A data sharing method and device based on data sharing center

Abstract

The present invention provides a data sharing method and device based on a data sharing center, which obtains multiple business data clusters of a data sharing end, constructs a matching field group of the business data cluster based on the field similarity of the fields of each business data in any business data cluster, then selects seed fields or singular fields from each matching field group of any business data cluster, obtains the mapping relationship between the seed field or singular field and the unified standard field issued by the supervision end, and based on the mapping relationship between the seed field or singular field and the unified standard field, determines the mapping relationship between the fields in each matching field group of the business data cluster and the unified standard field and constructs a mapping table of the business data cluster, and then based on the mapping table of each business data cluster of the data sharing end, converts and stores the reported data of the data sharing end, thereby improving the overall efficiency of data conversion and storage of the data sharing center.

Description

Technical Field

[0001] The present invention relates to the technical field of data sharing, and in particular, to a data sharing method and device based on a data sharing center. Background Art

[0002] In modern supervision and enterprise management, the interconnection and sharing of data have become key requirements. With the increasing complexity and informatization of business, regulatory authorities and enterprises are facing an increasing amount and variety of data. In order to effectively grasp the real-time status of enterprise operations, monitor business activities, identify risks and ensure compliance, regulatory authorities require "data connection" and "business connection", that is, data can be transmitted and shared smoothly between different departments, systems, and even industries. To achieve this goal, a centralized data sharing and exchange center can be built, and the regulatory side issues unified data standards or rules. The data reported by each data sharing side will be converted and stored according to the unified standards or rules for the regulatory side to conduct unified supervision and for each data sharing side to share and exchange data.

[0003] In order to convert the data reported by each data sharing side according to unified standards or rules, since the business data corresponding to the same business type from different data sources is heterogeneous, there are differences in the names, data formats, and units of the business fields corresponding to the same business field between different data sources. Therefore, it is necessary to establish a data mapping dictionary to store the mapping relationships (including name, format, and unit mappings) between the fields of different data sources and the fields in the unified standard.

[0004] However, due to the existence of multiple data sources, and the complexity of business types and large amounts of business data, the efficiency of establishing a data mapping dictionary for each data source for each business type is low. In addition, the business specifications within an enterprise often change, resulting in changes in the business data structure of the same business type. Once the data mapping dictionary is not updated in time, the data reported by the data sharing side cannot be converted into the standard format specified by the regulatory side in time, and business supervision and business data sharing cannot be carried out in time. Therefore, improving the field mapping efficiency is an urgent problem to be solved. Summary of the Invention

[0005] The present invention provides a data sharing method and device based on a data sharing center to solve the defect of poor field mapping efficiency in the prior art.

[0006] The present invention provides a data sharing method based on a data sharing center, including:

[0007] Obtaining a plurality of business data clusters of a data sharing side; any business data cluster contains business data of associated business types;

[0008] Construct a matching field group for any business data cluster based on the field similarity of each business data field in the business data cluster;

[0009] Select seed fields or singular fields from each matching field group of any business data cluster, obtain the mapping relationship between the seed fields or singular fields and the unified standard fields issued by the supervision end, and based on the mapping relationship between the seed fields or singular fields and the unified standard fields, determine the mapping relationship between the fields in each matching field group of any business data cluster and the unified standard fields and construct the mapping table of any business data cluster;

[0010] Based on the mapping tables of each business data cluster of the data sharing end, convert and store the reported data of the data sharing end.

[0011] According to a data sharing method based on a data sharing center provided by the present invention, constructing a matching field group for any business data cluster based on the field similarity of each business data field in the business data cluster includes:

[0012] Determine a candidate matching field group based on the name similarity of each business data field in any business data cluster;

[0013] Construct a matching field group for any business data cluster based on the name similarity, numerical unit matching result, and data type matching result of each field in the candidate matching field group.

[0014] According to a data sharing method based on a data sharing center provided by the present invention, constructing a matching field group for any business data cluster based on the name similarity, numerical unit matching result, and data type matching result of each field in the candidate matching field group includes:

[0015] If the name similarity between any two fields in the candidate matching field group is higher than a preset threshold and both the numerical unit matching result and the data type matching result indicate a match, determine that the two fields match, and put the matching fields in the candidate matching field group into the same matching field group.

[0016] According to a data sharing method based on a data sharing center provided by the present invention, multiple business data clusters of any data sharing end are determined in the following manner:

[0017] Based on the database table structures corresponding to each business type of any data sharing end, determine the foreign keys in each database table;

[0018] Based on the foreign keys in the database tables corresponding to each business type, determine the associated business types, and construct business data clusters based on the business data of the associated business types.

[0019] According to a data sharing method based on a data sharing center provided by the present invention, the data sharing method further includes:

[0020] Obtain a data access request from a data request end, and perform identity verification on the data request end;

[0021] After the data request end passes the identity verification, obtain the data description of the data to be accessed in the data access request and the business type of the data to be accessed;

[0022] Based on the business type of the data to be accessed in the business data cluster corresponding to the data request end, obtain a mapping table of the business type of the data to be accessed corresponding to the data request end;

[0023] After retrieving the data to be accessed based on the data description of the data to be accessed, perform conversion on the data to be accessed based on the mapping table of the business type of the data to be accessed corresponding to the data request end, and send the converted data to the data request end.

[0024] According to a data sharing method based on a data sharing center provided by the present invention, performing identity verification on the data request end includes:

[0025] Obtain the identity information included in the data access request of the data request end;

[0026] Send a randomly specified business type to the data request end, so that the data request end returns any business data corresponding to the randomly specified business type encrypted with a private key;

[0027] Based on the identity information included in the data access request of the data request end, determine a mapping table of the business type corresponding to the data sharing end indicated by the identity information for the randomly specified business type;

[0028] Decrypt the business data returned by the data request end based on the public key corresponding to the data sharing end indicated by the identity information. If the decryption is successful, perform conversion on the decrypted data based on the mapping table of the business type corresponding to the data sharing end indicated by the identity information for the randomly specified business type, and determine that the data request end passes the identity verification when all field conversions are successful.

[0029] According to a data sharing method based on a data sharing center provided by the present invention, the public key and private key corresponding to any data sharing end are determined based on the following method:

[0030] Randomly generate a seed polynomial, and obtain the coefficient matrix of the seed polynomial, as well as the upper triangular matrix and the lower triangular matrix corresponding to the coefficient matrix;

[0031] Randomly generate two matrices with the same size as the coefficient matrix and elements of 0 or 1, and use them as the adjoint matrix of the upper triangular matrix corresponding to the coefficient matrix and the adjoint matrix of the lower triangular matrix respectively;

[0032] Multiply the product of the upper triangular matrix corresponding to the coefficient matrix and its adjoint matrix by the product of the lower triangular matrix corresponding to the coefficient matrix and its adjoint matrix to obtain the public key;

[0033] Based on a plurality of random numbers, select multiple columns from the public key as the public key corresponding to any data sharing end, and select multiple rows from the inverse matrix of the public key based on the plurality of random numbers to obtain the private key corresponding to any data sharing end and return it to any data sharing end.

[0034] The present invention also provides a data sharing device based on a data sharing center, including:

[0035] A cluster acquisition unit, configured to acquire a plurality of service data clusters of a data sharing end; each service data cluster contains service data of associated service types;

[0036] A field matching unit, configured to construct a matching field group of any service data cluster based on the field similarity of the fields of each service data in any service data cluster;

[0037] A mapping table construction unit, configured to respectively select a seed field or a singular field from each matching field group of any service data cluster, obtain the mapping relationship between the seed field or the singular field and the unified standard field issued by the supervision end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determine the mapping relationship between the fields in each matching field group of any service data cluster and the unified standard field and construct the mapping table of any service data cluster;

[0038] A data conversion and storage unit, configured to convert and store the reported data of the data sharing end based on the mapping tables of each service data cluster of the data sharing end.

[0039] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the data sharing method based on a data sharing center as described in any one of the above.

[0040] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the data sharing method based on a data sharing center as described in any one of the above.

[0041] The present invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the data sharing method based on a data sharing center as described in any one of the above.

[0042] A data sharing method and apparatus based on a data sharing center provided by the present invention, by obtaining multiple service data clusters of a data sharing end, constructing a matching field group of the service data cluster based on the field similarity of each service data in any service data cluster, then respectively selecting a seed field or a singular field from each matching field group of any service data cluster, obtaining the mapping relationship between the seed field or the singular field and a unified standard field issued by a supervision end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determining the mapping relationship between the fields in each matching field group of the service data cluster and the unified standard field and constructing a mapping table of the service data cluster. Furthermore, based on the mapping tables of each service data cluster of the data sharing end, the reported data of the data sharing end is converted and stored, improving the efficiency of field mapping, thereby improving the overall efficiency of data conversion and storage in the data sharing center. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0044] Figure 1 is one of the flow diagrams of a data sharing method based on a data sharing center provided by the present invention;

[0045] Figure 2 is another flow diagram of a data sharing method based on a data sharing center provided by the present invention;

[0046] Figure 3 is the structural diagram of a data sharing apparatus based on a data sharing center provided by the present invention;

[0047] Figure 4 is the structural diagram of an electronic device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0049] Figure 1 FIG. 4 is a schematic flowchart of a data sharing method based on a data sharing center provided by the present invention. This method is executed by the data sharing center. As Figure 1 shown, this method includes:

[0050] Step 110: Obtain multiple business data clusters of the data sharing end; any business data cluster contains business data of associated business types;

[0051] Step 120: Based on the field similarity of each business data field in any business data cluster, construct a matching field group for the any business data cluster;

[0052] Step 130: Select seed fields or singular fields from each matching field group of any business data cluster, obtain the mapping relationship between the seed fields or singular fields and the unified standard fields issued by the supervision end, and based on the mapping relationship between the seed fields or singular fields and the unified standard fields, determine the mapping relationship between the fields in each matching field group of the any business data cluster and the unified standard fields and construct a mapping table for the any business data cluster;

[0053] Step 140: Based on the mapping tables of each business data cluster of the data sharing end, convert and store the reported data of the data sharing end.

[0054] Specifically, in the scenario of enterprise business data sharing, each enterprise can act as a data sharing end to report data and as a data requesting end to request shared data. Among them, data reporting means reporting its own business data to the data sharing center. The data sharing center performs standard conversion according to the unified data standard issued by the supervision end, converts the enterprise's business data into data that meets the standards set by the supervision end, and then stores it in the data sharing center; requesting shared data means requesting to obtain the business data of other enterprises from the data sharing center.

[0055] Considering that although the business specifications of different enterprises are different, the business data is heterogeneous, and the business types within the enterprise are complex and the volume of business data is large, the business specifications within the enterprise are relatively unified, and the design ideas of the field names, formats, and numerical units of each field in the business data of related businesses are more similar. Therefore, in order to improve the mapping efficiency of mapping the fields of enterprise business data to the standard fields set by the regulatory end, the business data of different business types within the enterprise can be clustered according to the relevance of business types, and the business data of related business types can be placed in a cluster for associated mapping.

[0056] Specifically, for any data sharing end, the data sharing center can request multiple business data clusters from the data sharing end. Among them, any business data cluster contains the business data of related business types. In one embodiment, the data sharing end can determine the foreign keys in each database table based on the database table structure corresponding to each business type of the data sharing end, and determine the related business types based on the foreign keys in the database tables corresponding to each business type. Among them, if the foreign key of a database table of one business type corresponds to the primary key of a database table of another business type, then these two business types can be related business types. Subsequently, a business data cluster is constructed based on the business data of related business types. For any business data cluster of the data sharing end, a matching field group of the business data cluster is constructed based on the field similarity of each business data in the business data cluster, and the fields within the same matching field group of the business data cluster are mapped to the same standard field, thereby forming a mapping table of the business data cluster. Subsequently, all business data corresponding to the business types of this business data cluster can use the mapping table of this business data cluster for standard conversion.

[0057] In some embodiments, when constructing the matching field group of any business data cluster, multiple candidate matching field groups can be determined based on the name similarity of the fields of each business data in the business data cluster. Wherein, each candidate matching field group contains one or more fields, and when there are multiple fields, the name similarity between the multiple fields is higher than a preset similarity threshold. Subsequently, based on the name similarity, numerical unit matching result, and data type matching result of each field in the candidate matching field group, the matching field group of the business data cluster is constructed. Here, when further screening the candidate matching field group to determine the matching field group, the fields in the candidate matching field group that meet the following conditions can be screened out and put into the same matching field group: the name similarity between any two fields is higher than the preset threshold, and both the numerical unit matching result and the data type matching result indicate a match. The preset threshold here can be slightly lower than the preset similarity threshold mentioned above. It should be noted that if any field in the candidate matching field group does not meet the above conditions with other fields or the candidate matching field group contains only one field, then this field is set as a singular field, and a separate matching field group is created for this field.

[0058] In the process of mapping the fields within the same matching field group of the business data cluster to the standard fields, a seed field or a singular field can be selected from the matching field group first. Wherein, if the matching field group contains multiple fields, a field is randomly selected as the seed field, and if the matching field group contains only one field, then this field is used as the singular field. Obtain the mapping relationship between the seed field or the singular field and the unified standard field issued by the supervision end. Based on the mapping relationship between the seed field or the singular field and the unified standard field, the mapping relationship between all fields in the matching field group and the unified standard field can be determined. After determining the mapping relationship between all fields in each matching field group and the unified standard field, the above mapping relationship can be converted into a mapping table, thereby obtaining the mapping table of the business data cluster. Based on the mapping tables of each business data cluster of the data sharing end, the reported data of the data sharing end can be converted and stored.

[0059] It should be noted that the mapping tables of the various business data clusters of each data sharing end are constructed and stored by the data sharing center. Therefore, the mapping tables of the various business data clusters of any data sharing end are unknown to all data sharing ends including that data sharing end. In addition, the mapping tables of the various business data clusters of any data sharing end reflect to a certain extent the data structure of the business data of that data sharing end, and the business data of different data sharing ends are heterogeneous. Therefore, the mapping tables of the various business data clusters of any data sharing end can be used to distinguish different data sharing ends. Coupled with the fact that the mapping tables are unknown and have a certain degree of security for all data sharing ends, they can be used as one of the bases for confirming the identity of the data sharing end, thereby enhancing the security of data sharing.

[0060] In some embodiments, when there is a data sharing requirement, such as Figure 2 shown, the sharing of business data can be achieved in the following manner:

[0061] Step 210, obtain the data access request of the data request end and confirm the identity of the data request end;

[0062] Step 220, after the data request end passes the identity confirmation, obtain the data description of the data to be accessed in the data access request and the business type of the data to be accessed;

[0063] Step 230, based on the business type of the data to be accessed, obtain the mapping table of the business type corresponding to the data to be accessed in the business data cluster corresponding to the data request end;

[0064] Step 240, after retrieving the data to be accessed based on the data description of the data to be accessed, convert the data to be accessed based on the mapping table of the business type corresponding to the data to be accessed in the data request end, and send the converted data to the data request end.

[0065] Here, after receiving the data access request from the data request end, the data sharing center can confirm the identity of the data request end that initiated the request based on the data access request, and then proceed with the subsequent data sharing process after the identity confirmation is passed to ensure the data security of the data sharing center. After the data request end passes the identity confirmation, obtain the data description of the data to be accessed carried in the data access request (used to retrieve the data to be accessed in the data sharing center) and the business type of the data to be accessed. Determine the business data cluster corresponding to the business type of the data to be accessed at the data request end, and obtain the mapping table of the business data cluster as the mapping table of the business type of the data to be accessed corresponding to the data request end. After retrieving the data to be accessed based on the data description of the data to be accessed, convert the data to be accessed based on the mapping table of the business type of the data to be accessed corresponding to the data request end, and send the converted data to the data request end. It should be noted that the reason why the mapping table corresponding to the business type of the data to be accessed is used to convert the data to be accessed before sending it to the data requester is that the mapping table is invisible to the data requester, so the data requester does not have the ability to directly parse the data to be accessed. The more important reason is to avoid the data requester from inferring the mapping table after getting the unconverted data to be accessed, breaking the security feature that the mapping table is invisible to the data requester / data sharing end.

[0066] In some embodiments, during the process of authenticating the identity of a data requestor, the data sharing center may obtain the identity information included in the data access request of the data requestor. This identity information indicates the identification information assigned to the data requestor by the data sharing center when it acts as a data sharing end. Subsequently, the data sharing center sends a randomly specified service type to the data requestor, so that the data requestor returns any service data corresponding to the randomly specified service type encrypted with its private key. After receiving the service data encrypted with the private key sent by the data requestor, based on the identity information included in the data access request of the data requestor, the mapping table corresponding to the randomly specified service type of the data sharing end indicated by this identity information can be determined, and the service data returned by the data requestor is decrypted based on the public key corresponding to the data sharing end indicated by this identity information. If the decryption is successful, the decrypted data is further transformed based on the mapping table corresponding to the randomly specified service type of the data sharing end indicated by this identity information, and when all fields are successfully transformed, it is determined that the data requestor has passed the identity authentication. It can be seen that a two-factor authentication is adopted in the identity authentication process: on the one hand, the public key and private key are used to authenticate the identity of the data requestor; on the other hand, after the identity of the data requestor is successfully authenticated based on the public key and private key, further confirmation is carried out based on the mapping table. This two-factor authentication method utilizes the particularity of the mapping table that can be used to distinguish different data sharing ends and the security that is invisible to the data sharing end / data requestor, improving the accuracy of the data sharing center in authenticating the identity of the data requestor, thereby enhancing data security.

[0067] In some other embodiments, the public key and private key corresponding to any data sharing end can be determined based on the following method:

[0068] Randomly generate a seed polynomial, and obtain the coefficient matrix of the seed polynomial and the upper triangular matrix and lower triangular matrix corresponding to the coefficient matrix. The seed polynomial is sparse, and the upper triangular matrix and lower triangular matrix corresponding to its coefficient matrix are obtained by setting the elements below the diagonal of the coefficient matrix to 0 and setting the elements above the diagonal of the coefficient matrix to 0, respectively;

[0069] Randomly generate two matrices with the same size as the above coefficient matrix and elements of 0 or 1, and use them as the adjoint matrix of the upper triangular matrix corresponding to the coefficient matrix and the adjoint matrix of the lower triangular matrix, respectively;

[0070] Multiply the product of the upper triangular matrix corresponding to the coefficient matrix and its adjoint matrix by the product of the lower triangular matrix corresponding to the coefficient matrix and its adjoint matrix to obtain the public key;

[0071] Based on multiple random numbers (the random numbers are less than or equal to the number of rows of the coefficient matrix), multiple columns are selected from the public key to form a new matrix, and this new matrix is saved as the public key corresponding to this data sharing end. Then, based on the above multiple random numbers, multiple rows are selected from the inverse matrix of the public key to obtain the private key corresponding to this data sharing end and return it to this data sharing end.

[0072] In summary, the data sharing method provided by the embodiments of the present invention obtains multiple service data clusters of a data sharing end, constructs a matching field group for the service data cluster based on the field similarity of the fields of each service data in any service data cluster, then respectively selects seed fields or singular fields from each matching field group of any service data cluster, obtains the mapping relationship between the seed fields or singular fields and the unified standard fields issued by the supervision end, and based on the mapping relationship between the seed fields or singular fields and the unified standard fields, determines the mapping relationship between the fields in each matching field group of the service data cluster and the unified standard fields and constructs the mapping table of the service data cluster. Furthermore, based on the mapping tables of each service data cluster of the data sharing end, the reported data of the data sharing end is converted and stored, improving the efficiency of field mapping, thereby improving the overall efficiency of data conversion and storage in the data sharing center.

[0073] The data sharing device provided by the present invention is described below. The data sharing device described below can be correspondingly referred to the data sharing method described above.

[0074] Based on any of the above embodiments, Figure 3 is a schematic structural diagram of the data sharing device based on the data sharing center provided by the present invention. This device is deployed at the data sharing center, as Figure 3 shown. This device includes:

[0075] A cluster acquisition unit 310, configured to acquire multiple service data clusters of a data sharing end; each service data cluster contains service data of associated service types;

[0076] A field matching unit 320, configured to construct a matching field group for any service data cluster based on the field similarity of the fields of each service data in any service data cluster;

[0077] A mapping table construction unit 330, configured to respectively select seed fields or singular fields from each matching field group of any service data cluster, obtain the mapping relationship between the seed fields or singular fields and the unified standard fields issued by the supervision end, and based on the mapping relationship between the seed fields or singular fields and the unified standard fields, determine the mapping relationship between the fields in each matching field group of any service data cluster and the unified standard fields and construct the mapping table of any service data cluster;

[0078] A data conversion and storage unit 340 is configured to convert and store the reported data of the data sharing end based on the mapping tables of each business data cluster of the data sharing end.

[0079] The data sharing device provided by the embodiment of the present invention obtains multiple business data clusters of the data sharing end, constructs a matching field group of any business data cluster based on the field similarity of each business data field in any business data cluster, then selects a seed field or a singular field from each matching field group of any business data cluster, obtains the mapping relationship between the seed field or the singular field and the unified standard field issued by the supervision end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determines the mapping relationship between the fields in each matching field group of the business data cluster and the unified standard field and constructs the mapping table of the business data cluster. Furthermore, based on the mapping tables of each business data cluster of the data sharing end, the reported data of the data sharing end is converted and stored, improving the efficiency of field mapping, thereby improving the overall efficiency of data conversion and storage in the data sharing center.

[0080] Based on any of the above embodiments, constructing a matching field group of any business data cluster based on the field similarity of each business data field in any business data cluster includes:

[0081] Determining a candidate matching field group based on the name similarity of each business data field in any business data cluster;

[0082] Constructing the matching field group of any business data cluster based on the name similarity, numerical unit matching result, and data type matching result of each field in the candidate matching field group.

[0083] Based on any of the above embodiments, constructing the matching field group of any business data cluster based on the name similarity, numerical unit matching result, and data type matching result of each field in the candidate matching field group includes:

[0084] If the name similarity of any two fields in the candidate matching field group is higher than a preset threshold and both the numerical unit matching result and the data type matching result indicate a match, determine that the any two fields match, and put the matching fields in the candidate matching field group into the same matching field group.

[0085] Based on any of the above embodiments, multiple business data clusters of any data sharing end are determined in the following manner:

[0086] Based on the database table structures corresponding to each business type of any data sharing end, determine the foreign keys in each database table;

[0087] Based on the foreign keys in the database tables corresponding to each business type, determine the associated business types, and construct business data clusters based on the business data of the associated business types.

[0088] Based on any of the above embodiments, the data sharing method further includes:

[0089] Obtain the data access request of the data request end, and perform identity verification on the data request end;

[0090] After the data request end passes the identity verification, obtain the data description of the data to be accessed in the data access request and the business type of the data to be accessed;

[0091] Based on the business type of the data to be accessed in the business data cluster corresponding to the data request end, obtain the mapping table of the business type of the data to be accessed corresponding to the data request end;

[0092] After retrieving the data to be accessed based on the data description of the data to be accessed, convert the data to be accessed based on the mapping table of the business type of the data to be accessed corresponding to the data request end, and send the converted data to the data request end.

[0093] Based on any of the above embodiments, performing identity verification on the data request end includes:

[0094] Obtain the identity information included in the data access request of the data request end;

[0095] Send a randomly specified business type to the data request end, so that the data request end returns any business data corresponding to the randomly specified business type encrypted with the private key;

[0096] Based on the identity information included in the data access request of the data request end, determine the mapping table of the business type corresponding to the randomly specified business type of the data sharing end indicated by the identity information;

[0097] Decrypt the business data returned by the data request end based on the public key of the data sharing end indicated by the identity information. If the decryption is successful, convert the decrypted data based on the mapping table of the business type corresponding to the randomly specified business type of the data sharing end indicated by the identity information, and determine that the data request end passes the identity verification when all fields are successfully converted.

[0098] Based on any of the above embodiments, the public key and private key corresponding to any data sharing end are determined in the following manner:

[0099] Randomly generate a seed polynomial, and obtain the coefficient matrix of the seed polynomial, as well as the upper triangular matrix and the lower triangular matrix corresponding to the coefficient matrix;

[0100] Randomly generate two matrices with the same size as the coefficient matrix and elements of 0 or 1, and use them as the adjoint matrix of the upper triangular matrix corresponding to the coefficient matrix and the adjoint matrix of the lower triangular matrix respectively;

[0101] Multiply the product of the upper triangular matrix corresponding to the coefficient matrix and its adjoint matrix by the product of the lower triangular matrix corresponding to the coefficient matrix and its adjoint matrix to obtain the public key;

[0102] Based on multiple random numbers, select multiple columns from the public key as the public key corresponding to any data sharing end, and select multiple rows from the inverse matrix of the public key based on the multiple random numbers to obtain the private key corresponding to any data sharing end and return it to any data sharing end.

[0103] Figure 4 It is a schematic structural diagram of the electronic device provided by the present invention. As Figure 4 shown, the electronic device may include: a processor 410, a memory 420, a communication interface 430, and a communication bus 440. Among them, the processor 410, the memory 420, and the communication interface 430 complete mutual communication through the communication bus 440. The processor 410 can call the logical instructions in the memory 420 to execute a data sharing method based on a data sharing center. The method includes: obtaining multiple service data clusters of a data sharing end; each service data cluster contains service data of related service types; based on the field similarity of each service data in any service data cluster, construct a matching field group of any service data cluster; select a seed field or a singular field from each matching field group of any service data cluster, obtain the mapping relationship between the seed field or the singular field and the unified standard field issued by the supervision end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determine the mapping relationship between the fields in each matching field group of any service data cluster and the unified standard field and construct a mapping table of any service data cluster; based on the mapping tables of each service data cluster of the data sharing end, convert and store the reported data of the data sharing end.

[0104] In addition, when the logical instructions in the above-mentioned memory 420 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0105] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a data sharing method based on a data sharing center provided by the above-mentioned various methods. The method includes: obtaining a plurality of service data clusters at a data sharing end; each service data cluster contains service data of associated service types; based on the field similarity of each service data in any service data cluster, constructing a matching field group for the any service data cluster; respectively selecting a seed field or a singular field from each matching field group of any service data cluster, obtaining a mapping relationship between the seed field or the singular field and a unified standard field issued by a supervision end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determining a mapping relationship between the fields in each matching field group of the any service data cluster and the unified standard field and constructing a mapping table for the any service data cluster; based on the mapping tables of each service data cluster at the data sharing end, converting and storing the reported data at the data sharing end.

[0106] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements a data sharing method based on a data sharing center provided above. The method includes: obtaining a plurality of service data clusters of a data sharing end; each service data cluster contains service data of an associated service type; based on the field similarity of the fields of each service data in any one of the service data clusters, constructing a matching field group of the any one of the service data clusters; respectively selecting a seed field or a singular field from each matching field group of any one of the service data clusters, obtaining a mapping relationship between the seed field or the singular field and a unified standard field issued by a supervision end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determining a mapping relationship between the fields in each matching field group of the any one of the service data clusters and the unified standard field and constructing a mapping table of the any one of the service data clusters; based on the mapping tables of the respective service data clusters of the data sharing end, converting and storing the reported data of the data sharing end.

[0107] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0108] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0109] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data sharing method based on a data sharing center, characterized in that: include: Obtain multiple business data clusters from the data sharing end; Any business data cluster contains business data of the associated business type; Based on the field similarity of the fields of each business data in any business data cluster, construct a matching field group of any business data cluster; Select a seed field or a singular field from each matching field group of any business data cluster, obtain a mapping relationship between the seed field or the singular field and the unified standard field issued by the supervisory end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determine the mapping relationship between the fields in each matching field group of any business data cluster and the unified standard field and construct a mapping table for any business data cluster; Based on the mapping table of each business data cluster of the data sharing terminal, the reported data of the data sharing terminal is converted and stored; The multiple business data clusters of any data sharing end are determined based on the following method: Based on the database table structure corresponding to each business type at any data sharing end, determine the foreign keys in each database table; Based on the foreign keys in the database table corresponding to each business type, the associated business type is determined, and a business data cluster is constructed based on the business data of the associated business type.

2. A data sharing method based on a data sharing center according to claim 1, characterized in that: Based on the field similarity of the fields of each business data in any business data cluster, a matching field group of any business data cluster is constructed, including: Determine a candidate matching field group based on the name similarity of the fields of each business data in any business data cluster; Based on the name similarity, numerical unit matching result and data type matching result of each field in the candidate matching field group, a matching field group of any business data cluster is constructed.

3. According to claim 2, a data sharing method based on a data sharing center, based on the name similarity, numerical unit matching result and data type matching result of each field in the candidate matching field group, constructing the matching field group of any business data cluster, comprising: If the name similarity of any two fields in the candidate matching field group is higher than a preset threshold and both the numerical unit matching result and the data type matching result indicate a match, it is determined that the any two fields match, and the matching fields in the candidate matching field group are placed in the same matching field group.

4. A data sharing method based on a data sharing center according to any one of claims 1 to 3, characterized in that: The data sharing method further includes: Obtaining a data access request from a data requesting end, and confirming the identity of the data requesting end; After the data request end passes the identity confirmation, obtaining the data description of the data to be accessed and the business type of the data to be accessed in the data access request; Based on the business data cluster corresponding to the business type of the data to be accessed at the data requesting end, obtaining a mapping table corresponding to the business type of the data to be accessed at the data requesting end; After the data to be accessed is retrieved based on the data description of the data to be accessed, the data to be accessed is converted based on a mapping table of the data request end corresponding to the business type of the data to be accessed, and the converted data is sent to the data request end.

5. A data sharing method based on a data sharing center according to claim 4, characterized in that: Confirming the identity of the data requesting end includes: Obtaining identity information contained in the data access request of the data request end; Sending a randomly specified service type to the data request end, so that the data request end returns any service data corresponding to the randomly specified service type encrypted by using a private key; Based on the identity information included in the data access request of the data requesting end, determining a mapping table corresponding to the randomly specified service type of the data sharing end indicated by the identity information; The business data returned by the data requesting end is decrypted based on the public key corresponding to the data sharing end indicated by the identity information. If the decryption is successful, the decrypted data is converted based on the mapping table corresponding to the randomly specified business type based on the data sharing end indicated by the identity information, and when all fields are converted successfully, it is determined that the data requesting end has passed the identity confirmation.

6. A data sharing method based on a data sharing center according to claim 5, characterized in that: The public key and private key corresponding to any data sharing end are determined based on the following method: Randomly generate a seed polynomial, and obtain a coefficient matrix of the seed polynomial and an upper triangular matrix and a lower triangular matrix corresponding to the coefficient matrix; Randomly generate two matrices of the same size as the coefficient matrix and with elements of 0 or 1, as adjoint matrices of the upper triangular matrix and the lower triangular matrix corresponding to the coefficient matrix, respectively; Multiply the product of the upper triangular matrix corresponding to the coefficient matrix and its adjoint matrix by the product of the lower triangular matrix corresponding to the coefficient matrix and its adjoint matrix to obtain a public key; Based on multiple random numbers, multiple columns are selected from the public key as the public key corresponding to any one of the data sharing terminals, and based on the multiple random numbers, multiple rows are selected from the inverse matrix of the public key to obtain the private key corresponding to any one of the data sharing terminals and return it to any one of the data sharing terminals.

7. A data sharing device based on a data sharing center, characterized in that: include: A cluster acquisition unit, used to acquire multiple business data clusters from a data sharing terminal; Any business data cluster contains business data of the associated business type; A field matching unit, configured to construct a matching field group of any business data cluster based on the field similarity of the fields of each business data in any business data cluster; A mapping table construction unit, used to select a seed field or a singular field from each matching field group of any business data class cluster, obtain a mapping relationship between the seed field or the singular field and the unified standard field issued by the supervision end, and based on the mapping relationship between the seed field or the singular field and the unified standard field, determine the mapping relationship between the fields in each matching field group of any business data class cluster and the unified standard field and construct a mapping table for any business data class cluster; A data conversion storage unit, used for converting and storing the reported data of the data sharing terminal based on the mapping table of each business data cluster of the data sharing terminal; The multiple business data clusters of any data sharing end are determined based on the following method: Based on the database table structure corresponding to each business type at any data sharing end, determine the foreign keys in each database table; Based on the foreign keys in the database table corresponding to each business type, the associated business type is determined, and a business data cluster is constructed based on the business data of the associated business type.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, a data sharing method based on a data sharing center as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements a data sharing method based on a data sharing center as described in any one of claims 1 to 6.

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