rights information of the encryption data owner holding the business encryption data to the business encryption data. And then, according to the association information of the preset user end and the preset encryption index keyword, acquiring the encryption index keyword corresponding to the ownership of the data from the distributed storage block chain system, and encrypting the data table by Hou Jian.

It should be noted that, before this step, the data processing method provided by the embodiment of the present application may further include:

receiving a data encryption storage request sent by at least one user terminal, wherein the data encryption storage request comprises user data and an encryption index keyword corresponding to the user data, the at least one terminal comprises a user terminal and a user terminal corresponding to an encryption data owner, and the user data comprises service encryption data;

Signing the user data according to the private key of the user side to obtain encrypted data;

Performing association mapping on the encryption index keywords and the encryption data through a distributed encryption storage network to obtain association information of preset encryption index keywords and preset encryption data;

Storing the encrypted data in an encrypted sealing sector, and recording associated information of a proving character string, a preset encryption index keyword and preset encrypted data in a blockchain of the distributed storage blockchain system, wherein the proving character string is used for representing the encrypted information and the stored information corresponding to the encrypted data.

The encryption index key words are generated by automatically capturing the data of the user side according to the frequency and the weight of the data in the service scene according to different service scenes, or the encryption index key words set by the user side are received by automatically capturing the data of the user side according to different service scenes.

In another or more possible embodiments, the process of determining the encryption dynamic table may be as follows, i.e., the step 3204 may specifically include:

Further, the step 3204 may specifically include:

acquiring storage nodes, encrypted data owners and traceable blocks of encrypted data, which are belonged to an encrypted sealing sector with an encrypted index keyword, from a distributed storage blockchain system according to the encrypted index keyword through CryptoSQL statement sets after service logic conversion;

and determining the mapping relation among the storage node to which the encryption sealing sector with the encryption index key belongs, the encrypted data owner and the traceable block of the encrypted data as an encryption dynamic table.

Illustratively, the data processing method provided by the embodiment of the application can support CryptoSQL statement sets of encrypted data authorization. The encryption index keyword, the encryption sector identifier, the encryption data owner and the encryption sector related block of the encryption data are linked through CryptoSQL statement sets, and CryptoSQL statement sets are SQL statements of the customized additional encryption keyword index, the data ownership, the sector ID and the hierarchical LOD.

Here, the CryptoSQL statement set in the embodiment of the present application includes 1) SELECT DATA _OWNER CREAT statement that is used to select the authorization data from the dynamic encryption tables of the distributed encryption database to create the encryption data table. 2) The SELECT DATA _owner WHERE statement is used to select the validation data from the dynamic encryption table of the distributed encryption database. 3) The SELECT DATA _OWNER JOIN statement is used to link different encrypted data tables and encrypted dynamic tables to construct a new encrypted data dynamic view. 4) The SELECT DATA _OWNER CHECK statement is used to encrypt user ownership in a data table or an encrypted dynamic table.

The encryption dynamic table with the encryption index key refers to a table formed by the encryption index key and the ownership of data in the existing encryption data table, and the encryption sector identifier, the encryption data owner, and the encryption sector related block. The encryption dynamic table is an encryption dataset describing the scope, hierarchy, aggregation, ownership of the encryption data. The encryption data table is a data set describing encryption index keys and data ownership.

Furthermore, referring to step 330, in one or more possible embodiments, step 330 may specifically include:

According to the encryption index key words, associating the data ownership, the storage node to which the encryption sealing sector belongs, the encryption data owner and the traceable block of the encryption data to obtain data associated with the service problem of the user side;

According to fields in data associated with the business problems of the user side, summarizing an encrypted data range, a data hierarchy and an aggregation algorithm of the data associated with the business problems of the user side, wherein the fields in the data associated with the business problems of the user side comprise classification fields and quantization fields;

according to the encrypted data range, the data hierarchy and the aggregation algorithm, the data associated with the business problem of the user side is divided into an encrypted data dynamic view with N layers.

Illustratively, as shown in fig. 2, the data types to which the data classification based on the data belongs are summarized, the classification fields are summarized based on the dimensions and the quantization fields are summarized based on the measures, then the analysis range, the hierarchy LOD and the field aggregation are summarized based on the classification fields and the quantization fields, so that the dynamic encryption data table is constructed into a dynamic encryption view through a CryptoSQL statement set (such as SELECT DATA _owner JOIN statement), and meanwhile, the generated encryption dynamic view is subjected to multi-layer drilling in the calculation modes of analysis strategy analysis level calculation, measure aggregation calculation, dimension aggregation calculation, encryption dynamic table calculation and the like.

Furthermore, referring to step 340, in one or more possible embodiments, the aggregation algorithm comprises at least one of a level algorithm, a metric aggregation algorithm, a dimension aggregation algorithm, an encryption dynamic table algorithm, based on which step 340 comprises:

sending authority inquiry requests to the encrypted data owners of the encrypted data of each level from the ith level in the N levels according to the direction of the i=i+1 level through an aggregation algorithm corresponding to the service problems, wherein the authority inquiry requests are used for inquiring whether the encrypted data owners allow the user side to use the encrypted data corresponding to the service problems or not, and i epsilon [0, N ];

and generating drilling results under the condition that confirmation information fed back by the encrypted data owners is received.

Illustratively, as shown in fig. 1, from N to 3, the dynamic view of encrypted data with 3 levels may include "level N" of level 1, "level N-1" of level 2, and "level 1" of level 3, where if i takes 1, then a permission query request may be sent to the encrypted data owner of the encrypted data of each level in the direction of i=i+1 from level 1, i.e. drill down, to obtain the drilling result of each level.

Then, referring to step 350, in one or more possible embodiments, prior to step 350, the method may further comprise:

Acquiring service encryption data corresponding to the encryption index key words from the encryption sealing sector, the storage node and the traceable block of the encryption data according to the association information of the preset encryption index key words and the preset encryption data;

based on this, this step 350 may specifically include:

Calculating a service answer corresponding to the service question according to the encrypted data corresponding to the drilling result;

and displaying the service answers on a block chain data visualization interface according to a preset display form by a multidimensional analysis algorithm of online analysis processing.

Here, the encrypted data corresponding to the drill result may be the service encrypted data corresponding to the encrypted index keyword. In summary, the data processing method provided by the embodiment of the application can receive a data visualization request sent by a user terminal, wherein the data visualization request comprises a service scene corresponding to the user terminal, and acquires a service problem of the service scene, an encrypted data table corresponding to the service problem and an encrypted dynamic table according to the service scene, wherein the encrypted data table comprises an encrypted index keyword and a data ownership, the encrypted dynamic table is used for describing a storage node, an encrypted data owner and a traceable block of encrypted data, the storage node, the encrypted data owner and the traceable block of the encrypted data belong to an encrypted sealing sector with the encrypted index keyword, an encrypted data dynamic view with N layers is constructed based on the encrypted data table and the encrypted dynamic table, drilling processing is carried out on the N layers in the encrypted data dynamic view through an aggregation algorithm corresponding to the service problem to obtain a drilling result of each of the N layers, and a block chain data visualization interface is displayed according to the encrypted data corresponding to the drilling result when the drilling result represents that the encrypted data owner allows the user terminal to use the encrypted data corresponding to the service problem. In this way, the service problems corresponding to the service scene are determined according to the data visualization request sent by the user terminal, an encryption data table and an encryption dynamic table are constructed according to the service operator problems, then an encryption data dynamic view with N layers is constructed based on the encryption data table and the encryption dynamic table, in this way, according to the aggregation algorithm of the service problems, multi-layer drilling is carried out on the constructed encryption data dynamic view, namely whether the encryption data owners of the encryption data corresponding to the service problems in each layer allow the user terminal to use the encryption data in the layer, if the encryption data owners allow the user terminal to use the encryption data corresponding to the service problems, the block chain data visualization interface is displayed according to the encryption data corresponding to the drilling result, thereby completing the visual analysis of the block chain data, in the process of executing the data visualization request sent by the user terminal, the user is not required to participate in, the authorization of the encryption data on the block chain is completed, the application of the encryption data on the block chain is realized, the complete data can be obtained for each service problem, and the integrity of the content displayed in the block chain data visualization interface is ensured.

Based on the same inventive concept, the application also provides a data processing device. This is described in detail with reference to fig. 4.

Fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application.

In some embodiments of the application, the data processing apparatus shown in FIG. 4 may be provided in a data processing system as shown in FIG. 1.

As shown in fig. 4, the data processing apparatus 40 may specifically include:

the receiving module 401 is configured to receive a data visualization request sent by a user terminal, where the data visualization request includes a service scenario corresponding to the user terminal;

the acquisition module 402 is configured to acquire, according to a service scenario, a service problem of the service scenario, an encrypted data table corresponding to the service problem, and an encrypted dynamic table, where the encrypted data table includes an encrypted index keyword and a data ownership;

a building module 403, configured to build a dynamic view of encrypted data with N levels, where N is an integer greater than 1, based on the encrypted data table and the encrypted dynamic table;

The processing module 404 is configured to drill N levels in the encrypted data dynamic view through an aggregation algorithm with a service problem, so as to obtain a drilling result of each level in the N levels;

and the display module 405 is configured to display a blockchain data visualization interface according to the encrypted data corresponding to the drilling result when the drilling result characterizes the encrypted data owner to allow the user side to use the encrypted data corresponding to the service problem.

The data processing apparatus 40 in the embodiment of the present application will be described in detail below.

In one or more alternative embodiments, the data processing apparatus 40 in embodiments of the present application further includes a classification module and a first generalization module, wherein,

The obtaining module 402 may be further configured to obtain N service questions corresponding to a service scenario according to the service scenario, where the service questions include a description field and an aggregation field, the description field is used to characterize a type of data required by the service scenario, and the aggregation field is used to characterize an amount of data required by the service scenario;

the classification module is used for classifying the N business problems according to the description field and the aggregation field;

the first induction module is used for inducing service logic between service scenes according to the data types after the service problems are classified;

the building module 403 may be further configured to create an encrypted dynamic table through the CryptoSQL statement set after the service logic conversion

In another or more alternative embodiments, the data processing apparatus 40 in embodiments of the present application further includes a determination module, wherein,

The obtaining module 402 may be further configured to obtain, through the CryptoSQL statement set, a storage node to which the encrypted sealing sector with the encrypted index key belongs, an encrypted data owner, and a traceable block of encrypted data;

And the determining module is used for determining the mapping relation among the storage node to which the encryption sealing sector with the encryption index key belongs, the encrypted data owner and the traceable block of the encrypted data as an encryption dynamic table.

In yet another or more alternative embodiments, the data processing apparatus 40 in embodiments of the present application further includes a second summarization module and a partitioning module, wherein,

The association module is used for associating the data ownership, the storage node to which the encryption sealing sector belongs, the encrypted data owner and the traceable block of the encrypted data according to the encryption index keyword to obtain data associated with the service problem of the user side;

The second induction module is used for inducing an encryption data range, a data hierarchy and an aggregation algorithm of the data associated with the business problems of the user terminal according to the fields in the data associated with the business problems of the user terminal, wherein the fields in the data associated with the business problems of the user terminal comprise a classification field and a quantization field;

and the dividing module is used for dividing the data associated with the business problems of the user side into an encrypted data dynamic view with N layers according to the encrypted data range, the data layers and the aggregation algorithm.

In yet another or more alternative embodiments, the aggregation algorithm includes at least one of a level algorithm, a metric aggregation algorithm, a dimension aggregation algorithm, and an encryption dynamic table algorithm, based on which the data processing apparatus 40 further includes a transmitting module and a generating module, wherein,

A transmitting module, configured to transmit, from an ith hierarchy of the N hierarchies, a permission query request to an encrypted data owner of the encrypted data of each hierarchy according to a direction of i=i+1 hierarchy, where the permission query request is used to query whether the encrypted data owner allows the user side to use the encrypted data corresponding to the service problem, i e [0, N ];

And the generation module is used for generating a drilling result under the condition that the confirmation information fed back by the encrypted data owner is received.

In yet another or more alternative embodiments, the data processing apparatus 40 in embodiments of the present application further includes a computing module, wherein,

The calculation module is used for calculating a service answer corresponding to the service question according to the encrypted data corresponding to the drilling result;

the display module 405 is further configured to display the answer to the service on the blockchain data visualization interface according to a preset display format through a multidimensional analysis algorithm of online analysis processing.

In yet another or more alternative embodiments, the acquisition module 402 may be further configured to acquire data ownership of an owner holding the service encrypted data based on the service encrypted data required for the service problem

The obtaining module 402 may be further configured to obtain, from the distributed storage blockchain system, an encrypted index keyword corresponding to the service encrypted data according to association information of a preset user identifier and a preset encrypted index keyword based on data ownership of an owner;

Acquiring an encryption sealing sector corresponding to the encryption index keyword according to the association information of the preset encryption index keyword and the preset encryption sealing sector;

And acquiring service encryption data corresponding to the encryption index keyword from the encryption sealing sector according to the association information of the preset encryption index keyword and the preset encryption data.

In yet another or more alternative embodiments, the data processing apparatus 40 in embodiments of the present application further includes an encryption module, a mapping module, and a storage module, wherein,

The receiving module 401 is further configured to receive a data encryption storage request sent by at least one end, where the data encryption storage request includes user data and an encryption index keyword corresponding to the user data, and the at least one end includes a user end and a user end corresponding to a holder, and the user data includes service encryption data;

the encryption module is used for signing the user data according to the private key of the user side to obtain encrypted data;

the mapping module is used for carrying out association mapping on the encryption index keywords and the encryption data through the distributed encryption storage network to obtain association information of preset encryption index keywords and preset encryption data;

The storage module is used for storing the encrypted data in the encrypted sealing sector, recording the proving character string, the preset encryption index key word and the associated information of the preset encrypted data in the block chain of the distributed storage block chain system, and the proving character string is used for representing the encrypted information and the storage information corresponding to the encrypted data.

The data processing device in the embodiment of the application can receive a data visualization request sent by a user side, the data visualization request comprises a service scene corresponding to the user side, an encrypted data table and an encrypted dynamic table corresponding to the service scene are obtained according to the service scene, the encrypted data table comprises an encrypted index key word and data ownership, the encrypted dynamic table is used for describing a storage node, an encrypted data owner and a traceable block of encrypted data, the encrypted data node is provided with the encrypted seal sector of the encrypted index key word, an encrypted data dynamic view with N layers is constructed based on the encrypted data table and the encrypted dynamic table, drilling processing is carried out on the N layers in the encrypted data dynamic view through an aggregation algorithm corresponding to the service problem to obtain a drilling result of each of the N layers, and a block chain data visualization interface is displayed according to the encrypted data corresponding to the drilling result when the drilling result represents that the encrypted data owner allows the user side to use the encrypted data corresponding to the service problem. In this way, the service problems corresponding to the service scene are determined according to the data visualization request sent by the user terminal, an encryption data table and an encryption dynamic table are constructed according to the service operator problems, then an encryption data dynamic view with N layers is constructed based on the encryption data table and the encryption dynamic table, in this way, according to the aggregation algorithm of the service problems, multi-layer drilling is carried out on the constructed encryption data dynamic view, namely whether the encryption data owners of the encryption data corresponding to the service problems in each layer allow the user terminal to use the encryption data in the layer, if the encryption data owners allow the user terminal to use the encryption data corresponding to the service problems, the block chain data visualization interface is displayed according to the encryption data corresponding to the drilling result, thereby completing the visual analysis of the block chain data, in the process of executing the data visualization request sent by the user terminal, the user is not required to participate in, the authorization of the encryption data on the block chain is completed, the application of the encryption data on the block chain is realized, the complete data can be obtained for each service problem, and the integrity of the content displayed in the block chain data visualization interface is ensured.

Based on the same inventive concept, the application also provides a computer device. This is described in detail with reference to fig. 5.

As shown in fig. 5, the computer device may comprise an electronic device or a server. The computer device may include, among other things, a processor 501 and a memory 502 storing computer program instructions.

In particular, the processor 501 may include a Central Processing Unit (CPU), or an Application SPECIFIC INTEGRATED Circuit (ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 502 may include mass storage for data or instructions. By way of example, and not limitation, memory 502 may comprise a hard disk drive (HARD DISK DRIVE, HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) drive, or a combination of two or more of the foregoing. Memory 502 may include removable or non-removable (or fixed) media, where appropriate. Memory 502 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 502 is a non-volatile solid state memory. In a particular embodiment, the memory 502 includes solid state storage (ROM). The ROM may be mask programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these, where appropriate.

The processor 501 implements any one of the data processing methods of the above embodiments by reading and executing computer program instructions stored in the memory 502.

In one example, the data processing device may also include a communication interface 503 and a bus 510. As shown in fig. 5, the processor 501, the memory 502, and the communication interface 503 are connected to each other by a bus 510 and perform communication with each other.

The communication interface 503 is mainly used to implement communication between each module, apparatus, unit and/or device in the embodiments of the present application.

Bus 510 includes hardware, software, or both, coupling components of the flow control device to one another. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 510 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, the application contemplates any suitable bus or interconnect.

The data processing apparatus may perform the data processing method in the embodiment of the present application, thereby implementing the data processing method and apparatus described in connection with fig. 1 to 4.

In addition, in connection with the data processing method in the above embodiment, the embodiment of the present application may be implemented by providing a computer readable storage medium. The computer readable storage medium having stored thereon computer program instructions which when executed by a processor implement any of the data processing methods of the above embodiments.

It should be understood that the application is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. The method processes of the present application are not limited to the specific steps described and shown, but various changes, modifications and additions, or the order between steps may be made by those skilled in the art after appreciating the spirit of the present application.

The functional blocks shown in the above block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. The present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and they should be included in the scope of the present application.

Claims

1. A method of data processing, comprising:

The method comprises the steps of obtaining a service problem of the service scene, an encryption data table and an encryption dynamic table corresponding to the service problem according to the service scene, wherein the encryption data table comprises encryption index keywords and data ownership;

And displaying a blockchain data visualization interface according to the encrypted data corresponding to the drilling result under the condition that the drilling result characterizes the encrypted data owner to allow the user side to use the encrypted data corresponding to the service problem.

2. The method according to claim 1, wherein the obtaining, according to the service scenario, a service problem of the service scenario and an encrypted data table and an encrypted dynamic table corresponding to the service problem includes:

According to the service scene, N service problems corresponding to the service scene are acquired, wherein the service problems comprise description fields and aggregation fields, the description fields are used for representing the types of data required by the service scene, and the aggregation fields are used for representing the quantity of the data required by the service scene;

Classifying the N business problems according to the description field and the aggregation field;

according to the data types of the classified service problems, summarizing service logic among the service scenes;

and determining an encryption data table and an encryption dynamic table corresponding to the service problem through the service logic.

3. The method of claim 2, wherein said determining, by said business logic, an encrypted data table and an encrypted dynamic table corresponding to said business problem comprises:

gradually checking the data ownership of the service encryption data required by each service problem according to the service logic, wherein the data ownership is used for representing authority information of an encryption data owner holding the service encryption data on the service encryption data;

And acquiring the encryption index key words corresponding to the data ownership from the distributed storage block chain system according to the association information of the preset user side and the preset encryption index key words.

4. The method of claim 3, wherein said determining, by said business logic, an encrypted data table and an encrypted dynamic table corresponding to said business problem comprises:

Acquiring a storage node, an encrypted data owner and a traceable block of encrypted data, which are provided with an encrypted sealing sector of the encrypted index key word, from the distributed storage block chain system according to the encrypted index key word through the CryptoSQL statement set after service logic conversion;

And determining the mapping relation among the storage node to which the encryption sealing sector with the encryption index key belongs, the encrypted data owner and the traceable block of the encrypted data as the encryption dynamic table.

5. The method of claim 1, wherein the constructing an encrypted data dynamic view having N levels based on the encrypted data table and the encrypted dynamic table comprises:

According to the encryption index key words, associating the data ownership, the storage node to which the encryption sealing sector belongs, the encrypted data owner and the traceable block of the encrypted data to obtain data associated with the service problem of the user side;

according to fields in data associated with the service problems of the user side, summarizing an encryption data range, a data hierarchy and an aggregation algorithm of the data associated with the service problems of the user side, wherein the fields in the data associated with the service problems of the user side comprise classification fields and quantization fields;

And dividing the data associated with the business problems of the user side into an encrypted data dynamic view with N layers according to the encrypted data range, the data hierarchy and the aggregation algorithm.

6. The method of claim 5, wherein the aggregation algorithm comprises at least one of a level algorithm, a metric aggregation algorithm, a dimension aggregation algorithm, an encryption dynamic table algorithm;

And performing drilling processing on N levels in the encrypted data dynamic view by an aggregation algorithm of the service problems to obtain a drilling result of each level in the N levels, wherein the drilling result comprises the following steps:

Sending, from an ith hierarchy of the N hierarchies, a permission query request to an encrypted data owner of encrypted data of each hierarchy according to the i=i+1 hierarchy direction through an aggregation algorithm corresponding to the service problem, where the permission query request is used to query whether the encrypted data owner allows the user side to use the encrypted data corresponding to the service problem, i e [0, N ];

And under the condition that confirmation information fed back by the encrypted data owner is received, generating a drilling result.

7. The method of claim 6, wherein the method further comprises, prior to the displaying a blockchain data visualization interface based on the encrypted data corresponding to the drill result:

Acquiring service encryption data corresponding to the encryption index key words from the encryption sealing sector, the storage node and the traceable block of the encryption data according to the association information of the preset encryption index key words and the preset encryption data, and displaying a blockchain data visualization interface according to the encryption data corresponding to the drilling result, wherein the method comprises the following steps:

And displaying the service answers on the block chain data visualization interface according to a preset display form through a multidimensional analysis algorithm of online analysis processing.

8. The method according to claim 7, wherein before the service encryption data corresponding to the encryption index key is obtained from the encryption seal sector, the storage node to which the encryption data belongs, and the traceable block of the encryption data according to the association information of the preset encryption index key and the preset encryption data, the method further comprises:

receiving a data encryption storage request sent by at least one user terminal, wherein the data encryption storage request comprises user data and an encryption index keyword corresponding to the user data, the at least one terminal comprises the user terminal and a user terminal corresponding to an encrypted data owner, and the user data comprises the service encryption data;

storing the encrypted data in an encrypted sealing sector, and recording a proving character string and associated information of the preset encryption index key word and the preset encrypted data in a blockchain of a distributed storage blockchain system, wherein the proving character string is used for representing the encrypted information and the stored information corresponding to the encrypted data.

9. A data processing apparatus, the apparatus comprising:

The receiving module is used for receiving a data visualization request sent by a user terminal, wherein the data visualization request comprises a service scene corresponding to the user terminal;

The system comprises an acquisition module, an encryption dynamic table, a storage node, an encryption data owner and a traceable block of encryption data, wherein the acquisition module is used for acquiring service problems of the service scene, an encryption data table and an encryption dynamic table corresponding to the service problems, and the encryption data table comprises an encryption index keyword and data ownership;

The processing module is used for carrying out drilling processing on N levels in the encrypted data dynamic view through an aggregation algorithm of the service problems to obtain a drilling result of each level in the N levels;

And the display module is used for displaying a block chain data visual interface according to the encrypted data corresponding to the drilling result under the condition that the drilling result characterizes the encrypted data owner to allow the user side to use the encrypted data corresponding to the service problem.

10. A computer device comprising a processor and a memory storing computer program instructions;

the processor, when executing the computer program instructions, implements a data processing method as claimed in any one of claims 1-8.

11. A storage medium having stored thereon computer program instructions which, when executed by a processor, implement the data processing method of any of claims 1-8.