A blockchain-based data security sharing method and system

Abstract

The application relates to the technical field of data sharing, in particular to a data security sharing method and system based on a blockchain. The method comprises the following steps: setting a plurality of data ports based on business requirement parameters, and establishing a repository of each data port; constructing an index relationship model and an associated data chain according to all data ports, wherein the associated data chain comprises a record library of each data port; acquiring input data of each data port, judging the data type of the input data, and setting a processing strategy of the input data according to a judgment result; judging whether an update instruction of the index relationship model is generated according to a preset update time node; constructing a plurality of data ports based on a blockchain technology and business requirements, and dynamically adjusting the processing strategy of the input data of each data port by constructing an index association model between all data ports, so that the security and query efficiency of data sharing in different ports are improved.

Description

Technical Field

[0001] This application relates to the field of data sharing technology, and in particular to a data security sharing method and system based on blockchain. Background Technology

[0002] Data sharing has fostered collaboration and progress across industries, bringing unprecedented convenience to technological applications and development. However, while bringing convenience, data sharing also faces numerous challenges, with issues such as data leaks, privacy violations, and data misuse occurring frequently during the sharing process.

[0003] Existing data sharing solutions have many problems, such as: reliance on third-party institutions, making them vulnerable to single-point attacks or data tampering; lack of transparent records in the sharing process, making it difficult to trace data usage; and reliance on traditional databases, resulting in high costs for data integrity verification. Summary of the Invention

[0004] The purpose of this application is to provide a data security sharing method and system based on blockchain to solve the above-mentioned technical problems, aiming to improve the efficiency and security of data sharing between different business departments.

[0005] In some embodiments of this application, a blockchain-based data security sharing method is provided, characterized by comprising: Multiple data ports are set based on business requirements parameters, and a storage library is established for each data port; An index relationship model and associated data chain are constructed based on all data ports, and the associated data chain includes a record library for each data port; Obtain the input data from each data port, determine the data type of the input data, and set the input data processing strategy based on the determination result; Determine whether to generate an update instruction for the index relationship model based on the preset update time node; When multiple data ports are configured, the following are included: Establish a data port sequence A, A=(a1,a2…a ... i …a n ), where a i Let be the i-th data port; n is the number of data ports.

[0006] In some embodiments of this application, the construction of the index relationship model includes: Based on the data port sequence A, set a sequentially. i For the target data port; Generate the correlation evaluation values ​​between the target data port and each data port; Establish a sequence of associated evaluation values ​​B, B=(b1,b2…b) for the target data port. i…b n ), wherein b i is an association evaluation value of the target data port and the i-th data port; n is the number of association evaluation values; pre-setting a first association evaluation value threshold B1 and a second association evaluation value threshold B2; wherein B1<B2; if B1≤b i <B2, setting the i-th data port as a first-level associated port of the target data port; if b i <B1, setting the i-th data port as a second-level associated port of the target data port; constructing an index sub-model of the target data port based on all first-level associated ports according to all first-level associated ports and all second-level associated ports; sequentially constructing index sub-models for each data port; constructing an index association model according to all index sub-models.

[0007] In some embodiments of the present application, generating the association evaluation values between the target data port and each data port comprises: sequentially setting a i as a port to be compared according to the data port sequence A; generating an association evaluation value b between the target data port and the port to be compared; b= β i *k i; wherein r1 is the number of association evaluation indicators; β i is an influence factor of the i-th association evaluation indicator; k i is a reference value of the i-th association evaluation indicator generated based on the target data port and the port to be compared; sequentially generating association evaluation values between the target data port and each data port.

[0008] In some embodiments of the present application, setting the processing strategy for input data according to the judgment result comprises: sequentially setting a i as a port to be processed according to the data port sequence A; judging the data category of the input data of the port to be processed; if the input data is first-level data, generating a first-level processing strategy for the input data; if the input data is second-level data, generating a second-level processing strategy for the input data.

[0009] In some embodiments of the present application, the first-level processing strategy comprises: generating a storage data packet according to the input data; setting the index sub-model of the port to be processed as the target index model; selecting the to-be-synchronized repositories and the to-be-mapped repositories storing data packets according to the target index model; acquiring the quantity c1 of to-be-synchronized repositories; generating c1 first-level synchronization packets according to the stored data packets; sending all the first-level synchronization packets to each to-be-synchronized repository according to a first-level synchronization instruction; acquiring the quantity c2 of to-be-mapped repositories; generating c2 first-level mapping packets according to the stored data packets; sending all the first-level mapping packets to each to-be-mapped repository according to a first-level mapping instruction.

[0010] In some embodiments of the present application, the first-level synchronization instruction comprises: generating a transmission evaluation value d; d= η i *j i; wherein r2 is the quantity of transmission evaluation indexes; η i is an influence factor of the i-th transmission evaluation index; j i is a reference value of the i-th transmission evaluation index; setting a synchronization quantity threshold C1 according to the transmission evaluation value d; if c1<C1, generating a first-level sending instruction, and sending all first-level synchronization packets once according to the first-level sending instruction; if c1>C1, generating a second-level sending instruction, setting a single sending quantity C1 according to the second-level sending instruction, and sending the first-level synchronization packets in batches according to the single sending quantity C1.

[0011] In some embodiments of the present application, the secondary processing strategy comprises: generating a supplementary data packet and a recording data packet according to input data; setting the index sub-model of the port to be processed as the target index model; selecting to-be-supplemented repositories of the supplementary data packet according to the target index model; acquiring the quantity v1 of to-be-supplemented repositories; generating v1 update data packets according to the compensation data packets, and sending all the update data packets to each to-be-supplemented repository; generating n recording data packets, and sending all the recording data packets to each recording repository.

[0012] In some embodiments of the present application, judging whether to generate an update instruction for an index relationship model comprises: establishing an index sub-model sequence P, P=(p1, p2…p i…p n ), where p i Let n be the index sub-model for the i-th data port; n is the number of index sub-models. Based on the index sub-model sequence P, p is set sequentially. i The sub-model to be evaluated; Generate the index evaluation value g of the sub-model to be evaluated at the current update time node; Generate the index evaluation value of each index sub-model at the current update time node in sequence; Auxiliary differences for each index sub-model at the current update time node are generated based on preset index evaluation value thresholds; The first evaluation value is set based on the processing results of all index evaluation values; The second evaluation value is set based on the processing results of all auxiliary differences; The update evaluation value f for the current update time node is set based on the weighted result of the first evaluation value and the second evaluation value; Preset update evaluation value threshold F1; If f > F1, a first-level update instruction is generated at the current update time node.

[0013] In some embodiments of this application, a blockchain-based data security sharing system is provided, including: The port unit is used to set multiple data ports based on business requirement parameters and to establish a storage library for each data port. The port unit is also used to establish a data port sequence A, A=(a1,a2…a ... i …a n ), where a i Let n be the i-th data port; n is the number of data ports. The processing unit is used to construct an index relationship model and an associated data chain based on all data ports, wherein the associated data chain includes a record library for each data port; The update unit is used to determine whether to generate an update instruction for the index relationship model based on a preset update time node; The processing unit includes: The first processing module is used to acquire input data from each data port; The first judgment module is used to determine the data type of the input data and set the processing strategy for the input data based on the judgment result.

[0014] In some embodiments of this application, the processing unit further includes: The second processing module is used to set a sequentially according to the data port sequence A. i For the target data port; Generate the correlation evaluation values ​​between the target data port and each data port; Establish an association evaluation value sequence B of the target data port, B=(b₁, b₂…b i …b n ), wherein b i is the association evaluation value of the target data port and the i-th data port; n is the number of association evaluation values; Pre-set a first association evaluation value threshold B₁ and a second association evaluation value threshold B₂; and B₁ < B₂; If B₁ ≤ b i < B₂, setting the i-th data port as a first-level associated port of the target data port; If b i < B₁, setting the i-th data port as a second-level associated port of the target data port; Construct an index sub-model of the target data port according to all first-level associated ports based on all first-level associated ports and all second-level associated ports; Sequentially construct the index sub-model of each data port; Construct an index association model according to all index sub-models.

[0015] Compared with the prior art, the beneficial effects of a block chain-based data security sharing method and system in the embodiments of the present application are: A plurality of data ports are constructed based on block chain technology and business requirements, and the processing strategy for input data of each data port is dynamically adjusted by constructing an index association model between all data ports, which improves the security and query efficiency of data sharing among different ports.

[0016] Data ports are established to realize data interaction among all storage repositories, and by monitoring the real-time status of each data port, the changed data in each storage repository can be shared in time, which improves the efficiency and real-time performance of data sharing. Description of Drawings

[0017] Figure 1 is a schematic flow chart of a block chain-based data security sharing method in a preferred embodiment of the embodiments of the present application. Detailed Description of the Embodiments

[0018] The following further describes the specific embodiments of the present application in detail with reference to the accompanying drawings and embodiments. The embodiments are used to illustrate the present application, but not to limit the scope of the present application.

[0019] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0020] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0021] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0022] like Figure 1 As shown, a preferred embodiment of this application provides a blockchain-based data security sharing method, comprising: S101: Set up multiple data ports based on business requirement parameters and establish a storage library for each data port; S102: Construct an index relationship model and associated data chain based on all data ports. The associated data chain includes the record library of each data port. S103: Obtain the input data from each data port, determine the data type of the input data, and set the input data processing strategy based on the determination result; S1O4: Determine whether to generate an update instruction for the index relationship model based on the preset update time node; When multiple data ports are configured, the following are included: Establish a data port sequence A, A=(a1,a2…a ... i …a n ), where a i Let be the i-th data port; n is the number of data ports.

[0023] Specifically, by analyzing business requirements, a plurality of business departments (such as sales department, marketing department, finance department, operation department, inventory department, etc.) are generated, and a plurality of requirement ports are established according to the requirement data categories of each business department (for example, order port of the sales department, customer profile port, budget control port of the finance department, accounts receivable and payable port, etc.). A plurality of data ports are established based on all requirement ports, wherein a single data port corresponds to one requirement port, and a storage repository corresponding to each data port is constructed (that is, the associated data of the current requirement port is stored. For example, if the current requirement port is the customer profile port, the identity profile data of each customer is stored in the storage repository), and a transmission channel between the storage repository and the corresponding data port is established.

[0024] Specifically, by constructing a record library corresponding to each data port, operations such as data query and modification of each data port are synchronously recorded, thereby reducing the risk of data tampering.

[0025] Specifically, constructing the index relationship model comprises the following steps: Set a sequentially according to the data port sequence A i as the target data port; generate an association evaluation value between the target data port and each data port; establish an association evaluation value sequence B of the target data port, B=(b1, b2...b i ...b n ), where b i is the association evaluation value between the target data port and the i-th data port; n is the number of association evaluation values; pre-set a first association evaluation value threshold B1 and a second association evaluation value threshold B2; and B1 < B2; if B1 ≤ b i < B2, setting the i-th data port as a first-level associated port of the target data port; if b i < B1, setting the i-th data port as a second-level associated port of the target data port; constructing an index sub-model of the target data port according to all first-level associated ports based on all first-level associated ports and all second-level associated ports; constructing index sub-models for each data port in sequence; constructing an index association model based on all index sub-models.

[0026] Specifically, the first association evaluation value threshold and the second association evaluation value threshold are set according to historical parameters, and when the real-time association evaluation value is the second association evaluation value threshold, the corresponding port to be compared is the target data port itself.

[0027] Specifically, when the real-time correlation evaluation value is between the first correlation evaluation value threshold and the second correlation evaluation value threshold, it indicates that there is a large sharing demand between the current data port and the target data port. The current data port is set as the first-level correlation port of the target data port, and a dedicated index channel is built between the two to increase the data interaction capability between the two storage databases.

[0028] Specifically, when the real-time correlation evaluation value is lower than the first correlation evaluation value threshold, it indicates that the interaction requirement between the current data port and the target data port is low. At this time, the current data port is set as the secondary correlation port of the target data, and only a data synchronization channel needs to be established between the two.

[0029] Specifically, an index sub-model for the target data port is generated based on all established dedicated index channels and all data synchronization channels.

[0030] Specifically, the higher the correlation evaluation value, the greater the need for data sharing and interaction between the target data port and the port to be compared.

[0031] Specifically, when generating the correlation evaluation values ​​between the target data port and each data port, the following steps are included: Based on the data port sequence A, set a sequentially. i Ports to be compared; Generate a correlation evaluation value b between the target data port and the port to be compared; b= β i *k i; Where r1 is the number of correlation evaluation indicators; β i Let k be the influence factor of the i-th correlation evaluation index; i It is a reference value for the i-th associated evaluation index generated based on the target data port and the port to be compared; The associated evaluation values ​​of the target data port and each data port are generated sequentially.

[0032] Specifically, the correlation evaluation indicators include, but are not limited to, the similarity of data stored in the storage repository (the higher the similarity, the larger the corresponding value), the data query frequency between ports (the higher the query frequency, the larger the corresponding value), and other parameters. By quantifying each correlation evaluation indicator, the reference values ​​of each correlation evaluation indicator are made to be within the same range.

[0033] Specifically, the influence factors of each related evaluation indicator can be set according to the degree of mapping between the data ports' interaction needs. The higher the degree of mapping, the larger the value of the corresponding influence factor. The mapping relationship between the two can be set according to historical parameters.

[0034] It is understandable that in the above embodiments, multiple data ports are established by splitting data according to business requirements, and personalized index sub-models are constructed based on the interaction requirements between each data port to achieve data sharing between different data ports, thereby improving the security and query efficiency of data sharing across different ports.

[0035] In a preferred embodiment of this application, when setting the processing strategy for input data based on the judgment result, the following is included: Based on the data port sequence A, set a sequentially. i Ports to be processed; Determine the data type of the input data at the port to be processed; If the input data is first-level data, generate a first-level processing strategy for the input data; If the input data is secondary data, generate a secondary processing strategy for the input data.

[0036] Specifically, the first-level data consists of newly added data for the port to be processed, and the second-level data consists of the operation parameters for the port to be processed, including data query and data modification. Specifically, the primary processing strategies include: Generate a storage data package based on the input data; Set the index sub-model of the port to be processed as the target index model; Select the storage library that needs to be synchronized and the storage library that needs to be mapped based on the target index model; Get the number of storage libraries that need to be synchronized, c1; Generate c1 first-level synchronization packets based on the stored data packets; All first-level synchronization packets are sent to each storage repository that needs to be synchronized according to the first-level synchronization command; Get the number of storage libraries to be mapped, c2; Generate c2 first-level mapping packets based on the stored data packets; All first-level mapping packets are sent to the respective storage repositories that need to be mapped, according to the first-level mapping instructions.

[0037] Specifically, the storage library to be synchronized is the storage library corresponding to the first-level associated port of the port to be processed. The storage library to be mapped is the storage library corresponding to the second-level associated port of the port to be processed.

[0038] Specifically, when new data is detected on the port to be processed, the new data is encapsulated to generate a storage data packet, and the encapsulated data is copied according to the number of databases to be synchronized, generating multiple first-level synchronization packets, and then broadcast globally to improve data sharing efficiency.

[0039] Specifically, after compressing the newly added data, a single first-level mapping package is generated, and the first-level mapping package is copied according to the number of repositories to be mapped to generate the same number of first-level mapping packages. The packages are then synchronized to each corresponding repository to be mapped, thereby completing the global sharing of the newly added data.

[0040] Specifically, the first-level synchronization instruction includes: Generating a transmission evaluation value d; d= η i *j i; wherein r2 is the number of transmission evaluation indicators; η i is the influence factor of the i-th transmission evaluation indicator; j i is the reference value of the i-th transmission evaluation indicator; Setting a synchronization quantity threshold C1 according to the transmission evaluation value d; If c1 < C1, a first-level sending instruction is generated, and all first-level synchronization packages are sent in a single transmission according to the first-level sending instruction; If c1 > C1, a second-level sending instruction is generated, a single transmission quantity C2 is set according to the second-level sending instruction, and the first-level synchronization packages are sent in batches according to the single transmission quantity C2.

[0041] Specifically, the transmission evaluation indicators include but are not limited to a plurality of parameters such as the number of first-level synchronization packages (the larger the number, the larger the corresponding reference value) and the memory of a single first-level synchronization package (the higher the memory, the larger the corresponding reference value), and each transmission evaluation indicator is quantified such that all transmission evaluation indicators fall within the same value range.

[0042] Specifically, the influence factor of each transmission evaluation indicator can be set according to its mapping degree to transmission pressure; the higher the mapping degree, the larger the reference value of the corresponding influence factor, and the mapping relationship between the two can be set according to historical parameters.

[0043] Specifically, the larger the transmission evaluation value, the greater the current transmission pressure, and the smaller the corresponding synchronization quantity threshold C1, and the mapping relationship between the two can be set according to historical parameters.

[0044] Specifically, when the number of first-level synchronization packages exceeds the synchronization quantity threshold C1, batch transmission is performed according to the second-level sending instruction, which avoids data loss caused by an excessively large single transmission quantity. The batch order can be arranged in descending order according to the association evaluation value between the port to be processed and each repository to be synchronized, thereby improving the transmission security and sharing efficiency of data and reducing the bearing pressure of network transmission.

[0045] It is understood that in the above embodiments, data interaction between all storage databases is realized by establishing data ports, and the changing data in each storage database is shared in a timely manner by monitoring the real-time status of each data port, thereby improving the efficiency and real-time performance of data sharing.

[0046] In a preferred embodiment of this application, the secondary processing strategy includes: Generate supplementary data packets and record data packets based on the input data; Set the index sub-model of the port to be processed as the target index model; Select the supplementary storage database for the supplementary data package based on the target index model; Get the number of storage units that need to be replenished, v1; Generate v1 update data packets based on the compensation data packets, and send all update data packets to each storage database that needs to be supplemented; Generate n record data packets and send all record data packets to the respective record databases.

[0047] Specifically, a supplementary data package (i.e., the content to be modified in the storage) is generated based on the actual data modified and the difference between the modified data, and a record data package (i.e., the relevant records of the modification process) is generated based on the modification process.

[0048] Specifically, it is necessary to supplement the storage database, namely the storage database of each primary associated port corresponding to the port to be processed. By using different synchronization methods, the data synchronization cost can be reduced. That is, in each data port where the data interaction demand with the port to be processed is weak, only the data modification process is recorded, without the need to make substantial modifications to the data, thereby reducing the additional consumption caused by frequent modification of database content.

[0049] It is understood that in the above embodiments, multiple data ports are constructed based on blockchain technology and business needs, and the processing strategy of input data of each data port is dynamically adjusted by constructing an index association model between all data ports, thereby improving the security and query efficiency of data sharing across different ports.

[0050] In a preferred embodiment of this application, determining whether to generate an update instruction for the index relationship model includes: Establish an indexed sub-model sequence P, P=(p1, p2…p i …p n ), where p i Let n be the index sub-model for the i-th data port; n is the number of index sub-models. Based on the index sub-model sequence P, p is set sequentially. i The sub-model to be evaluated; Generate the index evaluation value g of the sub-model to be evaluated at the current update time node; Generate the index evaluation value of each index sub-model at the current update time node in sequence; Auxiliary differences for each index sub-model at the current update time node are generated based on preset index evaluation value thresholds; The first evaluation value is set based on the processing results of all index evaluation values; The second evaluation value is set based on the processing results of all auxiliary differences; The update evaluation value f for the current update time node is set based on the weighted result of the first evaluation value and the second evaluation value; Preset update evaluation value threshold F1; If f > F1, a first-level update instruction is generated at the current update time node.

[0051] Specifically, the corresponding index evaluation value is set according to the data retrieval efficiency of the current data port (i.e., the speed at which data is retrieved from different storage databases according to its own operational needs) and data processing capability. The higher the index evaluation value, the higher the data retrieval efficiency and data processing capability of the current data port.

[0052] Specifically, the index evaluation value threshold can be set based on historical parameters. When the real-time index evaluation value is lower than the preset index evaluation value threshold, it indicates that the current index sub-model's operating efficiency has not met expectations and needs to be updated promptly.

[0053] Specifically, the first evaluation value is set based on the sum of all index evaluation values. The larger the sum, the smaller the corresponding first evaluation value. The mapping relationship between the two can be set based on historical parameters.

[0054] Specifically, if the index evaluation value of the current index sub-model is greater than the preset index evaluation value threshold, the auxiliary difference value of the current index sub-model is set to 0. If the index evaluation value of the current index sub-model is lower than the preset index evaluation value threshold, the absolute value of the difference between the two is set to the auxiliary difference value of the current index sub-model.

[0055] Specifically, a second evaluation value is set based on the sum of all auxiliary differences. The larger the sum, the larger the corresponding second evaluation value. The mapping relationship between the two can be set according to historical parameters, and the first evaluation value and the second evaluation value have the same range.

[0056] Specifically, an updated evaluation value is generated by weighting the first evaluation value and the second evaluation value. The weight coefficients of the first evaluation value and the second evaluation value can be set according to historical parameters, and the sum of the weight coefficients of the two is 1.

[0057] Specifically, the larger the update evaluation value is, the lower the operating efficiency of the current index relationship model is. It is necessary to optimize the current index relationship model according to the data call parameters between the current update time node and the previous update time node, so as to improve the data sharing efficiency.

[0058] As another preferred embodiment of the block chain-based data security sharing method in any of the above preferred embodiments, this preferred embodiment provides a block chain-based data security sharing method, comprising: a port unit, configured to set a plurality of data ports based on service requirement parameters, and establish a storage for each data port; the port unit is further configured to establish a data port sequence A, A=(a1, a2...a i ...a n ), wherein a i is the i-th data port; n is the number of data ports; a processing unit, configured to construct an index relationship model and an associated data chain according to all data ports, wherein the associated data chain includes a record library for each data port; an update unit, configured to determine whether to generate an update instruction for the index relationship model according to a preset update time node; the processing unit comprises: a first processing module, configured to acquire input data of each data port; a first judgment module, configured to judge a data type of the input data, and set a processing strategy for the input data according to a judgment result.

[0059] Specifically, the processing unit further comprises: a second processing module, configured to sequentially set a i as a target data port according to the data port sequence A; generate association evaluation values between the target data port and each data port; establish an association evaluation value sequence B of the target data port, B=(b1, b2...b i ...b n ), wherein b i is the association evaluation value between the target data port and the i-th data port; n is the number of association evaluation values; presetting a first association evaluation value threshold B1 and a second association evaluation value threshold B2; and B1<B2; if B1≤b i <B2, setting the i-th data port as a first-level associated port of the target data port; if b i <B1, setting the i-th data port as a second-level associated port of the target data port; Construct an index sub-model for the target data port based on all first-level associated ports and all second-level associated ports. Construct index sub-models for each data port in sequence; Construct an index association model based on all index sub-models.

[0060] Based on the first concept of this application, multiple data ports are constructed based on blockchain technology and business needs. By constructing an index association model among all data ports, the processing strategy of input data of each data port is dynamically adjusted to improve the security and query efficiency of data sharing across different ports.

[0061] According to the second concept of this application, a data port is established to realize data interaction between all storage databases, and by monitoring the real-time status of each data port, the changed data in each storage database is shared in a timely manner, thereby improving the efficiency and real-time performance of data sharing.

[0062] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application.

Claims

1. A data security sharing method based on blockchain, characterized in that, Comprising: setting a plurality of data ports based on service requirement parameters, and establishing a storage repository for each data port; constructing an index relationship model and an associated data chain according to all data ports, wherein the associated data chain includes a recording library for each data port; acquiring input data of each data port, determining a data type of the input data, and setting a processing strategy for the input data according to a determination result; determining whether to generate an update instruction for the index relationship model according to a preset update time node; wherein setting the plurality of data ports comprises: Establish a data port sequence A, A=(a1,a2…a ... i …a n ), where a i Let be the i-th data port; n is the number of data ports.

2. The data security sharing method based on blockchain as described in claim 1, characterized in that, constructing the index relationship model comprises: Based on the data port sequence A, set a sequentially. i For the target data port; generating association evaluation values between a target data port and each data port; Establish a sequence of associated evaluation values ​​B, B=(b1,b2…b) for the target data port. i …b n ), where b i The evaluation value associated with the target data port and the i-th data port; n is the number of associated evaluation values; presetting a first association evaluation value threshold B1 and a second association evaluation value threshold B2, wherein B1 < B2; If B1 ≤ b i < B2, setting the i-th data port as a first-level associated port of the target data port; if b i <B1, set the i-th data port as the secondary associated port of the target data port; constructing an index sub-model of the target data port according to all first-level association ports based on all first-level association ports and all second-level association ports; constructing index sub-models for each data port sequentially; constructing an index association model according to all the index sub-models.

3. The blockchain-based secure data sharing method as described in claim 2, characterized in that, generating the association evaluation values between the target data port and each data port comprises: Based on the data port sequence A, set a sequentially. i Ports to be compared; generating an association evaluation value b between the target data port and a port to be compared; b= b i *k i; Where r1 is the number of correlation evaluation indicators; β i Let k be the influence factor of the i-th correlation evaluation index; i It is a reference value for the i-th associated evaluation index generated based on the target data port and the port to be compared; generating the association evaluation values between the target data port and each data port sequentially.

4. The blockchain-based secure data sharing method as described in claim 2, characterized in that, setting the processing strategy for the input data according to the determination result comprises: Based on the data port sequence A, set a sequentially. i Ports to be processed; determining a data category of input data of a port to be processed; if the input data is first-level data, generating a first-level processing strategy for the input data; if the input data is second-level data, generating a second-level processing strategy for the input data.

5. The blockchain-based secure data sharing method as described in claim 4, characterized in that, the first-level processing strategy comprises: generating a storage data packet according to the input data; setting the index sub-model of the port to be processed as a target index model; selecting to-be-synchronized storage repositories and to-be-mapped storage repositories for the storage data packet according to the target index model; acquiring a quantity c1 of the to-be-synchronized storage repositories; generating c1 first-level synchronization packets according to the storage data packet; sending all the first-level synchronization packets to each to-be-synchronized storage repository according to a first-level synchronization instruction; acquiring a quantity c2 of the to-be-mapped storage repositories; generating c2 first-level mapping packets according to the storage data packet; sending all the first-level mapping packets to each to-be-mapped storage repository according to a first-level mapping instruction.

6. The blockchain-based secure data sharing method as described in claim 5, characterized in that, the first-level synchronization instruction comprises: generating a transmission evaluation value d; d= or i *j i; Where r2 is the number of transmission evaluation indicators; η i Let j be the influence factor of the i-th transmission evaluation index; i This is the reference value for the i-th transmission evaluation index; setting a synchronization quantity threshold C1 according to the transmission evaluation value d; if c1 < C1, generating a first-level sending instruction, and sending all the first-level synchronization packets in one time according to the first-level sending instruction; if c1 > C1, generating a second-level sending instruction, setting a single sending quantity C1 according to the second-level sending instruction, and sending the first-level synchronization packets in batches according to the single sending quantity C1.

7. The blockchain-based secure data sharing method as described in claim 5, characterized in that, the second-level processing strategy comprises: generating a supplementary data packet and a recording data packet according to the input data; setting the index sub-model of the port to be processed as a target index model; selecting to-be-supplemented storage repositories for the supplementary data packet according to the target index model; acquiring a quantity v1 of the to-be-supplemented storage repositories; generating v1 update data packets according to the supplementary data packet, and sending all the update data packets to each to-be-supplemented storage repository; generating n recording data packets, and sending all the recording data packets to each recording library.

8. The blockchain-based secure data sharing method as described in claim 7, characterized in that, determining whether to generate the update instruction for the index relationship model comprises: Establish an indexed sub-model sequence P, P=(p1, p2…p i …p n ), where p i Let n be the index sub-model for the i-th data port; n is the number of index sub-models. Based on the index sub-model sequence P, p is set sequentially. i The sub-model to be evaluated; Generate the index evaluation value g of the sub-model to be evaluated at the current update time node; Generate the index evaluation value of each index sub-model at the current update time node in sequence; Auxiliary differences for each index sub-model at the current update time node are generated based on preset index evaluation value thresholds; The first evaluation value is set based on the processing results of all index evaluation values; The second evaluation value is set based on the processing results of all auxiliary differences; The update evaluation value f for the current update time node is set based on the weighted result of the first evaluation value and the second evaluation value; Preset update evaluation value threshold F1; If f > F1, a first-level update instruction is generated at the current update time node.

9. A blockchain-based secure data sharing system, employing the blockchain-based secure data sharing method according to any one of claims 1-8, characterized in that, include: The port unit is used to set multiple data ports based on business requirement parameters and to establish a storage library for each data port. The port unit is also used to establish a data port sequence A, A=(a1,a2…a ... i …a n ), where a i Let n be the i-th data port; n is the number of data ports. The processing unit is used to construct an index relationship model and an associated data chain based on all data ports, wherein the associated data chain includes a record library for each data port; The update unit is used to determine whether to generate an update instruction for the index relationship model based on a preset update time node; The processing unit includes: The first processing module is used to acquire input data from each data port; The first judgment module is used to determine the data type of the input data and set the processing strategy for the input data based on the judgment result.

10. The blockchain-based secure data sharing system as described in claim 9, characterized in that, The processing unit further includes: The second processing module is used to set a sequentially according to the data port sequence A. i For the target data port; Generate the correlation evaluation values ​​between the target data port and each data port; Establish a sequence of associated evaluation values ​​B, B=(b1,b2…b) for the target data port. i …b n ), where b i The evaluation value associated with the target data port and the i-th data port; n is the number of associated evaluation values; Preset a first correlation evaluation value threshold B1 and a second correlation evaluation value threshold B2; and B1 <B2; If B1≤b i <B2, setting the i-th data port as the first-level associated port of the target data port; If b i <B1, set the i-th data port as the secondary associated port of the target data port; Construct an index sub-model for the target data port based on all first-level associated ports and all second-level associated ports. Construct index sub-models for each data port in sequence; Construct an index association model based on all index sub-models.

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