Data right confirmation method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention discloses a data right confirmation method and device, equipment, a storage medium and a program product, and the data right confirmation method applied to a first platform comprises the steps that a first position index sent by a first node is received, and the first position index represents position indexes of j feature values corresponding to target data to be subjected to right confirmation, j is an integer greater than or equal to 1; under the condition that the first position index is not matched with the second position index, a first binary table of the second position index is updated to obtain a second binary table, and the second position index represents the position index of the characteristic value corresponding to the overall data of which the right is confirmed; and issuing a data asset registration certificate to the first node to complete right confirmation of the target data.

Description

Technical Field

[0001] The present application belongs to the field of public data, and in particular relates to a data rights confirmation method, device, equipment, storage medium and program product. Background Art

[0002] From data resources to data assets, the first challenge is how to define the ownership of data. In related technologies, the ownership of data resources can be confirmed by calculating the similarity between authorized data and unauthorized data, which can improve the accuracy of data resource confirmation to a certain extent. However, since a generative artificial intelligence model is needed to calculate the similarity between data, a large amount of sample data is needed to adjust the parameters of the artificial intelligence model, and more computing resources are consumed. Summary of the invention

[0003] In order to solve the problem of high implementation complexity and high consumption of computing resources in related technologies, the embodiments of the present application propose a data rights confirmation method, device, equipment, storage medium and program product.

[0004] The present application embodiment provides a data rights confirmation method, which is applied to a first platform, and the method includes:

[0005] Receive a first position index sent by the first node, where the first position index represents a position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1;

[0006] In the case where the first position index does not match the second position index, updating the first binary table of the second position index to obtain a second binary table, wherein the second position index represents the position index of the feature value corresponding to the overall data for which the right has been confirmed;

[0007] The ownership of the target data is confirmed by issuing a data asset registration certificate to the first node.

[0008] In some embodiments, after receiving the first location index sent by the first node, the method also includes: determining a first number of location indexes that do not match the second location index among the first location indexes; when a ratio of the first number to the j is greater than a first threshold, determining that the first location index does not match the second location index; when a ratio of the first number to the j is less than or equal to the first threshold, determining that the first location index matches the second location index.

[0009] In some embodiments, the method also includes: when the first position index matches the second position index, receiving the first public key and the first ciphertext sent by the first node, the first node is used to generate the first public key and the private key corresponding to the first public key, and using the first public key to encrypt the first eigenvector to generate the first ciphertext; the first eigenvector represents the eigenvector corresponding to each eigenvalue of the j eigenvalues; using the first public key to encrypt the second eigenvector corresponding to the first binary table to obtain the second ciphertext; the second eigenvector represents the eigenvector of the eigenvalue corresponding to each confirmed data; when the first ciphertext and the second ciphertext match, sending a rejection confirmation result to the first platform.

[0010] In some embodiments, after receiving the first public key and the first ciphertext sent by the first node, the method further includes: determining, among the eigenvalues ​​corresponding to the respective authenticated data, m eigenvalues ​​having the same position index as each eigenvalue in the j eigenvalues, where m is an integer greater than or equal to 1; and determining the eigenvector corresponding to the m eigenvalues ​​as the second eigenvector.

[0011] In some embodiments, the method further includes: when the first ciphertext and the second ciphertext do not match, updating the first binary table indexed by the second position to obtain a second binary table; and completing the confirmation of ownership of the target data by issuing a data asset registration certificate to the first node.

[0012] In some embodiments, the updating of the first binary table of the second position index to obtain the second binary table includes: updating the element of the target position in the position index of the characteristic value corresponding to the confirmed overall data from 0 to 1, wherein the element of the target position of the first binary table corresponding to at least one index of the position indexes of the j characteristic values ​​corresponding to the target data to be confirmed is 0.

[0013] In some embodiments, after obtaining the second ciphertext, the method further includes: determining a second number of ciphertexts that match the first ciphertext among each ciphertext of the second ciphertext; when a ratio of the second number to the m is less than a second threshold, determining that the first ciphertext does not match the second ciphertext; when a ratio of the second number to the m is greater than or equal to a second threshold, determining that the first ciphertext matches the second ciphertext.

[0014] In some embodiments, the confirmation of ownership of the target data is completed by issuing a data asset registration certificate to the first node, including: generating a data asset registration certificate by publicly announcing the first position index and the first feature vector on the blockchain; and confirming ownership of the target data based on the data asset registration certificate.

[0015] The embodiment of the present application also provides a data rights confirmation method, which is applied to a first node, and the method includes:

[0016] Sending a first position index of the target data to be confirmed to the first platform, where the first position index represents the position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1;

[0017] Receive the data asset registration certificate issued by the first platform, and complete the ownership confirmation of the target data based on the data asset registration certificate; the first platform is used to update the first binary table of the second position index to obtain the second binary table when the first position index does not match the second position index, and the second position index represents the position index of the characteristic value corresponding to the overall data that has been confirmed.

[0018] In some embodiments, the first platform is used to receive the first public key and the first ciphertext sent by the first node when the first location index matches the second location index, and use the first public key to encrypt the second feature vector corresponding to the first binary table to obtain the second ciphertext; when the first ciphertext and the second ciphertext do not match, update the first binary table of the second location index to obtain the second binary table, and issue a data asset registration certificate to the first node; wherein the first feature vector represents the feature vector corresponding to each of the j feature values, and the second feature vector represents the feature vector of the feature value corresponding to each confirmed data; the method also includes: after sending the first public key and the first ciphertext to the first node, receiving the data asset registration certificate issued by the first platform, and completing the confirmation of the target data based on the data asset registration certificate.

[0019] In some embodiments, before sending the first position index to the first platform, the method further includes: slicing the target data to obtain multiple slice data; determining each eigenvalue corresponding to each slice data in the multiple slice data, selecting k eigenvalues ​​from the respective eigenvalues, and a ratio of the sum of the k eigenvalues ​​to the sum of the respective eigenvalues ​​is greater than a third threshold; the j eigenvalues ​​corresponding to the target data include the k eigenvalues ​​corresponding to the respective slice data.

[0020] In some embodiments, after obtaining j feature values ​​and before sending the first location index to the first platform, the method further includes: receiving a preset hash function from the first platform, and determining the first location index based on the j feature values ​​corresponding to the target data and the hash function.

[0021] The present application also provides a data processing device, which is applied to a first platform, and the device includes:

[0022] A transceiver module, configured to receive a first position index sent by a first node, wherein the first position index represents a position index of j characteristic values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1;

[0023] A first processing module, configured to update a first binary table of the second position index to obtain a second binary table when the first position index does not match the second position index, wherein the second position index represents a position index of a feature value corresponding to the overall data for which the right has been confirmed;

[0024] The second processing module is used to complete the confirmation of the ownership of the target data by issuing a data asset registration certificate to the first node.

[0025] The embodiment of the present application also provides another data processing device, which is applied to a first node, and the device includes:

[0026] A third processing module is used to send a first position index of the target data to be confirmed to the first platform, where the first position index represents a position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1;

[0027] The fourth processing module is used to receive the data asset registration certificate issued by the first platform, and complete the confirmation of the target data based on the data asset registration certificate; the first platform is used to update the first binary table of the second position index to obtain the second binary table when the first position index does not match the second position index, and the second position index represents the position index of the characteristic value corresponding to the overall data that has been confirmed.

[0028] An embodiment of the present application also provides an electronic device, comprising a processor and a memory for storing a computer program that can be run on the processor; wherein the processor is used to run the computer program to execute any one of the above-mentioned data confirmation methods.

[0029] An embodiment of the present application also provides a computer storage medium on which a computer program is stored. When the computer program is executed by a processor, any one of the above-mentioned data ownership confirmation methods is implemented.

[0030] An embodiment of the present application also provides a computer program product, including a computer program, which implements any of the above-mentioned data rights confirmation methods when executed by a processor.

[0031] It can be seen that the embodiment of the present application realizes the confirmation of the ownership of the target data by judging whether the location index matches. When determining the location index, only the characteristic value needs to be used, and there is no need to use a large amount of sample data to realize the parameter adjustment of the artificial intelligence model, thereby reducing the computing resources consumed in data confirmation to a certain extent and reducing the amount of data required to obtain when confirming data. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of a data rights confirmation method applied to a first platform according to an embodiment of the present application;

[0033] Figure 2 This is a flow chart of a data rights confirmation method applied to a first node in an embodiment of the present application;

[0034] Figure 3 An interactive flow chart of the data rights confirmation method provided in the embodiment of the present application;

[0035] Figure 4 An interactive flow chart of the data authorization method provided in the embodiment of the present application;

[0036] Figure 5 This is a schematic diagram of the structure of a data rights confirmation device applied to a first platform according to an embodiment of the present application;

[0037] Figure 6 This is a structural diagram of a data rights confirmation device applied to a first node according to an embodiment of the present application;

[0038] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] At present, the construction of the data factor market is still in its infancy and still faces many challenges such as low data supply quality and poor data circulation mechanism. The mainstream view in the industry is that to promote the development of the data factor market, the first task is to achieve a complete closed loop of "resourceization, assetization, and capitalization" of data. From data resources to data assets, the first difficulty to be faced is how to define the ownership of data. The issue of data resource confirmation has not yet been properly resolved.

[0040] The first technical solution of the related technology proposes a privacy data rights confirmation method, system and computer-readable medium. In this solution, the data is desensitized and a watermark is implanted into the desensitized data, and the data assets are registered on the chain. At the same time, the watermark information is extracted to verify the source of the data; when the data needs to be tracked or traced, the watermark in the data is extracted to confirm the ownership and source of the data. The first technical solution of the related technology is more suitable for data rights confirmation of non-structured data such as videos and images.

[0041] The second technical solution of the related technology proposes a data authorization method and system for data element transactions; in this solution, the user's identity information is reviewed by a third-party CA agency based on the request; the third-party CA agency returns the issuance certificate CertA to the data right confirmation system and the data operator end, and the third-party CA agency issues the public key certificate CertB to the data operator end; the data operator end generates a mapping relationship table MapC based on the issuance certificate CertA and the public key certificate CertB; the user's authorizable data is authorized to the data operator end; and the data authorized by the user to the data operator end is obtained. The second technical solution of the related technology mainly authorizes the data after verifying the identity through the certificate of the third-party CA center, and does not involve the data information itself.

[0042] The third technical solution of the related art proposes a data governance platform and a data rights confirmation method for data governance; in this solution, a signal of a change in a data governance unit can be received; the data governance units in the data governance platform are processed in sequence to obtain and save the first column transformation feature matrix X, the first array B1 and the second column transformation feature matrix Y; according to the first column transformation feature matrix X, the first array B1 and the second column transformation feature matrix Y, the first target table data traceability information array D1 is obtained; the signal of a change in the right holder of the data source table is received, and the data governance units in the data governance platform are processed in sequence to obtain the second array B2; according to the first column transformation feature matrix X, the second array B2 and the second column transformation feature matrix Y, the second target table data traceability information array D2 is obtained. The third technical solution of the related art needs to use matrix transformation to confirm data rights, which is more complicated to calculate and has performance problems when processing large amounts of data.

[0043] The fourth technical solution of the related art proposes a blockchain-based on-chain text data rights confirmation method; in this solution, a character variable tree index data structure can be established, and then text fragment sampling and text fragment query can be performed; this solution adds a novel character variable tree index data structure to the traditional blockchain, and uses the smallest possible storage space to establish an index for the text content on the chain. Based on the index, fuzzy matching of text fragments is achieved, and the text content on the chain is further confirmed to ensure that plagiarized text with minor modifications can be quickly detected. The fourth technical solution of the related art is mainly a rights confirmation solution for text data, and cannot be applied to the rights confirmation of other types of data.

[0044] The fifth technical scheme of the related technology proposes a method for confirming the rights of data resources; in this scheme, the data to be confirmed, the confirmed data set and the similar data set can be obtained and the feature vector can be extracted in a preset manner, wherein the confirmed data set includes multiple confirmed data, and the similar data set includes multiple pairs of data, each pair of data includes the confirmed data and its corresponding similar data; obtain the similarity threshold, wherein the similarity threshold is obtained by using the feature vector of the data as the state, the similarity threshold as the action, and whether the similarity of the confirmed data and its corresponding similar data is greater than or equal to the similarity threshold as the value feedback calculation reward, and using the similar data set to train the reinforcement learning model until convergence; calculate the similarity between the feature vector of the data to be confirmed and the feature vector of each confirmed data, and confirm the rights based on the similarity threshold. By adopting the similarity threshold determined by the reinforcement learning method, the problem of accuracy of confirmation is solved. However, since a generative artificial intelligence model is needed to calculate the similarity between data, a large amount of sample data is needed to realize the parameter adjustment of the artificial intelligence model, which has high complexity and consumes more computing resources.

[0045] In order to solve the above technical problems, a technical solution of the embodiment of the present application is proposed.

[0046] The following is a further detailed description of the embodiments of the present application in conjunction with the accompanying drawings and examples. It should be understood that the embodiments provided herein are only used to explain the embodiments of the present application and are not intended to limit the embodiments of the present application. In addition, the embodiments provided below are partial embodiments for implementing the present application, rather than providing all embodiments for implementing the present application. In the absence of conflict, the technical solutions recorded in the embodiments of the present application can be implemented in any combination.

[0047] It should be noted that, in the embodiments of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a method or device including a series of elements includes not only the elements explicitly recorded, but also includes other elements not explicitly listed, or also includes elements inherent to the implementation of the method or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other related elements (such as steps in a method or units in a device, for example, a unit may be a part of a circuit, a part of a processor, a part of a program or software, etc.) in the method or device including the element.

[0048] The data rights confirmation method provided in the embodiment of the present application includes a series of steps, but the data rights confirmation method provided in the embodiment of the present application is not limited to the recorded steps. Similarly, the data rights confirmation device provided in the embodiment of the present application includes a series of modules, but the device provided in the embodiment of the present application is not limited to including the modules explicitly recorded, and may also include modules required to obtain relevant information or perform processing based on the information.

[0049] An embodiment of the present application proposes a data rights confirmation method applied to a first platform. Exemplarily, the first platform may be a data asset registration platform or other platform. The data asset registration platform may include a disclosure module for publicizing data, a confirmation module for data rights confirmation, and an authentication module for generating a data asset registration certificate.

[0050] Figure 1 Flow chart of the data rights confirmation method applied to the first platform in an embodiment of the present application. Figure 1 As shown, the process may include:

[0051] Step 101: Receive a first position index sent by a first node, where the first position index represents the position index of j feature values ​​corresponding to target data to be confirmed, where j is an integer greater than or equal to 1.

[0052] In some embodiments, the first node may be a node of a data provider. The node of a data provider is a locally installed node, and the node of a data provider is also called a privacy computing node, a trusted node, etc. Exemplarily, after extracting the target data to be confirmed from the database, the node of the data provider may generate j feature values ​​corresponding to the target data to be confirmed.

[0053] In some embodiments, the node of the data provider may slice the target data to be confirmed according to a fixed length or a fixed number of rows, and each slice may be compressed using a method such as singular value decomposition (SVD), and then each eigenvalue corresponding to each slice data and each eigenvector corresponding to each slice data may be obtained. K eigenvalues ​​are selected from each eigenvalue corresponding to each slice data, and the ratio of the sum of the k eigenvalues ​​to the sum of the eigenvalues ​​is greater than a third threshold.

[0054] Here, the j eigenvalues ​​corresponding to the target data include the k eigenvalues ​​corresponding to the respective slice data. The third threshold value may be set according to actual needs, for example, the third threshold value may be greater than 90%. Exemplarily, after obtaining the eigenvalues ​​corresponding to each slice data, the first k eigenvalues ​​may be selected from the eigenvalues ​​corresponding to each slice data.

[0055] Compared with the third technical solution of the related technology, the embodiment of the present application can slice the data before calculating the eigenvalues ​​and eigenvectors, thereby reducing the calculation complexity of the eigenvalues ​​and eigenvectors. In addition, after calculating the eigenvalues ​​corresponding to each slice data, only the first k eigenvalues ​​of the eigenvalues ​​corresponding to each slice data are retained, which is conducive to further reducing the subsequent calculation amount of eigenvalue operations, and the value of k can be calculated according to the formula instead of being determined according to experience.

[0056] In some embodiments, the first node can calculate the position index of the j eigenvalues ​​corresponding to the target data according to a preset hash function, and the number of preset hash functions is n, where n is an integer greater than 1. Exemplarily, the right confirmation module of the first platform can send the preset n hash functions to the first node, and the first node can bring each of the j eigenvalues ​​into the preset n hash functions to obtain a binary string, and the binary string corresponding to the above j eigenvalues ​​is the first position index. It can be seen that the position index of the j eigenvalues ​​corresponding to the target data can be calculated more accurately through the preset hash function.

[0057] Step 102: When the first position index does not match the second position index, the first binary table of the second position index is updated to obtain a second binary table, where the second position index represents the position index of the feature value corresponding to the overall data whose rights have been confirmed.

[0058] In an embodiment of the present application, after the ownership of each piece of data is confirmed, each piece of data can be inserted into the overall data for which the ownership has been confirmed, and then the characteristic value corresponding to the overall data for which the ownership has been confirmed can be calculated; illustratively, the characteristic value corresponding to the overall data for which the ownership has been confirmed can be substituted into the preset n hash functions to obtain the second position index.

[0059] In some embodiments, the first position index and the second position index can be represented according to a binary array. When the element in the second position index is 0, it means that there is no title confirmation data at the position represented by the element; when the element in the second position index is 1, it means that there is title confirmation data at the position represented by the element.

[0060] In some embodiments, when the first position index and the second position index do not match, the element of the target position in the position index of the characteristic value corresponding to the confirmed overall data can be updated from 0 to 1, wherein the element of the target position of the first binary table corresponding to at least one index of the position indexes of the j characteristic values ​​corresponding to the target data to be confirmed is 0.

[0061] Step 103: Complete the confirmation of ownership of the target data by issuing a data asset registration certificate to the first node.

[0062] In some embodiments, when the first position index does not match the second position index, the first platform generates a data asset registration certificate by publicly announcing the first position index and the first feature vector on the blockchain; and completes the confirmation of the target data according to the data asset registration certificate. Here, when the first position index and the second position index do not match, it can be considered that the target data has never appeared in the confirmed data. Therefore, the first position index and the first feature vector can be publicly announced on the blockchain after hashing, thereby reliably realizing the confirmation of the target data.

[0063] In practical applications, steps 101 to 104 can be implemented based on a processor, and the processor can be at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor.

[0064] It can be seen that the embodiment of the present application realizes the confirmation of the ownership of the target data by judging whether the location index matches. When determining the location index, only the characteristic value needs to be used, and there is no need to use a large amount of sample data to realize the parameter adjustment of the artificial intelligence model, thereby reducing the computing resources consumed in data confirmation to a certain extent and reducing the amount of data required to obtain when confirming data.

[0065] In some embodiments of the present application, after receiving the first location index sent by the first node, the method further includes: determining a first number of location indexes that do not match the second location index among the first location indexes; determining that the first location index does not match the second location index when a ratio of the first number to j is greater than a first threshold; and determining that the first location index matches the second location index when a ratio of the first number to j is less than or equal to a first threshold.

[0066] Here, the title confirmation module of the first platform can extract the second position index, and then match the second position index with the position indexes of the j eigenvalues ​​corresponding to the target data to be confirmed. The position where the element is 1 in the position index of any eigenvalue corresponding to the target data to be confirmed is recorded as a specific position. If all the elements of the specific positions in the second position index are 1, it means that the position index of the first eigenvalue matches the second position index. Otherwise, it means that the position index of the corresponding eigenvalue in the first position index does not match the second position index.

[0067] After determining the first quantity, the ratio of the first quantity to j can be calculated, and the relationship between the ratio and the first threshold can be determined. Exemplarily, the first threshold can be set according to actual needs. For example, the value range of the first threshold is between 50% and 98%.

[0068] In an example, the second position index can be represented by a binary array of length 6. For example, the second position index is [0,0,1,0,1,1]. There are 3 preset hash functions, j=3. The 3 eigenvalues ​​corresponding to the target data to be confirmed are 7, 8 and 9 respectively. After performing a hash operation on the eigenvalues ​​according to the hash function, the position indexes corresponding to the above 3 eigenvalues ​​can be obtained; for example, the position index corresponding to 7 is [0,1,1,0,0,1], the position index corresponding to 8 is [0,1,1,0,1,0], and the position index corresponding to 9 is [1,1,1,0,0,0]; it can be seen It can be seen that the element at the second position in the position index of 7 is 1, and the element at the second position in the second position index is 0, which means that the position index corresponding to 7 does not appear in the binary array, that is, the position index corresponding to 7 does not match the second position index. Similarly, the position index corresponding to 8 and the position index corresponding to 9 do not match the second position index. The first number is 3 / 3=1; the first threshold can be recorded as u. When the value of u is 50%, since 1 is greater than 50%, it can be considered that the first position index does not match the second position index, that is, the characteristic value of the target data to be confirmed has never appeared in the confirmation module.

[0069] It can be seen that the embodiment of the present application can determine the first number of position indexes that do not match the second position index among the various position indexes of the first position index, and determine the ratio of the first number to j. Based on the relationship between the ratio and the first threshold, it can be more accurately determined whether the first position index matches the second position index.

[0070] In some embodiments of the present application, when the first position index matches the second position index, the first platform can receive the first public key and the first ciphertext sent by the first node; use the first public key to encrypt the second feature vector corresponding to the first binary table to obtain the second ciphertext; the second feature vector represents the feature vector of the feature value corresponding to each confirmed data; when the first ciphertext and the second ciphertext match, send a rejection confirmation result to the first platform.

[0071] Here, the first node is used to generate a first public key and a private key corresponding to the first public key, and use the first public key to encrypt the first eigenvector to generate the first ciphertext; the first eigenvector represents the eigenvector corresponding to each eigenvalue in the j eigenvalues.

[0072] It can be seen that when the first ciphertext and the second ciphertext match, it can be considered that the target data has appeared in the confirmed data. At this time, by sending a rejection confirmation result to the first node, the situation of duplicate data confirmation can be avoided to a certain extent.

[0073] In some embodiments of the present application, after receiving the first public key and the first ciphertext sent by the first node, the first platform can also determine, among the eigenvalues ​​corresponding to each authenticated data, m eigenvalues ​​having the same position index as each eigenvalue in the j eigenvalues, and determine the eigenvectors corresponding to the m eigenvalues ​​as the second eigenvector; m is an integer greater than or equal to 1.

[0074] In some embodiments of the present application, the first platform can also update the first binary table indexed by the second position to obtain the second binary table when the first ciphertext and the second ciphertext do not match; then, the ownership of the target data is confirmed by issuing a data asset registration certificate to the first node.

[0075] In some embodiments, when the first ciphertext and the second ciphertext do not match, the first platform can generate a data asset registration certificate by publicly announcing the first position index and the first feature vector on the blockchain; and complete the confirmation of ownership of the target data based on the data asset registration certificate.

[0076] Here, when the first ciphertext and the second ciphertext do not match, it can be considered that the target data has never appeared in the confirmed data. Therefore, the first position index and the first feature vector can be publicly posted on the blockchain after a hash operation, thereby reliably realizing the confirmation of the target data.

[0077] In some embodiments, in the case where the first ciphertext and the second ciphertext do not match, the element at the target position in the position index of the eigenvalue corresponding to the overall data that has been confirmed can be updated from 0 to 1, where at least one of the elements at the target positions in the position index of the j eigenvalues corresponding to the target data to be confirmed is 0 in the first binary table.

[0078] In some embodiments of the present application, after the first platform obtains the second ciphertext, it can also determine the second quantity of the ciphertexts that match the first ciphertext among the respective ciphertexts of the second ciphertext; in the case where the ratio of the second quantity to m is less than the second threshold, it is determined that the first ciphertext does not match the second ciphertext; in the case where the ratio of the second quantity to m is greater than or equal to the second threshold, it is determined that the first ciphertext matches the second ciphertext.

[0079] Here, after determining the second quantity, the ratio of the second quantity to m can be calculated, and the magnitude relationship between this ratio and the second threshold can be judged. Exemplarily, the second threshold can be set according to actual requirements. For example, the value range of the second threshold is between 50% and 90%.

[0080] In one example, the encryption result of the eigenvector corresponding to any eigenvalue in the first ciphertext is S1, S1 is CSFSDFSHDIFSDFSDF, the position index of the eigenvalue corresponding to S1 is [0,0,0,1,1,1], the second threshold is denoted as U2, and U2 = 50%. The position index of the eigenvalue corresponding to the overall data that has been confirmed is the binary array [0,0,1,0,1,1]. There are 3 eigenvectors corresponding to the position index [0,0,0,1,1,1] in the overall data that has been confirmed, and these 3 eigenvectors are denoted as V1, V2, and V3 respectively; after encrypting V1, V2, and V3 respectively using the first target public key, the following three ciphertexts can be obtained:

[0081] Sdhfsidhfsd, ryqweyriwryw, CSFSDFSHDIFSDFSDF.

[0082] It can be seen that among the ciphertexts corresponding to V1, V2, and V3 respectively, the number of ciphertexts that are exactly the same as S1 is 1, so the ratio of the second quantity to m is 1 / 3. Since 1 / 3 < U2 = 50%, it can be determined that the first ciphertext does not match the second ciphertext.

[0083] The embodiments of the present application can determine the second quantity of the ciphertexts that do not match the first ciphertext among the respective ciphertexts of the second ciphertext, and determine the ratio of the second quantity to m. According to the magnitude relationship between this ratio and the second threshold, it can be more accurately judged whether the first ciphertext matches the second ciphertext.

[0084] In some embodiments of the present application, the first platform may also receive information about the target developer sent by the first node, and the first node may select the target developer from the L data developers sent by the first platform; the target developer is used to generate a second public key and a private key corresponding to the second public key, and send the second public key to the first platform. The first platform sends the second public key to the first node, and the first node may use the second public key to encrypt the access information of the data development module to obtain a third ciphertext, and send the third ciphertext to the first platform; here, the third ciphertext is used for the target developer to decrypt using the private key.

[0085] Here, the access information of the data development module may include at least one of the following information: access address, account, and initial password.

[0086] It can be seen that the first platform can obtain the second public key by interacting with the target developer selected by the first node, and thus can send the second public key to the first node, so that the first node can send the encrypted third ciphertext to the first platform. Since the third ciphertext is the encryption result obtained by encrypting the access information of the data development module using the second public key, the embodiment of the present application can realize the encrypted transmission of the access information of the data development module, which is conducive to improving the confidentiality of data authorization when realizing data development.

[0087] Figure 2 Flow chart of the data rights confirmation method applied to the first node in an embodiment of the present application. Figure 2 As shown, the process may include:

[0088] Step 201: Send the first location index of the target data to be confirmed to the first platform.

[0089] Step 202: Receive the data asset registration certificate issued by the first platform, and complete the ownership confirmation of the target data based on the data asset registration certificate.

[0090] Among them, the first platform is used to update the first binary table of the second position index to obtain the second binary table when the first position index does not match the second position index, and the second position index represents the position index of the characteristic value corresponding to the overall data that has been confirmed.

[0091] In practical applications, steps 201 to 202 may be implemented based on a processor, and the processor may be at least one of ASIC, DSP, DSPD, PLD, FPGA, CPU, controller, microcontroller, and microprocessor.

[0092] It can be seen that the embodiment of the present application realizes the confirmation of the ownership of the target data by judging whether the location index matches. When determining the location index, only the characteristic value needs to be used, and there is no need to use a large amount of sample data to realize the parameter adjustment of the artificial intelligence model, thereby reducing the computing resources consumed in data confirmation to a certain extent and reducing the amount of data required to obtain when confirming data.

[0093] In some embodiments, before sending the first position index to the first node, the second node may also slice the target data to obtain multiple slice data; determine each eigenvalue corresponding to each slice data in the multiple slice data, and select k eigenvalues ​​from each eigenvalue, and the ratio of the sum of the k eigenvalues ​​to the sum of the eigenvalues ​​is greater than a third threshold.

[0094] Figure 3 The interactive flow chart of the data rights confirmation method provided in the embodiment of the present application is as follows: Figure 3 As shown, the process includes:

[0095] Step a1: The first node obtains the eigenvalue corresponding to the target data.

[0096] The implementation method of this step has been explained in the above-mentioned content.

[0097] Step a2: The first node initiates a title confirmation request to the title confirmation module.

[0098] Step a3: The rights confirmation module sends the preset hash function to the first node.

[0099] Here, the right confirmation module may also send the encryption function to the first node.

[0100] Step a4: The first node calculates a first position index.

[0101] Step a5: The first node sends the first location index to the right confirmation module.

[0102] Step a6: The right confirmation module determines whether the first position index matches the second position index. If yes, execute steps a7 to a7.5; if no, execute step a8.

[0103] Step a7: The rights confirmation module sends the first matching result to the first node.

[0104] Step a7.1: The first node generates a first public key and a first ciphertext.

[0105] Step a7.2: The first node sends the first public key and the first ciphertext to the authentication module.

[0106] Step a7.3: The authentication module determines whether the first ciphertext matches the second ciphertext. If yes, execute step a7.4; if no, execute step a7.5.

[0107] Step a7.4: The right confirmation module sends a confirmation rejection result to the first node.

[0108] Step a7.5: The rights confirmation module sends a request to the first node to upload the information to the blockchain.

[0109] Here, the right confirmation module may also update the elements in the second position index.

[0110] Step a8: The rights confirmation module sends a request to the first node to go online.

[0111] Here, the right confirmation module may also update the elements in the second position index.

[0112] Step a9: The first node generates uplink information R1.

[0113] Here, the first node may add the corresponding feature vector to the first position index, and then encrypt the data after adding the feature vector using a hash encryption method such as md5 to obtain the on-chain information R1.

[0114] Step a10: The first node sends R1 to the blockchain.

[0115] Here, the first node sends R1 to the blockchain through the interface.

[0116] Step a11: The blockchain generates an on-chain certificate.

[0117] Here, the blockchain reviews the integrity of the information on the chain and generates a chain certificate after the review is passed.

[0118] Step a12: The blockchain sends the on-chain certificate to the title confirmation module and the first node.

[0119] Step a13: The rights confirmation module sends the metadata to the public disclosure module.

[0120] Here, the metadata may be metadata of the target data, for example, the metadata may include a first position index and a first feature vector.

[0121] Step a14: The public module publicizes the metadata

[0122] Here, the publicizing module publicizes the metadata at a specified time.

[0123] Step a15: After the publicity is completed, the publicity module sends the publicity results to the title confirmation module.

[0124] Step a16: When the rights confirmation module determines that there is no objection within the specified time, it sends a data resource rights confirmation request to the authentication module, and then executes steps a17 to a19; when it is determined that there is an objection within the specified time, executes step a20.

[0125] Here, the title confirmation module can determine whether there are any objections within the specified time based on the publicity results.

[0126] Step a17: The authentication module generates a data asset registration certificate.

[0127] Step a18: The authentication module sends the data asset registration certificate to the rights confirmation module.

[0128] Step a19: The rights confirmation module synchronizes the data asset registration certificate to the first node.

[0129] Step a20: the right confirmation module sends a confirmation rejection result to the first node.

[0130] In some embodiments, the data asset registration platform may include an operation module and a resource module. Figure 4 The interactive flow chart of the data authorization method provided in the embodiment of the present application is as follows: Figure 4 As shown, the process includes:

[0131] Step b1: The first node initiates a listing request to the resource module.

[0132] Exemplarily, the listing request may include basic information such as the data resource name, data item, and data application scenario, and may also include supporting materials such as a data asset registration certificate, and may also include a filled-in development requirement template. For example, the development requirement template may include data application scenarios, development levels, development methods, development performance, development resources, developer qualification requirements, etc. The development level may be high, medium, or low, and the development method may be federated learning, anonymous query, API, data sandbox, data space, etc.

[0133] Step b2: The resource module reviews the information.

[0134] Here, the resource module reviews basic resource information, supporting materials, integrity and other information.

[0135] Step b3: The resource module synchronizes the development requirement template to the operation module.

[0136] Here, the resource module can synchronize the development requirement template to the operation module after passing the review.

[0137] Step b4: The operation module updates the development requirement template.

[0138] Here, the operation module can update the development requirement template in the development requirement template library.

[0139] Step b5: The operation module synchronizes the blank development template to the data developer.

[0140] Here, the blank development template is a template that the data developer needs to fill in; illustratively, the blank development template may include information such as data application scenarios, supported development levels, supported development methods, supported development product performance, supported development resources, and developer qualifications. The supported development level may be high, medium, or low, and the supported development methods may be federated learning, anonymous query, API, data sandbox, data space, etc.

[0141] Step b6: The data developer returns the completed template to the operation module.

[0142] Step b7: The operation module determines L data developers.

[0143] Here, the operation module can calculate the string similarity between the completed templates returned by each data opening and the development requirement template, and determine the data developers corresponding to the L highest similarities.

[0144] Step b8: The operation module sends the information of L data developers to the first node.

[0145] Step b9: The first node selects a target developer.

[0146] Here, the first node can review the qualifications and capabilities of the first L open parties and select the target developer based on the review results.

[0147] Step b10: The first node returns the target developer's information to the operation module.

[0148] Step b11: the operation module sends the selected result to the target developer, and the target developer sends the second public key to the operation module.

[0149] Here, the operation module may generate a second public key and a private key corresponding to the second public key.

[0150] Step b12: The operation module synchronizes the second public key to the first node.

[0151] Step b13: The first node generates a third ciphertext.

[0152] Step b14: The first node sends the third ciphertext to the operation module.

[0153] Step b15: The target developer obtains the third ciphertext in the operation module and decrypts it using the private key.

[0154] Step b16: The target developer performs data development.

[0155] Here, the target developer can log in to the development module of the data provider and develop data products according to the authorized content.

[0156] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0157] Figure 5 Schematic diagram of the structure of the data rights confirmation device applied to the first platform in the embodiment of the present application. Figure 5 As shown, the device comprises:

[0158] The transceiver module 501 is configured to receive a first position index sent by a first node, where the first position index represents a position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1;

[0159] A first processing module 502 is configured to update a first binary table of the second position index to obtain a second binary table when the first position index does not match the second position index, wherein the second position index represents a position index of a feature value corresponding to the overall data for which the right has been confirmed;

[0160] The second processing module 503 is used to complete the confirmation of the ownership of the target data by issuing a data asset registration certificate to the first node.

[0161] In some embodiments, the transceiver module 501 is also used to determine, among the various position indexes of the first position index, a first number of position indexes that do not match the second position index after receiving the first position index sent by the first node; when the ratio of the first number to the j is greater than a first threshold, determine that the first position index does not match the second position index; when the ratio of the first number to the j is less than or equal to the first threshold, determine that the first position index matches the second position index.

[0162] In some embodiments, the first processing module 502 is further configured to receive a first public key and a first ciphertext sent by the first node when the first position index matches the second position index, the first node is configured to generate the first public key and a private key corresponding to the first public key, and encrypt the first eigenvector using the first public key to generate the first ciphertext; the first eigenvector represents the eigenvector corresponding to each eigenvalue of the j eigenvalues;

[0163] Using the first public key, encrypt the second feature vector corresponding to the first binary table to obtain a second ciphertext; the second feature vector represents a feature vector of the feature value corresponding to each authenticated data;

[0164] In the case where the first ciphertext and the second ciphertext match, a result of rejecting confirmation is sent to the first platform.

[0165] In some embodiments, the first processing module 502 is further used to, after receiving the first public key and the first ciphertext sent by the first node, determine, among the eigenvalues ​​corresponding to the respective authenticated data, m eigenvalues ​​having the same position index as each eigenvalue in the j eigenvalues, and determine the eigenvectors corresponding to the m eigenvalues ​​as the second eigenvector, where m is an integer greater than or equal to 1.

[0166] In some embodiments, the first processing module 502 is further used to update the first binary table of the second position index to obtain the second binary table when the first ciphertext and the second ciphertext do not match; and complete the confirmation of the ownership of the target data by issuing a data asset registration certificate to the first node.

[0167] In some embodiments, the first processing module 502 is used to update the first binary table of the second position index to obtain the second binary table, including: updating the element of the target position in the position index of the characteristic value corresponding to the confirmed overall data from 0 to 1, wherein the element of the target position of the first binary table corresponding to at least one index of the position indexes of the j characteristic values ​​corresponding to the target data to be confirmed is 0.

[0168] In some embodiments, the first processing module 502 is further used to determine, after obtaining the second ciphertext, a second number of ciphertexts that match the first ciphertext among the respective ciphertexts of the second ciphertext; when a ratio of the second number to the m is less than a second threshold, determine that the first ciphertext does not match the second ciphertext; when a ratio of the second number to the m is greater than or equal to a second threshold, determine that the first ciphertext matches the second ciphertext.

[0169] In some embodiments, the second processing module 503 is used to complete the ownership confirmation of the target data by issuing a data asset registration certificate to the first node, including: generating a data asset registration certificate by publicly announcing the first position index and the first feature vector on the blockchain; and completing the ownership confirmation of the target data according to the data asset registration certificate.

[0170] In practical applications, the transceiver module 501, the first processing module 502 and the second processing module 503 can be implemented based on a processor and a communication device.

[0171] Figure 6 Schematic diagram of the structure of the data rights confirmation device applied to the first platform in the embodiment of the present application. Figure 6 As shown, the device comprises:

[0172] The third processing module 601 is used to send the first position index of the target data to be confirmed to the first platform, where the first position index represents the position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1;

[0173] The fourth processing module 602 is used to receive the data asset registration certificate issued by the first platform, and complete the confirmation of the target data based on the data asset registration certificate; the first platform is used to update the first binary table of the second position index to obtain the second binary table when the first position index does not match the second position index, and the second position index represents the position index of the characteristic value corresponding to the overall data that has been confirmed.

[0174] In some embodiments, the first platform is used to receive the first public key and the first ciphertext sent by the first node when the first location index matches the second location index, encrypt the second feature vector corresponding to the first binary table using the first public key to obtain the second ciphertext, and update the first binary table of the second location index to obtain the second binary table when the first ciphertext does not match the second ciphertext, and issue a data asset registration certificate to the first node; wherein the first feature vector represents the feature vector corresponding to each feature value of the j feature values, and the second feature vector represents the feature vector of the feature value corresponding to each confirmed data;

[0175] The fourth processing module 602 is further used to receive a data asset registration certificate issued by the first platform after sending the first public key and the first ciphertext to the first platform, and complete the ownership confirmation of the target data based on the data asset registration certificate.

[0176] In some embodiments, the third processing module 601 is further used to slice the target data to obtain multiple slice data before sending the first position index to the first platform; determine each eigenvalue corresponding to each slice data in the multiple slice data, select k eigenvalues ​​from the each eigenvalue, and the ratio of the sum of the k eigenvalues ​​to the sum of the each eigenvalue is greater than a third threshold; the j eigenvalues ​​corresponding to the target data include the k eigenvalues ​​corresponding to the each slice data.

[0177] In some embodiments, the third processing module 601 is also used to receive a preset hash function from the first platform after obtaining j feature values ​​and before sending the first location index to the first platform, and determine the first location index based on the j feature values ​​corresponding to the target data and the hash function.

[0178] In practical applications, the third processing module 603 and the fourth processing module 604 can be implemented based on a processor and a communication device.

[0179] It should be noted that the description of the above device embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the device embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0180] It should be noted that in the embodiments of the present application, if the above method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a computer device (which can be a terminal, a server, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a disk or an optical disk. In this way, the embodiments of the present application are not limited to any specific combination of hardware and software.

[0181] Correspondingly, an embodiment of the present application further provides a computer program product, which includes computer executable instructions, and the computer executable instructions are used to implement any data rights confirmation method provided in the embodiment of the present application.

[0182] Correspondingly, an embodiment of the present application further provides a computer storage medium, on which computer executable instructions are stored, and the computer executable instructions are used to implement any one of the data rights confirmation methods provided in the above embodiments.

[0183] An embodiment of the present application also provides an electronic device. Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 7 As shown, the electronic device 70 may include:

[0184] Memory 701, used to store executable instructions;

[0185] The processor 702 is used to implement any of the above-mentioned data rights confirmation methods when executing the execution instructions stored in the memory 701.

[0186] The processor 702 may be at least one of an ASIC, a DSP, a DSPD, a PLD, a FPGA, a CPU, a controller, a microcontroller, and a microprocessor.

[0187] The above-mentioned computer-readable storage medium and memory 702 can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory (Flash Memory), a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM) and other memories; it can also be various terminals including one or any combination of the above-mentioned memories, such as a mobile phone, a computer, a tablet device, a personal digital assistant, etc.

[0188] In some embodiments, the functions or modules included in the device provided in the embodiments of the present application can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments. For the sake of brevity, it will not be repeated here.

[0189] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0190] The methods disclosed in the various method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0191] The features disclosed in the various product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0192] The features disclosed in the various method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0193] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0194] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A data rights confirmation method, characterized in that: Applied to the first platform, the method comprises: Receive a first position index sent by the first node, where the first position index represents a position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1; In the case where the first position index does not match the second position index, updating the first binary table of the second position index to obtain a second binary table, wherein the second position index represents the position index of the feature value corresponding to the overall data for which the right has been confirmed; The ownership of the target data is confirmed by issuing a data asset registration certificate to the first node.

2. The method according to claim 1, characterized in that After receiving the first location index sent by the first node, the method further includes: Determining, among each of the first position indexes, a first number of position indexes that do not match the second position index; When the ratio of the first number to the j is greater than a first threshold, it is determined that the first position index does not match the second position index; when the ratio of the first number to the j is less than or equal to the first threshold, it is determined that the first position index matches the second position index.

3. The method according to claim 1, characterized in that The method further comprises: In the case where the first position index matches the second position index, receiving a first public key and a first ciphertext sent by the first node, the first node is used to generate the first public key and a private key corresponding to the first public key, and encrypt a first eigenvector using the first public key to generate the first ciphertext; the first eigenvector represents an eigenvector corresponding to each eigenvalue of the j eigenvalues; Using the first public key, encrypt the second feature vector corresponding to the first binary table to obtain a second ciphertext; the second feature vector represents a feature vector of the feature value corresponding to each authenticated data; In the case where the first ciphertext and the second ciphertext match, a result of rejecting confirmation is sent to the first platform.

4. The method according to claim 3, characterized in that: After receiving the first public key and the first ciphertext sent by the first node, the method further includes: Among the eigenvalues ​​corresponding to the respective authenticated data, m eigenvalues ​​having the same position index as each of the j eigenvalues ​​are determined, where m is an integer greater than or equal to 1; The eigenvectors corresponding to the m eigenvalues ​​are determined as the second eigenvectors.

5. The method according to claim 3, characterized in that The method further comprises: In the case where the first ciphertext and the second ciphertext do not match, updating the first binary table indexed by the second position to obtain a second binary table; The ownership of the target data is confirmed by issuing a data asset registration certificate to the first node.

6. The method according to claim 1 or 5, characterized in that: The updating of the first binary table of the second position index to obtain the second binary table includes: updating the element of the target position in the position index of the characteristic value corresponding to the overall data that has been confirmed from 0 to 1, wherein the element of the target position of the first binary table corresponding to at least one index of the position indexes of the j characteristic values ​​corresponding to the target data to be confirmed is 0.

7. The method according to claim 4, characterized in that After obtaining the second ciphertext, the method further includes: determining a second number of ciphertexts matching the first ciphertext among the ciphertexts of the second ciphertext; When the ratio of the second number to the m is less than a second threshold, it is determined that the first ciphertext does not match the second ciphertext; when the ratio of the second number to the m is greater than or equal to the second threshold, it is determined that the first ciphertext matches the second ciphertext.

8. The method according to claim 1 or 5, characterized in that: The method of completing the confirmation of ownership of the target data by issuing a data asset registration certificate to the first node includes: generating a data asset registration certificate by publicly announcing the first position index and the first feature vector on the blockchain; and completing the confirmation of ownership of the target data according to the data asset registration certificate.

9. A data rights confirmation method, characterized in that: Applied to the first node, the method comprises: Sending a first position index of the target data to be confirmed to the first platform, where the first position index represents the position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1; Receive the data asset registration certificate issued by the first platform, and complete the ownership confirmation of the target data based on the data asset registration certificate; the first platform is used to update the first binary table of the second position index to obtain the second binary table when the first position index does not match the second position index, and the second position index represents the position index of the characteristic value corresponding to the overall data that has been confirmed.

10. The method according to claim 9, characterized in that The first platform is used to receive the first public key and the first ciphertext sent by the first node when the first position index matches the second position index, encrypt the second feature vector corresponding to the first binary table using the first public key to obtain the second ciphertext, and update the first binary table of the second position index to obtain the second binary table when the first ciphertext does not match the second ciphertext, and issue a data asset registration certificate to the first node; wherein the first feature vector represents the feature vector corresponding to each feature value of the j feature values, and the second feature vector represents the feature vector of the feature value corresponding to each confirmed data; The method further includes: after sending the first public key and the first ciphertext to the first platform, receiving a data asset registration certificate issued by the first platform, and completing the confirmation of ownership of the target data based on the data asset registration certificate.

11. The method according to claim 9, characterized in that Before sending the first location index to the first platform, the method further includes: Slicing the target data to obtain a plurality of slice data; determining each eigenvalue corresponding to each slice data in the plurality of slice data, selecting k eigenvalues ​​from the eigenvalues, and a ratio of a sum of the k eigenvalues ​​to a sum of the eigenvalues ​​being greater than a third threshold; The j eigenvalues ​​corresponding to the target data include the k eigenvalues ​​corresponding to the respective slice data.

12. The method according to claim 9 or 11, characterized in that: After obtaining j feature values ​​and before sending the first location index to the first platform, the method further includes: A preset hash function is received from the first platform, and the first location index is determined based on the j feature values ​​corresponding to the target data and the hash function.

13. A data rights confirmation device, characterized in that: Applied to the first platform, the device comprises: A transceiver module, configured to receive a first position index sent by a first node, wherein the first position index represents a position index of j characteristic values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1; A first processing module, configured to update a first binary table of the second position index to obtain a second binary table when the first position index does not match the second position index, wherein the second position index represents a position index of a feature value corresponding to the overall data for which the right has been confirmed; The second processing module is used to complete the confirmation of the ownership of the target data by issuing a data asset registration certificate to the first node.

14. A data rights confirmation device, characterized in that: Applied to a first node, the device comprises: A third processing module is used to send a first position index of the target data to be confirmed to the first platform, where the first position index represents a position index of j feature values ​​corresponding to the target data to be confirmed, where j is an integer greater than or equal to 1; The fourth processing module is used to receive the data asset registration certificate issued by the first platform, and complete the confirmation of the target data based on the data asset registration certificate; the first platform is used to update the first binary table of the second position index to obtain the second binary table when the first position index does not match the second position index, and the second position index represents the position index of the characteristic value corresponding to the overall data that has been confirmed.

15. An electronic device, characterized in that: The electronic device comprises a processor and a memory for storing a computer program that can be run on the processor; wherein, The processor is configured to run the computer program to perform the method according to any one of claims 1 to 12.

16. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 12 is implemented.

17. A computer program product comprising a computer program, characterized in that The computer program implements the method according to any one of claims 1 to 12 when executed by a processor.

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