Artificial intelligence sample data tracing method and device based on block chain

Abstract

The invention discloses an artificial intelligence sample data tracing method and device based on a block chain, and relates to the technical field of block chains, and the method comprises the steps: generating a sample data object based on artificial intelligence sample data, and then generating a sample data fingerprint, adding the sample data fingerprint and the sample data object to a block chain account book and generating a first evidence storage number; determining sample traceability key nodes corresponding to the full life cycle of the artificial intelligence sample data and determining priorities; according to the sample data fingerprint, the first evidence number, the key link, the circulation sequence and the priority, generating a data object corresponding to the sample traceability key node, adding the data object to a block chain account book according to a time sequence, and generating a second evidence number; and when an artificial intelligence sample data traceability request is received, obtaining the evidence storage number, and carrying out on-chain evidence collection based on the evidence storage number, the first evidence storage number and the second evidence storage number to obtain evidence collection content data. And the data quality, the data traceability efficiency, the data traceability accuracy and the data security are improved.

Description

Technical Field

[0001] The present application relates to the field of blockchain technology, and in particular to a blockchain-based artificial intelligence sample data tracing method, device, electronic device and computer-readable medium. Background Art

[0002] In recent years, relying on the improvement of big data and computing power, large model technology in the field of AI has achieved rapid development. The training of large models requires a large amount of sample data, and the quality and security of sample data have become important factors restricting the development of large models. Since data needs to flow in practical applications, there will be multiple data transmissions and interactions between multi-level sample data. Insufficient transparency in the flow of sample data will lead to a lack of guarantee of data quality. The flow path of sample data from collection to participation in model training is long. Once the sample data is polluted and biased during the flow process, it may lead to wrong decision-making of the artificial intelligence model. Insufficient compliance control of sample data will lead to a lack of guarantee of data security. When sample data participates in model training across levels and departments, if integrity, confidentiality and privacy protection are not performed, it may lead to privacy leakage and other problems. Summary of the invention

[0003] In view of this, the embodiments of the present application provide an artificial intelligence sample data traceability method, device, electronic device and computer-readable medium based on blockchain, which can solve the existing technical problems in practical applications, such as multiple data transmission and interaction of sample data, insufficient transparency of sample data flow, low data traceability efficiency and poor accuracy, resulting in poor sample data quality and lack of data security.

[0004] To achieve the above purpose, according to one aspect of the embodiments of the present application, a blockchain-based artificial intelligence sample data tracing method is provided, comprising: When the generated artificial intelligence sample data is detected, generating a sample data object based on the artificial intelligence sample data; Encrypt the sample data object using a hash encryption algorithm to generate a sample data fingerprint, add the sample data fingerprint and the sample data object to the blockchain account book, and generate a first evidence storage number; Determine the key nodes of sample traceability corresponding to the entire life cycle of AI sample data, and determine the priority of the key nodes of sample traceability according to the flow order of the key links corresponding to the entire life cycle; Generate data objects corresponding to key nodes of sample traceability based on sample data fingerprint, first evidence number, key links, circulation order and priority, add data objects to blockchain ledger in time sequence and generate second evidence numbers, and return corresponding second evidence numbers to key nodes of sample traceability; When a request for tracing the artificial intelligence sample data is received, the corresponding evidence number is obtained, and on-chain evidence is collected based on the evidence number, the first evidence number, and the second evidence number to obtain the evidence content data, and the evidence content data is returned to the user.

[0005] Optionally, based on the artificial intelligence sample data, a sample data object is generated, including: Extract metadata information of artificial intelligence sample data, and generate metadata objects based on the metadata information; Generate sample data objects based on metadata objects and artificial intelligence sample data.

[0006] Optionally, adding the sample data fingerprint and the sample data object to the blockchain ledger includes: Generate a data block according to the sample data fingerprint and the sample data object; The data block is verified for integrity based on the blockchain smart contract, and in response to passing the integrity verification, the data block is added to the blockchain ledger.

[0007] Optionally, return forensic content data to the user, including: Based on the forensic content data, a third data object is generated, and the third data object is returned to the user.

[0008] Optionally, the key links include an upload link and a distribution link, the flow order is upload first and then distribution, the key nodes of sample traceability include a collection terminal-level sample library, a business-level sample library and a headquarters-level sample library, and the priority includes the priority in the upload link and the priority in the distribution link, wherein the priority in the upload link is that the priority of the collection terminal-level sample library is greater than the priority of the business-level sample library, which is greater than the priority of the headquarters-level sample library, and the priority in the distribution link is that the priority of the headquarters-level sample library is greater than the priority of the business-level sample library; and According to the sample data fingerprint, the first evidence number, key links, circulation order and priority, generate each data object corresponding to the key node of sample traceability, add each data object to the blockchain account book according to the time sequence and generate each second evidence number, including: In response to the completion of adding the sample data fingerprint and the sample data object to the blockchain account book by the acquisition terminal-level sample library, a corresponding data object B is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the first evidence number, the acquisition terminal-level sample library, the business-level sample library, the upload link and the current time, and the data object B is added to the blockchain account book through the business-level sample library and a corresponding second evidence number No2 is generated; In response to the business-level sample library completing the addition of data object B to the blockchain ledger, a corresponding data object B' is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No2, the business-level sample library, the headquarters-level sample library, the upload link and the current time, and the data object B' is added to the blockchain ledger through the headquarters-level sample library and a corresponding second evidence number No3 is generated; In response to the headquarters-level sample library completing the addition of data object B' to the blockchain ledger, the corresponding data object B'' is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No3, the headquarters-level sample library, the business-level sample library, the distribution link and the current time. The data object B'' is added to the blockchain ledger through the business-level sample library and the corresponding second evidence number No4 is generated.

[0009] Optionally, performing on-chain evidence collection based on the evidence number, the first evidence number, and the second evidence number to obtain evidence content data includes: The evidence number is matched with the first evidence number and each second evidence number, and the corresponding evidence content data is queried in the blockchain ledger based on the matched first evidence number or second evidence number. If the queried evidence content data also contains the evidence number, the corresponding evidence content data is continued to be queried based on the contained evidence number until the queried evidence content data no longer contains the evidence number, and all the queried evidence content data are summarized in time series to obtain the evidence content data.

[0010] Optionally, the method further comprises: When data flows at each key sample traceability node and each key link in the entire life cycle of artificial intelligence sample data, the smart contract is automatically executed to determine whether the data flow is reasonable. If the data flow is unreasonable, the corresponding data flow will not be executed and an error message will be given.

[0011] In addition, the present application also provides an artificial intelligence sample data tracing device based on blockchain, including: a sample data object generation unit configured to generate a sample data object based on the artificial intelligence sample data when the generated artificial intelligence sample data is detected; A sample data fingerprint generating unit is configured to encrypt the sample data object using a hash encryption algorithm to generate a sample data fingerprint, add the sample data fingerprint and the sample data object to the blockchain account book, and generate a first evidence storage number; A priority determination unit is configured to determine the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data, and determine the priority of the sample traceability key nodes according to the flow order of the key links corresponding to the entire life cycle; The sample data circulation tracking unit is configured to generate each data object corresponding to the sample traceability key node according to the sample data fingerprint, the first evidence number, the key link, the circulation order and the priority, add each data object to the blockchain account book according to the time sequence and generate each second evidence number, and return the corresponding second evidence number to each sample traceability key node; The sample data full-process traceability unit is configured to obtain the corresponding evidence number when receiving an artificial intelligence sample data traceability request, perform on-chain evidence collection based on the evidence number, the first evidence number and the second evidence number to obtain the evidence content data, and return the evidence content data to the user.

[0012] Optionally, the sample data object generation unit is further configured to: Extract metadata information of artificial intelligence sample data, and generate metadata objects based on the metadata information; Generate sample data objects based on metadata objects and artificial intelligence sample data.

[0013] Optionally, the sample data fingerprint generating unit is further configured to: Generate a data block according to the sample data fingerprint and the sample data object; The data block is verified for integrity based on the blockchain smart contract, and in response to passing the integrity verification, the data block is added to the blockchain ledger.

[0014] Optionally, the sample data full-process traceability unit is further configured to: Based on the forensic content data, a third data object is generated, and the third data object is returned to the user.

[0015] Optionally, the key links include an upload link and a distribution link, the flow order is upload first and then distribution, the key nodes of sample traceability include a collection terminal-level sample library, a business-level sample library and a headquarters-level sample library, and the priority includes the priority in the upload link and the priority in the distribution link, wherein the priority in the upload link is that the priority of the collection terminal-level sample library is greater than the priority of the business-level sample library, which is greater than the priority of the headquarters-level sample library, and the priority in the distribution link is that the priority of the headquarters-level sample library is greater than the priority of the business-level sample library; and The sample data flow tracking unit is further configured to: In response to the completion of adding the sample data fingerprint and the sample data object to the blockchain account book by the acquisition terminal-level sample library, a corresponding data object B is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the first evidence number, the acquisition terminal-level sample library, the business-level sample library, the upload link and the current time, and the data object B is added to the blockchain account book through the business-level sample library and a corresponding second evidence number No2 is generated; In response to the business-level sample library completing the addition of data object B to the blockchain ledger, a corresponding data object B' is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No2, the business-level sample library, the headquarters-level sample library, the upload link and the current time, and the data object B' is added to the blockchain ledger through the headquarters-level sample library and a corresponding second evidence number No3 is generated; In response to the headquarters-level sample library completing the addition of data object B' to the blockchain ledger, the corresponding data object B'' is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No3, the headquarters-level sample library, the business-level sample library, the distribution link and the current time. The data object B'' is added to the blockchain ledger through the business-level sample library and the corresponding second evidence number No4 is generated.

[0016] Optionally, the sample data full-process traceability unit is further configured to: The evidence number is matched with the first evidence number and each second evidence number, and the corresponding evidence content data is queried in the blockchain ledger based on the matched first evidence number or second evidence number. If the queried evidence content data also contains the evidence number, the corresponding evidence content data is continued to be queried based on the contained evidence number until the queried evidence content data no longer contains the evidence number, and all the queried evidence content data are summarized in time series to obtain the evidence content data.

[0017] Optionally, the device further includes a smart contract execution unit configured to: When data flows at each key sample traceability node and each key link in the entire life cycle of artificial intelligence sample data, the smart contract is automatically executed to determine whether the data flow is reasonable. If the data flow is unreasonable, the corresponding data flow will not be executed and an error message will be given.

[0018] In addition, the present application also provides an artificial intelligence sample data traceability electronic device based on blockchain, including: one or more processors; a storage device for storing one or more programs, when one or more programs are executed by one or more processors, one or more processors implement the above-mentioned blockchain-based artificial intelligence sample data traceability method.

[0019] In addition, the present application also provides a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned blockchain-based artificial intelligence sample data traceability method is implemented.

[0020] To achieve the above objective, according to another aspect of the embodiments of the present application, a computer program product is provided.

[0021] A computer program product of an embodiment of the present application includes a computer program, which, when executed by a processor, implements the blockchain-based artificial intelligence sample data tracing method provided in an embodiment of the present application.

[0022] An embodiment of the above invention has the following advantages or beneficial effects: the present application generates a sample data object based on the artificial intelligence sample data when the generated artificial intelligence sample data is detected; the sample data object is encrypted using a hash encryption algorithm to generate a sample data fingerprint, the sample data fingerprint and the sample data object are added to the blockchain account book, and a first evidence number is generated; the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data are determined, and the priority of the sample traceability key nodes is determined according to the flow sequence of the key links corresponding to the entire life cycle; according to the sample data fingerprint, the first evidence number, the key link, the flow sequence and the priority, each data object corresponding to the sample traceability key node is generated, each data object is added to the blockchain account book according to the time sequence and each second evidence number is generated, and the corresponding second evidence number is returned to each sample traceability key node; when receiving an artificial intelligence sample data traceability request, the corresponding evidence number is obtained, and on-chain evidence is obtained based on the evidence number, the first evidence number and the second evidence number to obtain evidence content data, and the evidence content data is returned to the user. This application introduces the first evidence number and the second evidence number, and traces the artificial intelligence sample data based on the blockchain, which can enhance the transparency of the flow of artificial intelligence sample data, improve the quality of artificial intelligence sample data, improve the efficiency and accuracy of data traceability, and improve the training effect of related models. By encrypting the sample data objects with a hash encryption algorithm, the compliance management and control of sample use can be strengthened, and the security of core confidential data can be ensured while sharing resources, thereby improving data security.

[0023] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are used to better understand the present application and do not constitute an improper limitation on the present application. Figure 1 It is a schematic diagram of the main process of the blockchain-based artificial intelligence sample data tracing method according to one embodiment of the present application; Figure 2 It is a schematic diagram of the main process of the blockchain-based artificial intelligence sample data tracing method according to one embodiment of the present application; Figure 3 This is a schematic diagram of the main process of sample data fingerprint generation of a blockchain-based artificial intelligence sample data traceability method according to an embodiment of the present application; Figure 4This is a schematic diagram of the main process of sample data flow tracking of a blockchain-based artificial intelligence sample data traceability method according to an embodiment of the present application; Figure 5 This is a schematic diagram of the main process of tracing the source of sample data throughout the process of an artificial intelligence sample data tracing method based on blockchain according to an embodiment of the present application; Figure 6 It is a schematic diagram of the main units of the artificial intelligence sample data tracing device based on blockchain according to an embodiment of the present application; Figure 7 is an exemplary system architecture diagram to which the embodiments of the present application can be applied; Figure 8 It is a structural diagram of a computer system of a terminal device or server suitable for implementing an embodiment of the present application. DETAILED DESCRIPTION

[0025] The following is an explanation of the exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, the description of known functions and structures is omitted in the following description. It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of the present application are in compliance with the relevant provisions of national laws and regulations. It should be noted that in the embodiments of the present application, certain software, components, models, and other existing solutions in the industry may be mentioned, which should be considered as exemplary, and their purpose is only to illustrate the feasibility of the implementation of the technical solution of the present application, but it does not mean that the applicant has or must have used the solution. In the technical solution of the present application, the collection, collection, update, analysis, processing, use, transmission, storage, etc. of the user personal information involved are in compliance with the provisions of relevant laws and regulations, are used for legal and reasonable purposes, and do not violate public order and good customs, are not shared, leaked or sold outside these legal uses, and are subject to supervision and management by regulatory authorities. Take necessary measures to prevent illegal access to such user personal information data, maintain the security of user personal information, network security and national security, ensure that persons who have access to personal information data comply with relevant laws and regulations, and ensure the security of user personal information. Once such user personal information data is no longer needed, the risk should be minimized by limiting or even prohibiting data collection and / or deleting data.

[0026] When used, including in certain related applications, user privacy is protected by de-identifying data, such as by removing specific identifiers when used, controlling the amount or specificity of data stored, controlling how data is stored, and / or other methods of de-identification.

[0027] Figure 1 It is a schematic diagram of the main process of the blockchain-based artificial intelligence sample data tracing method according to an embodiment of the present application, such as Figure 1 As shown, the blockchain-based artificial intelligence sample data traceability method mainly includes the following steps S101-S105.

[0028] Step S101, when generated artificial intelligence sample data is detected, a sample data object is generated based on the artificial intelligence sample data.

[0029] In this embodiment, the execution subject (for example, a server) of the blockchain-based artificial intelligence sample data traceability method can detect in real time whether artificial intelligence sample data is generated through a wired connection or a wireless connection. When the generated artificial intelligence sample data is detected, the execution subject can generate a sample data object based on the artificial intelligence sample data.

[0030] Specifically, based on artificial intelligence sample data, a sample data object is generated, including: extracting metadata information of the artificial intelligence sample data, and generating a metadata object according to the metadata information; and generating a sample data object based on the metadata object and the artificial intelligence sample data.

[0031] For example, the metadata information of sample data can be a series of data fields that describe the sample, including name, sample data access address, sample format (picture, audio, video, text, etc.), sample source (business system name, collection terminal name, etc.), sample generation method (terminal collection, system collection, manual collection, etc.), sample business type, sample collection time, sample collection location, etc.

[0032] For example, the metadata object has a specific structure, which may be as follows:

[0033] Combining metadata objects and AI sample data to construct complete sample data objects can be used for data integrity verification and improve the quality of AI sample data.

[0034] Step S102: encrypt the sample data object using a hash encryption algorithm to generate a sample data fingerprint, add the sample data fingerprint and the sample data object to the blockchain account book, and generate a first evidence number.

[0035] For example, a one-way hash function is used to "summarize" the sample data object to be processed into a string of fixed-length ciphertext, namely the sample data fingerprint. The results of summarizing different sample data objects into ciphertext are always different, while the summaries of the same original text must be consistent.

[0036] Specifically, adding the sample data fingerprint and the sample data object to the blockchain ledger includes: generating a data block according to the sample data fingerprint and the sample data object; performing integrity verification on the data block based on the blockchain smart contract, and adding the data block to the blockchain ledger in response to passing the integrity verification.

[0037] The execution subject can combine the sample data fingerprint and the sample data object according to the preset rules to generate a data block. The generated data block is verified for integrity using the blockchain smart contract. After the integrity verification is passed, the corresponding data block is added to the blockchain account book and the first evidence number, such as No1, is generated, thereby ensuring the high quality of the artificial intelligence sample data.

[0038] Step S103, determine the key nodes of sample traceability corresponding to the entire life cycle of the artificial intelligence sample data, and determine the priority of the key nodes of sample traceability according to the flow order of the key links corresponding to the entire life cycle.

[0039] For example, the key nodes of sample traceability corresponding to the full life cycle of artificial intelligence sample data may include: acquisition terminal-level sample library, business-level sample library, and headquarters-level sample library. The key links corresponding to the full life cycle of artificial intelligence sample data may include: one or more of the links of collection, uploading, distribution, desensitization, and encrypted transmission.

[0040] The flow order of the key links corresponding to the full life cycle of artificial intelligence sample data can be collection-upload-distribution-desensitization-encrypted transmission, where the collection link involves the collection terminal-level sample library, the upload link involves the collection terminal-level sample library, the business-level sample library and the headquarters-level sample library in turn, and the distribution link involves the headquarters-level sample library and the business-level sample library in turn, thereby determining the priority of the sample library (i.e., the sample traceability key node) involved in the link involved in the flow order. Specifically, according to the flow order, first determine the priority (i.e., use priority or call priority) of the sample traceability key node in the upload link that needs to be used first, specifically, the priority of the collection terminal-level sample library is greater than the priority of the business-level sample library, which is greater than the priority of the headquarters-level sample library, and then determine the priority (i.e., use priority or call priority) of the sample traceability key node in the distribution link that needs to be used later, specifically, the priority of the headquarters-level sample library is greater than the priority of the business-level sample library.

[0041] Step S104, based on the sample data fingerprint, the first evidence number, the key links, the flow order and the priority, generate each data object corresponding to the sample traceability key node, add each data object to the blockchain account book according to the time sequence and generate each second evidence number, and return the corresponding second evidence number to each sample traceability key node.

[0042] According to the sample data fingerprint, the first evidence number (for example, evidence number No1), key links (for example, including upload links and distribution links), flow order (for example, upload first and then distribute) and priority (for example, the priority of the key node of sample traceability in the upload link that needs to be used first (that is, the use priority or call priority), specifically, the priority of the acquisition terminal-level sample library is higher than the priority of the business-level sample library, and the priority of the key node of sample traceability in the distribution link that needs to be used later (that is, the use priority or call priority), specifically, the priority of the headquarters-level sample library is higher than the priority of the business-level sample library), generate the sample traceability key nodes (for example, the acquisition terminal-level sample library, the business-level sample library, the headquarters ... For each data object corresponding to the business-level sample library and the headquarters-level sample library (for example, a data object containing a structure such as sample data metadata, sample data fingerprint, the evidence number returned by the blockchain in the previous link, the source node of this flow, the destination node of this flow, the type of operation of this flow and the flow time), each data object is added to the blockchain ledger according to the time sequence and each second evidence number is generated (each second evidence number, such as evidence number No2, evidence number No3, evidence number No4), and the corresponding second evidence number is returned to each sample traceability key node, for example, evidence number No2 is returned to the business-level sample library, evidence number No3 is returned to the headquarters-level sample library, and evidence number No4 is returned to the business-level sample library.

[0043] Step S105, when receiving the artificial intelligence sample data traceability request, obtain the corresponding evidence number, perform on-chain evidence collection based on the evidence number, the first evidence number and the second evidence number to obtain the evidence content data, and return the evidence content data to the user.

[0044] The executive entity provides users with a unified sample chain traceability interface service by opening a unified sample chain traceability interface to users, so that users can trace the source of artificial intelligence sample data, enhance the transparency of artificial intelligence sample data flow, improve the quality of artificial intelligence sample data, improve data traceability efficiency and accuracy, and enhance the training effect of related models.

[0045] Specifically, on-chain evidence is collected based on the evidence number, the first evidence number and the second evidence number to obtain evidence content data, including: matching the evidence number with the first evidence number and each second evidence number, querying the corresponding evidence content data in the blockchain ledger based on the matched first evidence number or second evidence number, if the queried evidence content data also contains the evidence number, continuing to query the corresponding evidence content data based on the contained evidence number until the queried evidence content data no longer contains the evidence number, and then summarizing all the queried evidence content data according to time series to obtain the evidence content data.

[0046] For example, the evidence number (for example, No4) is matched with the first evidence number (for example, No1) and each second evidence number (for example, No2, No3, No4), and the corresponding evidence content data (for example, No4) is queried in the blockchain account book based on the matched first evidence number or the second evidence number (for example, No4 is matched). If the queried evidence content data also contains the evidence number (for example, No3 is also included), then the corresponding evidence content data (for example, No2, sample fingerprint, upload record, etc.) is continued to be queried based on the included evidence number (for example, No3). If the queried evidence content data also contains the evidence number (for example, No2 is also included), then the corresponding evidence content data (for example, sample fingerprint, sample collection record, etc.) is continued to be queried based on the included evidence number (for example, No2) until the queried evidence content data (for example, sample fingerprint, sample collection record, etc.) no longer contains the evidence number, and all the queried evidence content data are summarized according to the time series to obtain the evidence content data.

[0047] The forensic content data is obtained by summarizing all the evidence content data on the blockchain obtained through queries.

[0048] Specifically, returning the forensic content data to the user includes: generating a third data object based on the forensic content data, and returning the third data object to the user.

[0049] For example, the third data object may be as follows: { { "id":0, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Collection equipment / business system A", / / Source node of this flow “destination”:”Acquisition terminal level sample library”, / / The destination node of this flow "operation":"Collection and Generation", / / Type of this flow operation “time”:”2024 / 10 / 10 9:00:00”, / / transfer time } { "id":1, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Acquisition terminal level sample library", / / Source node of this flow “destination”:”Business-level sample library”, / / The destination node of this transfer “operation”:”upload”, / / type of this transfer operation “time”:”2024 / 10 / 10 10:00:00”, / / transfer time } { "id":2, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Business-level sample library", / / Source node of this transfer “destination”:”Headquarters-level sample library”, / / The destination node of this transfer “operation”:”upload”, / / type of this transfer operation “time”:”2024 / 10 / 10 11:00:00”, / / transfer time } { "id":3, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Headquarters-level sample library", / / Source node of this transfer “destination”:”Business-level sample library”, / / The destination node of this transfer "operation":"distribution and use", / / type of this transfer operation “time”:”2024 / 10 / 10 12:00:00”, / / transfer time } } Specifically, the method also includes: when data flows at each key sample traceability node and each key link in the entire life cycle of artificial intelligence sample data, the smart contract is automatically executed to determine whether the data flow is reasonable. When the data flow is unreasonable, the corresponding data flow is not executed and an error message is given.

[0050] For example, smart contracts are used to manage the flow of data samples. Smart contracts specify the rules for the flow of data samples between different links. For example, only nodes with specific permissions can process and circulate data samples. Smart contracts are automatically executed during the data flow process, and judge whether the flow is reasonable based on preset conditions (for example, before uploading samples, it is necessary to meet the operation of generating sample fingerprints and storing evidence. Only when there is a certificate number corresponding to the sample fingerprint evidence on the chain, can the upload operation be performed). If it is unreasonable, it will not be executed and an error message will be given.

[0051] This embodiment generates a sample data object based on the artificial intelligence sample data when the generated artificial intelligence sample data is detected; encrypts the sample data object using a hash encryption algorithm to generate a sample data fingerprint, adds the sample data fingerprint and the sample data object to the blockchain account book, and generates a first evidence number; determines the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data, and determines the priority of the sample traceability key nodes according to the flow sequence of the key links corresponding to the entire life cycle; generates each data object corresponding to the sample traceability key node according to the sample data fingerprint, the first evidence number, the key link, the flow sequence and the priority, adds each data object to the blockchain account book according to the time sequence and generates each second evidence number, and returns the corresponding second evidence number to each sample traceability key node; when receiving an artificial intelligence sample data traceability request, obtains the corresponding evidence number, performs on-chain evidence collection based on the evidence number, the first evidence number and the second evidence number to obtain evidence content data, and returns the evidence content data to the user. This application introduces the first evidence number and the second evidence number, and traces the artificial intelligence sample data based on the blockchain, which can enhance the transparency of the flow of artificial intelligence sample data, improve the quality of artificial intelligence sample data, improve the efficiency and accuracy of data traceability, and improve the training effect of related models. By encrypting the sample data objects with a hash encryption algorithm, the compliance management and control of sample use can be strengthened, and the security of core confidential data can be ensured while sharing resources, thereby improving data security.

[0052] Figure 2 This is a schematic diagram of the main process of the blockchain-based artificial intelligence sample data tracing method according to an embodiment of the present application. Figure 2 As shown, the blockchain-based artificial intelligence sample data traceability method mainly includes the following steps S201-S208.

[0053] Step S201, when generated artificial intelligence sample data is detected, a sample data object is generated based on the artificial intelligence sample data.

[0054] The artificial intelligence sample data and the metadata information corresponding to the artificial intelligence sample data are constructed into a complete sample data object.

[0055] Step S202: encrypt the sample data object using a hash encryption algorithm to generate a sample data fingerprint, add the sample data fingerprint and the sample data object to the blockchain account book, and generate a first evidence number.

[0056] The first certificate number, for example No1.

[0057] Step S203, determine the key nodes of sample traceability corresponding to the entire life cycle of the artificial intelligence sample data, and determine the priority of the key nodes of sample traceability according to the flow order of the key links corresponding to the entire life cycle.

[0058] For example, the key links may include the upload link and the distribution link. The flow order is upload first and then distribution. The key nodes of sample traceability include the collection terminal-level sample library, the business-level sample library and the headquarters-level sample library.

[0059] The priority of the key nodes of sample traceability can be determined according to the order of calling (or using) of sample libraries involved in the key links corresponding to the entire life cycle of artificial intelligence sample data.

[0060] For example, the priority may include the priority in the upload link and the priority in the distribution link, wherein the priority in the upload link is that the priority of the collection terminal-level sample library is greater than the priority of the business-level sample library, which is greater than the priority of the headquarters-level sample library, and the priority in the distribution link is that the priority of the headquarters-level sample library is greater than the priority of the business-level sample library.

[0061] In the embodiment of the present application, data object B, data object B', and data object B'' are all data objects containing a structure including sample data metadata, sample data fingerprint, the evidence number returned by the blockchain in the previous link, the source node of this transfer, the destination node of this transfer, the type of operation of this transfer, and the transfer time. The difference is that the evidence number returned by the blockchain in the previous link, the source node of this transfer, the destination node of this transfer, the type of operation of this transfer, and the transfer time in data object B, data object B', and data object B'' may be different.

[0062] Step S204, in response to the completion of the acquisition terminal-level sample library adding the sample data fingerprint and the sample data object to the blockchain ledger, based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the first evidence number, the acquisition terminal-level sample library, the business-level sample library, the upload link and the current time, the corresponding data object B is generated, and the data object B is added to the blockchain ledger through the business-level sample library and the corresponding second evidence number No2 is generated.

[0063] Specifically, when the acquisition terminal-level sample library completes adding the sample data fingerprint and the sample data object to the blockchain account book, the execution entity can generate the corresponding data object B according to the preset structure based on the metadata information of the artificial intelligence sample data (that is, the sample data metadata, which may include the sample name), the sample data fingerprint, the first evidence number (for example, No1, which is the evidence number returned by the blockchain in the previous link), the acquisition terminal-level sample library (that is, the source node of this flow), the business-level sample library (that is, the destination node of this flow), the upload link (that is, the type of this flow operation) and the current time (that is, the flow time). For example, the data object B can be as follows: { "id":1, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Acquisition terminal level sample library", / / Source node of this flow “destination”:”Business-level sample library”, / / The destination node of this transfer “operation”:”upload”, / / type of this transfer operation “time”:”2024 / 10 / 10 10:00:00”, / / transfer time } Among them, "id": 1 represents the first evidence number (for example, No1, which is the evidence number returned by the blockchain in the previous link).

[0064] The data object B is added to the blockchain account book through the business-level sample library and the corresponding second evidence number No2 is generated.

[0065] Step S205, in response to the business-level sample library completing the addition of data object B to the blockchain ledger, based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No2, the business-level sample library, the headquarters-level sample library, the upload link and the current time, the corresponding data object B' is generated, and the data object B' is added to the blockchain ledger through the headquarters-level sample library and the corresponding second evidence number No3 is generated.

[0066] Specifically, when the business-level sample library completes adding the data object B to the blockchain account book, the execution subject can generate the corresponding data object B' based on the metadata information of the artificial intelligence sample data (that is, the sample data metadata, which may include the sample name), the sample data fingerprint, the second evidence number No2 (that is, the evidence number returned by the blockchain in the previous link), the business-level sample library (that is, the source node of this transfer), the headquarters-level sample library (that is, the destination node of this transfer), the upload link (that is, the type of this transfer operation) and the current time (that is, the transfer time), as shown below: { "id":2, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Business-level sample library", / / Source node of this transfer “destination”:”Headquarters-level sample library”, / / The destination node of this transfer “operation”:”upload”, / / type of this transfer operation “time”:”2024 / 10 / 10 11:00:00”, / / transfer time } Among them, "id": 2 represents the second evidence number No2 (that is, the evidence number returned by the blockchain in the previous link).

[0067] The data object B' is added to the blockchain account book through the headquarters-level sample library and a corresponding second evidence number No3 is generated.

[0068] Step S206, in response to the headquarters-level sample library completing the addition of data object B' to the blockchain ledger, based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No3, the headquarters-level sample library, the business-level sample library, the distribution link and the current time, the corresponding data object B'' is generated, and the data object B'' is added to the blockchain ledger through the business-level sample library and the corresponding second evidence number No4 is generated.

[0069] Specifically, when the headquarters-level sample library completes adding the data object B' to the blockchain account book, the execution entity can generate the corresponding data object B'' based on the metadata information of the artificial intelligence sample data (that is, the sample data metadata, which may include the sample name), the sample data fingerprint, the second evidence number No3 (that is, the evidence number returned by the blockchain in the previous link), the headquarters-level sample library (that is, the source node of this transfer), the business-level sample library (that is, the destination node of this transfer), the distribution link (that is, the type of this transfer operation) and the current time (that is, the transfer time), as shown below: { "id":3, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Headquarters-level sample library", / / Source node of this transfer “destination”:”Business-level sample library”, / / The destination node of this transfer "operation":"distribution and use", / / type of this transfer operation “time”:”2024 / 10 / 10 12:00:00”, / / transfer time } Among them, "id": 3 represents the second evidence number No3 (that is, the evidence number returned by the blockchain in the previous link).

[0070] The data object B'' is added to the blockchain ledger through the business-level sample library and the corresponding second evidence number No4 is generated.

[0071] Step S207, returning the corresponding second evidence number to each sample traceability key node.

[0072] Each second evidence number, such as evidence number No. 2, evidence number No. 3, and evidence number No. 4, returns the corresponding second evidence number to each sample traceability key node. For example, evidence number No. 2 is returned to the business-level sample library, evidence number No. 3 is returned to the headquarters-level sample library, and evidence number No. 4 is returned to the business-level sample library.

[0073] Step S208, when receiving the artificial intelligence sample data traceability request, obtain the corresponding evidence number, perform on-chain evidence collection based on the evidence number, the first evidence number and the second evidence number to obtain the evidence content data, and return the evidence content data to the user.

[0074] When receiving the artificial intelligence sample data traceability request, obtain the corresponding evidence number, match the evidence number (for example, No4) with the first evidence number (for example, No1) and each second evidence number (for example, No2, No3, No4), and query (for example, No4) the corresponding evidence content data (for example, No3, sample fingerprint, usage record, etc.) in the blockchain account book based on the matched first evidence number or second evidence number (for example, No4). If the queried evidence content data also contains the evidence number (for example, No3 is also included), then based on The included evidence number (for example, No3) continues to query the corresponding evidence content data (for example, No2, sample fingerprint, upload records, etc.); if the queried evidence content data also contains the evidence number (for example, also includes No2), then based on the included evidence number (for example, No2), continue to query the corresponding evidence content data (for example, sample fingerprint, sample collection records, etc.) until the queried evidence content data (for example, sample fingerprint, sample collection records, etc.) no longer contains the evidence number, then all the queried evidence content data are summarized according to the time series to obtain the evidence content data.

[0075] The embodiment of the present application provides a unified interface for users with needs to query, allowing artificial intelligence developers and users, data managers or regulatory agencies to conduct traceability queries. The user initiates a traceability query by entering the fingerprint of the sample data or the certificate number returned by any node blockchain. Based on the query request, the blockchain network retrieves all transaction records related to the data sample from the account book, including the initial entry record of the data, various circulation records, etc. Based on these records, a traceability path for the data sample is constructed, showing all the links, processing nodes, time and other information that the data sample has experienced from generation to the current state, thereby realizing the traceability of the artificial intelligence sample data.

[0076] The embodiment of the present application performs artificial intelligence sample data traceability based on blockchain, tracks the entire life cycle of sample data on the blockchain, and creates sample data traceability management capabilities based on on-chain and off-chain collaboration mechanisms. This can help companies with AI capabilities to control the quality and security of sample data and create safe and efficient artificial intelligence services.

[0077] Explanation of relevant terms: AI sample data: AI sample data refers to a collection of data used to train or test AI models. These data sets usually contain a large number of instances (or samples), each of which contains multiple attributes (or features) and corresponding attribute values. For example, in an image recognition task, sample data may include a large number of labeled pictures, where each picture is an instance, the pixel values ​​of the picture constitute its attributes, and the category of the picture (such as cat, dog) is its label. These sample data are crucial for training AI models. They help the model learn and understand the inherent laws and patterns of the data, thereby improving the prediction accuracy of the model.

[0078] Sample library: In enterprise-level applications, especially for large or multinational companies, the sample library is not only a data storage and management system, but also a vertically layered data ecosystem that is closely linked to the corporate organizational structure. This system starts from the top level of the company and extends downward to each business unit, department, and even specific position. Each level has a corresponding sample library to achieve the collection, upload, distribution, utilization, and management of sample data. By building a vertically layered enterprise-level sample library system, enterprises can better integrate and utilize data resources at all levels of institutions, improve the efficiency and quality of data analysis and utilization, and provide strong support for the company's strategic decision-making and business development.

[0079] Data traceability: Data traceability is a technology that tracks the process of data from source to final product. It records the evolution information and evolution processing content of data throughout its life cycle, including data generation, dissemination, modification and extinction. Data traceability aims to ensure the authenticity and historical traceability of data. By recording the source, processing process and conversion relationship of data, data users can understand the complete history of data, verify the accuracy of data, and discover possible problems with data. Data traceability technology has been widely used in many fields such as biology, medicine, GIS, cloud computing, etc. to improve the reliability and credibility of data.

[0080] Blockchain: Blockchain is a technical architecture, a distributed infrastructure and computing paradigm for programming and operating data. Blockchain uses block chain data structure to verify and store data, uses distributed node consensus algorithm to generate and update data, uses cryptography to ensure the security of data transmission and access, and uses smart contracts composed of automated script codes. Blockchain has the characteristics of being tamper-proof and trustworthy.

[0081] Blockchain traceability: Blockchain traceability refers to the data traceability method implemented using blockchain technology. As an open and distributed ledger, blockchain uses a decentralized recording method to generate unique and encrypted hash values ​​through a hash algorithm, and permanently stores these records on the blockchain. Blockchain traceability uses the immutability and transparency of blockchain to ensure that every link of data from the source to the final product is fully recorded and traced. In blockchain traceability, each transaction record is bound to the trader information, and these data records cannot be destroyed or tampered with, thereby improving the security and credibility of data traceability. Blockchain traceability has important application value in finance, supply chain and other fields, which can reduce fraud risks and improve data security.

[0082] On-chain and off-chain collaboration: On-chain and off-chain collaboration refers to the interaction and collaboration between data on the blockchain network and data outside the blockchain network. On-chain data refers to data stored in the blockchain network, such as transaction records, smart contract status, etc., which are open, transparent, and tamper-proof. Off-chain data refers to data stored outside the blockchain network, such as business data, file storage, etc., and the storage and operation of these data are not directly affected by the blockchain. On-chain and off-chain collaboration uses certain technical means (such as synchronization mechanisms, event-driven models, etc.) to achieve real-time synchronization or on-demand updates between on-chain data and off-chain data to optimize business processes and improve system performance. On-chain and off-chain collaboration can reduce overall costs, improve system flexibility and interoperability while ensuring the core advantages of blockchain (such as tamper-proof and security), thereby supporting diverse application scenarios and business needs.

[0083] Artificial intelligence sample database: In enterprise-level applications, especially large or multinational companies, they usually build their own enterprise-level artificial intelligence platforms, in which the sample database is not only a storage and management system for sample data, but also a vertically layered data ecosystem that is closely linked to the corporate organizational structure. This system starts from the top level of the company and extends downward to each business unit and even specific positions. From top to bottom, it is divided into three layers: headquarters-level sample library, business-level sample library, and collection terminal-level sample library. Each level has a corresponding sample library to realize the collection, upload, distribution, utilization and management of sample data. The three-layer sample data will have multiple data transmissions and interactions.

[0084] Collection: The terminal-level sample library is responsible for collecting sample data from the business areas or work environments of specific positions to ensure the comprehensiveness and accuracy of the data.

[0085] Upload: Through data pipelines, API interfaces and other technical means, data transmission and sharing between lower-level sample libraries and higher-level sample libraries are realized to ensure the timeliness and consistency of data.

[0086] Distribution: Based on business needs and data permissions, the headquarters-level sample library is responsible for distributing sample data to the business-level sample library to support data analysis and decision-making on the business side.

[0087] Management: Sample libraries at all levels are also responsible for data quality management, data lifecycle management, data security and privacy protection to ensure data compliance and sustainability.

[0088] Blockchain smart contract: Blockchain smart contract is a self-executing contract clause stored in code on the blockchain network. It is a computer protocol designed to disseminate, verify or execute contracts in an information-based manner. Based on the characteristics of blockchain, such as decentralization, immutability and traceability. The code of the smart contract is deployed on the blockchain, and when the preset conditions are met, the contract automatically performs the corresponding operations. For example, in a supply chain finance scenario, if the goods have arrived at the designated location (this fact is verified and recorded on the blockchain through IoT devices, etc.), then according to the terms of the smart contract, the payment will be automatically transferred from the buyer's account to the seller's account. The technical route and development language of blockchain smart contracts are usually different from those of business systems. By calling the blockchain SDK in the application system, the corresponding API interface of the smart contract is developed to interact with the business system.

[0089] Digital summary: Digital summary uses a one-way hash function to convert the original text to be processed into a string of fixed-length ciphertext. The results of converting different original text summaries into ciphertext are always different, while the summaries of the same original text must be the same.

[0090] In view of the business characteristics of enterprise-level artificial intelligence platform sample libraries with multiple levels and complex sample circulation links, a blockchain-based artificial intelligence sample data traceability method is designed with a high cohesion and low coupling design approach. Generate a unique and verifiable fingerprint for each piece of sample data, bind the operation records of the sample data in key links such as collection, uploading, distribution, desensitization, and encrypted transmission to the sample fingerprint and leave traces on the chain, establish a sample life cycle traceability link on the blockchain, and realize the full process record of sample data operations and full link credibility. Use smart contracts to set key nodes for sample traceability, customize multiple sample traceability links, and help improve sample quality management; provide a unified sample chain traceability interface service for sample libraries at all levels. On the one hand, the embodiment of the present application can enhance the transparency of sample data circulation, which is conducive to improving sample data quality and further improving model training effects; on the other hand, it can strengthen the compliance management and control of sample use, and ensure the security of core confidential data while sharing resources.

[0091] The embodiment of the present application can implement a blockchain-based sample data fingerprint generation method. The blockchain-based sample data fingerprint is generated based on digital summary technology. Taking a sample with a certain content as a unit, after the sample is generated, a hash operation is performed on the sample data / file to generate a unique and verifiable digital summary of the sample, and the summary is stored on the chain to construct a sample set fingerprint. The fingerprint on the chain is unique and cannot be tampered with. For all subsequent upload, distribution, traceability and other operations, as long as the sample content remains unchanged, the correspondence between the sample fingerprint and the actual received sample set can be verified anytime and anywhere.

[0092] The embodiment of the present application can realize a sample data flow tracking mechanism. The mechanism is based on blockchain smart contracts and application API technology, and a sample data evidence smart contract is developed. The functions include the evidence storage and evidence collection of sample data on the blockchain. The operation records of sample data in key links such as collection, uploading, distribution, desensitization, and encrypted transmission are bound to the sample fingerprint and recorded on the chain. The evidence relationship chain is established step by step, and the traceability link of the sample's entire life cycle is established on the blockchain, so as to realize the full process record of sample data operation and the full link credibility.

[0093] The embodiment of the present application can construct a traceability path for the entire process of sample data. This mechanism is based on blockchain smart contracts and application API technology. It uses smart contracts to set key nodes for sample traceability, customizes multiple sample traceability links, and based on the evidence relationship chain established in the previous process, any evidence node can be used as the traceability starting point to generate sample traceability results step by step. Provide a unified sample chain traceability interface service for sample libraries at all levels.

[0094] The most important of these is the construction and tracing of the evidence chain of sample data. The evidence chain is constructed by combining the sample data fingerprint with the chain evidence number of the previous operation of the sample data flowing between sample libraries at all levels. The evidence is then given a new number, which is constructed from small numbers to large numbers. When tracing the source, it is reversed and recursively peeled off level by level to obtain the evidence chain.

[0095] The artificial intelligence sample data traceability method based on blockchain in the embodiment of the present application involves at least three units, namely, a sample data fingerprint generation unit, a sample data flow tracking unit, and a sample data full-process traceability unit. The three units have a sequential dependency relationship in the business process, and the work completed by the previous unit is the basis for the work of the next unit. Each unit may include multiple modules, among which the sample data fingerprint generation unit may include a sample data fingerprint generation module, the sample data flow tracking unit may include a sample data flow tracking module, and the sample data full-process traceability unit may include a sample data full-process traceability module.

[0096] 1) Sample data fingerprint generation unit Sample data generation: When artificial intelligence sample data is generated, a series of metadata information of the sample data is collected to generate a data object A (i.e., the metadata object in the embodiment of the present application), the structure of which is as follows:

[0097] Among them, longitude is longitude and latitude is latitude.

[0098] The metadata of sample data is a series of data fields that describe the sample, including name, sample data access address, sample format (picture, audio, video, text, etc.), sample source (business system name, collection terminal name, etc.), sample generation method (terminal collection, system collection, manual collection, etc.), sample business type, sample collection time, sample collection location, etc.

[0099] Sample fingerprint generation and entry: The sample data and metadata are constructed into a complete sample data object, the sample data object is encrypted using a hash encryption algorithm, the sample data fingerprint is generated, and the sample data fingerprint and the sample data object are used together to call the blockchain evidence contract. The nodes in the blockchain network verify the uploaded data block, and after the verification is passed, it is added to the blockchain account book. After entering the blockchain, the evidence number No1 is returned.

[0100] 2) Sample data flow tracking unit Circulation record: When AI sample data circulates between sample libraries at different levels (such as uploading, distribution, etc.), each circulation is recorded as a new transaction on the blockchain. This transaction contains the data object B with the following structure:

[0101] The metadata of the sample data, the sample data fingerprint, the evidence number of the previous link of the flow, the source node and target node of the flow, the flow time and other information (that is, constructing this information into a data object with a structure like data object B and storing it in the blockchain again). It can be understood that the data object of each transaction is different at least because of the different evidence numbers, but the structure of the data object of each transaction is the same as the structure of data object B. In each processing link (such as uploading, distribution, etc.), the processing node verifies the data sample by comparing the sample fingerprint with the content of the sample source data to ensure the integrity of the data. After the verification is passed, the flow record is added to the blockchain ledger and the corresponding evidence number is returned.

[0102] Smart contract management: Use smart contracts to manage the flow of data samples. Smart contracts specify the rules for the flow of data samples between different links. For example, only nodes with specific permissions can process and circulate data samples. Smart contracts are automatically executed during the data flow process, and judge whether the flow is reasonable based on preset conditions (for example, before uploading samples, it is necessary to meet the operation of generating sample fingerprints and storing evidence. Only when there is a certificate number corresponding to the sample fingerprint evidence on the chain, can the upload operation be performed). If it is unreasonable, it will not be executed and an error message will be given.

[0103] 3) Sample data full process traceability unit Query interface: Provides a unified interface for users to query, allowing AI developers and users, data managers or regulators to conduct traceability queries. Users initiate traceability queries by entering the fingerprint of sample data or the certificate number returned by any node blockchain.

[0104] Tracing path construction: Based on the query request, the blockchain network retrieves all transaction records related to the data sample from the account book, including the initial data entry record, various circulation records, etc. Based on these records, the tracing path of the data sample is constructed, showing all the links, processing nodes, time and other information that the data sample has gone through from generation to the current state, thereby realizing the tracing of the AI ​​sample data.

[0105] The implementation process of the blockchain-based artificial intelligence sample data traceability method of the embodiment of the present application can be divided into three parts according to the execution stage, including: 1. Generate sample data fingerprint; 2. Track sample data flow; 3. Trace sample data throughout the entire process.

[0106] Figure 3 It is a schematic diagram of the main process of sample data fingerprint generation according to a blockchain-based artificial intelligence sample data traceability method according to an embodiment of the present application.

[0107] like Figure 3 As shown, specifically, sample data fingerprint generation (not yet used as Figure 3 The process of the business-level sample library and headquarters-level sample library shown in the figure is as follows: 1. Start - sample collection - sample generation: each business system, each collection terminal, and each sample data collector completes the collection and generation of a sample data set; 2. Transmit sample data, collected source information and other metadata to the blockchain platform: Data object A generated based on a series of metadata information of the sample data, together with the sample data source file, is constructed into a complete data object (i.e., sample data object). After data summary encryption, a sample data fingerprint (also called sample fingerprint) is generated and the sample collection record is stored on the blockchain; 3. The sample data fingerprint and the sample data object are used together to call the blockchain platform's evidence storage smart contract (also known as the blockchain evidence storage contract). The processing node in the blockchain network verifies the uploaded data block consisting of the sample data fingerprint and the sample data object, and adds it to the blockchain account book after verification. After entering the blockchain, the evidence storage number No1 corresponding to the first entry operation of the sample data is returned to the collection terminal-level sample library, and the collection terminal-level sample library completes the fingerprint evidence.

[0108] Figure 4 This is a schematic diagram of the main flow of sample data flow tracking of the artificial intelligence sample data traceability method based on blockchain according to an embodiment of the present application. Figure 4 As shown, the sample data flow tracking process is as follows: 4. Sample upload (transmit No. 1 at the same time). After the terminal-level sample library completes the sample data collection and blockchain entry, it uploads the sample data to the next level, that is, the business-level sample library, and at the same time uploads the evidence number No. 1 returned by the blockchain in the last circulation operation of the sample data.

[0109] 5. Business-level sample collection. After the business-level sample library collects the sample data, it uploads the data structured as data object B, including sample fingerprint, evidence number No1, upload source information and other metadata, to the blockchain platform (based on the blockchain evidence storage smart contract, also known as the blockchain evidence contract), to achieve the chain-based evidence storage of sample upload records. The blockchain platform returns the evidence number No2 of this upload operation to the business-level sample library.

[0110] 6. Sample upload (transmit No. 2 at the same time). After receiving the sample data uploaded by the collection terminal, the business-level sample library uploads the sample data to the next level, that is, the headquarters-level sample library, and uploads the evidence number No. 2 returned by the blockchain in the last circulation operation of the sample data.

[0111] 7. Headquarters sample collection: After the headquarters-level sample library collects the sample data from the business-level sample library, it uploads the data with the structure of data object B, including sample fingerprint, evidence number No2, upload source information and other metadata, to the blockchain platform (based on the blockchain evidence storage smart contract, also known as the blockchain evidence contract), to realize the chain storage of sample upload records. The blockchain platform returns the evidence number No3 of this upload operation to the headquarters-level sample library.

[0112] 8. Sample distribution (transmitting No. 3 at the same time). After the headquarters-level sample library collects all sample data, it distributes the sample data to the business-level sample library according to the business needs and data permissions of the business-level sample library to support data analysis and decision-making on the business side, and transmits the evidence number No. 3 to a certain business-level sample library at the same time.

[0113] 9. Business-level sample usage: After receiving the sample data distributed by the superior sample library (i.e., the headquarters-level sample library), the business-level sample library uses the sample data for model training and other operations (based on the blockchain evidence smart contract, also known as the blockchain evidence contract). The data with the structure of data object B, including sample fingerprint, evidence number No3, usage information and other metadata, is uploaded to the blockchain platform to realize the on-chain evidence storage of sample distribution and usage records. The blockchain returns the evidence number No4 of this usage operation to the business-level sample library. The whole process of sample information is uploaded to the chain.

[0114] Figure 5 This is a schematic diagram of the main process of tracing the source of sample data in the whole process of the artificial intelligence sample data tracing method based on blockchain according to an embodiment of the present application. Figure 5 As shown in the figure, the whole process traceability of sample data is as follows: 10. Start tracing from No.4 and collect evidence on the chain. Taking the sample distribution node as the starting point of the traceability chain, the user holding the evidence number No.4 corresponding to the sample data usage evidence record initiates a traceability application to the blockchain platform and transmits it to No.4.

[0115] 11. Through the blockchain platform, evidence is collected on the chain according to No4, and the obtained evidence content structure is data object B, which specifically includes: No3+sample fingerprint+usage record, etc.; pass it to No3 to continue to collect evidence, extract No3 to continue to collect evidence on the blockchain, and the obtained evidence content structure is data object B, which specifically includes: No2+sample fingerprint+upload record, etc.; pass it to No2 to continue to collect evidence, extract No2 to continue to collect evidence on the blockchain, and the obtained evidence content structure is data object B, which specifically includes: No1+sample fingerprint+upload record, etc.; pass it to No1 to continue to collect evidence, extract No1 to continue to collect evidence on the blockchain, and the obtained evidence content structure is data object B, which specifically includes: sample fingerprint+sample collection record; when the obtained evidence content no longer contains the evidence number, this traceability operation is completed.

[0116] 12. The blockchain constructs the chain of traceability on the chain into a data object C, and returns it to the user as the result of traceability (i.e., forensic content data): { { "id":0, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Collection equipment / business system A", / / Source node of this flow “destination”:”Acquisition terminal level sample library”, / / The destination node of this flow "operation":"Collection and Generation", / / Type of this flow operation “time”:”2024 / 10 / 10 9:00:00”, / / transfer time } { "id":1, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Acquisition terminal level sample library", / / Source node of this flow “destination”:”Business-level sample library”, / / The destination node of this transfer “operation”:”upload”, / / type of this transfer operation “time”:”2024 / 10 / 10 10:00:00”, / / transfer time } { "id":2, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Business-level sample library", / / Source node of this transfer “destination”:”Headquarters-level sample library”, / / The destination node of this transfer “operation”:”upload”, / / type of this transfer operation “time”:”2024 / 10 / 10 11:00:00”, / / transfer time } { "id":3, "name":"Sample name", “data_id”:”6cbd8fa85ad397b758a49d32b151ca0b8456d504cdbbd85e50c521c3b3d424c9”, / / / Sample data fingerprint "source":"Headquarters-level sample library", / / Source node of this transfer “destination”:”Business-level sample library”, / / The destination node of this transfer "operation":"distribution and use", / / type of this transfer operation “time”:”2024 / 10 / 10 12:00:00”, / / transfer time } } The embodiment of the present application can realize a sample data flow tracking mechanism, which is based on blockchain smart contracts and application API technology, and develops sample data evidence smart contracts, and its functions include evidence storage and evidence collection on the blockchain. The operation records of sample data in key links such as collection, uploading, distribution, desensitization, and encrypted transmission are bound to sample fingerprints and recorded on the chain, and evidence storage relationship chains are established step by step. The traceability link of the sample's entire life cycle is established on the blockchain to achieve full-process records of sample data operations and full-link credibility. Construct a full-process traceability path for sample data. This mechanism is based on blockchain smart contracts and application API technology. It uses smart contracts to set sample traceability key nodes, customizes multiple sample traceability links, and based on the evidence storage relationship chain established in the previous process, any evidence storage node can be used as the traceability starting point, and the sample traceability results are generated step by step. For sample libraries at all levels, a unified sample chain traceability interface service is provided. Sample data needs to be circulated between multi-level sample libraries when collected, uploaded, shared, and distributed. From the perspective of management and application, there is a real need to trace the source of sample data. The sample traceability method based on blockchain in the embodiment of the present application can, on the one hand, enhance the transparency of sample data flow, which is conducive to improving the quality of sample data and further improving the model training effect; on the other hand, it can strengthen the compliance management and control of sample use, and ensure the security of core confidential data while sharing resources.

[0117] Figure 6 Schematic diagram of the main units of the artificial intelligence sample data traceability device based on blockchain according to an embodiment of the present application. Figure 6 As shown, the blockchain-based artificial intelligence sample data traceability device 600 includes a sample data object generation unit 601, a sample data fingerprint generation unit 602, a priority determination unit 603, a sample data flow tracking unit 604 and a sample data full-process traceability unit 605.

[0118] The sample data object generation unit 601 is configured to generate a sample data object based on the artificial intelligence sample data when the generated artificial intelligence sample data is detected.

[0119] The sample data fingerprint generating unit 602 is configured to encrypt the sample data object using a hash encryption algorithm to generate a sample data fingerprint, add the sample data fingerprint and the sample data object to the blockchain account book, and generate a first evidence number.

[0120] The priority determination unit 603 is configured to determine the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data, and determine the priority of the sample traceability key nodes according to the flow order of the key links corresponding to the entire life cycle.

[0121] The sample data flow tracking unit 604 is configured to generate each data object corresponding to the sample traceability key node according to the sample data fingerprint, the first evidence number, the key link, the flow order and the priority, add each data object to the blockchain ledger according to the time sequence and generate each second evidence number, and return the corresponding second evidence number to each sample traceability key node.

[0122] The sample data full-process traceability unit 605 is configured to obtain the corresponding evidence number when receiving the artificial intelligence sample data traceability request, perform on-chain evidence collection based on the evidence number, the first evidence number and the second evidence number to obtain the evidence content data, and return the evidence content data to the user.

[0123] In some embodiments, the sample data object generation unit 601 is further configured to: extract metadata information of the artificial intelligence sample data, and generate a metadata object based on the metadata information; and generate a sample data object based on the metadata object and the artificial intelligence sample data.

[0124] In some embodiments, the sample data fingerprint generation unit 602 is further configured to: generate a data block according to the sample data fingerprint and the sample data object; perform integrity verification on the data block based on the blockchain smart contract, and in response to passing the integrity verification, add the data block to the blockchain ledger.

[0125] In some embodiments, the sample data full-process tracing unit 605 is further configured to: generate a third data object based on the forensic content data, and return the third data object to the user.

[0126] In some embodiments, key links include an upload link and a distribution link, and the flow order is upload first and then distribution. Key nodes for sample traceability include a collection terminal-level sample library, a business-level sample library, and a headquarters-level sample library. The priority includes the priority in the upload link and the priority in the distribution link, wherein the priority in the upload link is that the priority of the collection terminal-level sample library is greater than the priority of the business-level sample library, which is greater than the priority of the headquarters-level sample library; and the priority in the distribution link is that the priority of the headquarters-level sample library is greater than the priority of the business-level sample library; and the sample data flow tracking unit 604 is further configured to: in response to the collection terminal-level sample library completing the addition of the sample data fingerprint and the sample data object to the blockchain ledger, based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the first evidence number, the collection terminal-level sample library, the business-level sample library, the upload link and the current time, generate a corresponding data object B, and pass the business The business-level sample library adds the data object B to the blockchain ledger and generates a corresponding second evidence number No2; in response to the business-level sample library completing the addition of the data object B to the blockchain ledger, based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No2, the business-level sample library, the headquarters-level sample library, the upload link and the current time, the corresponding data object B' is generated, and the data object B' is added to the blockchain ledger through the headquarters-level sample library and the corresponding second evidence number No3 is generated; in response to the headquarters-level sample library completing the addition of the data object B' to the blockchain ledger, based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No3, the headquarters-level sample library, the business-level sample library, the distribution link and the current time, the corresponding data object B'' is added to the blockchain ledger through the business-level sample library and the corresponding second evidence number No4 is generated.

[0127] In some embodiments, the sample data full-process traceability unit 605 is further configured to: match the evidence number with the first evidence number and each second evidence number, and query the corresponding evidence content data in the blockchain ledger based on the matched first evidence number or second evidence number; if the queried evidence content data also contains the evidence number, continue to query the corresponding evidence content data based on the contained evidence number until the queried evidence content data no longer contains the evidence number, and then summarize all the queried evidence content data according to the time series to obtain the evidence content data.

[0128] In some embodiments, the blockchain-based artificial intelligence sample data traceability device also includes Figure 6The smart contract execution unit not shown in the figure is configured to automatically execute the smart contract to determine whether the data flow is reasonable when data is circulated at each key node and each key link of the sample traceability in the entire life cycle of the artificial intelligence sample data. When the data flow is unreasonable, the corresponding data flow is not executed and an error message is given.

[0129] It should be noted that the blockchain-based artificial intelligence sample data traceability method and the blockchain-based artificial intelligence sample data traceability device of the present application have a corresponding relationship in terms of specific implementation content, so the repeated content will not be explained again.

[0130] Figure 7 An exemplary system architecture 700 is shown to which the blockchain-based artificial intelligence sample data tracing method or blockchain-based artificial intelligence sample data tracing device according to an embodiment of the present application can be applied.

[0131] like Figure 7 As shown, system architecture 700 may include terminal devices 701, 702, 703, network 704 and server 705. Network 704 is used to provide a medium for communication links between terminal devices 701, 702, 703 and server 705. Network 704 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0132] The user can use the terminal devices 701, 702, 703 to interact with the server 705 through the network 704 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 701, 702, 703, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0133] Terminal devices 701, 702, and 703 can be various electronic devices that have a blockchain-based artificial intelligence sample data traceability processing screen and support web browsing, including but not limited to smartphones, tablet computers, laptops, desktop computers, etc.

[0134] Server 705 may be a server that provides various services, such as a background management server that provides support for artificial intelligence sample data generated by users using terminal devices 701 , 702 , and 703 (only as an example). The backend management server can generate a sample data object based on the artificial intelligence sample data when the generated artificial intelligence sample data is detected; encrypt the sample data object using a hash encryption algorithm to generate a sample data fingerprint, add the sample data fingerprint and the sample data object to the blockchain account book, and generate a first evidence number; determine the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data, and determine the priority of the sample traceability key nodes according to the flow sequence of the key links corresponding to the entire life cycle; generate each data object corresponding to the sample traceability key node according to the sample data fingerprint, the first evidence number, the key link, the flow sequence and the priority, add each data object to the blockchain account book according to the time sequence and generate each second evidence number, and return the corresponding second evidence number to each sample traceability key node; when receiving an artificial intelligence sample data traceability request, obtain the corresponding evidence number, perform on-chain evidence based on the evidence number, the first evidence number and the second evidence number to obtain evidence content data, and return the evidence content data to the user. This application introduces the first evidence number and the second evidence number, and traces the artificial intelligence sample data based on the blockchain, which can enhance the transparency of the flow of artificial intelligence sample data, improve the quality of artificial intelligence sample data, improve the efficiency and accuracy of data traceability, and improve the training effect of related models. By encrypting the sample data objects with a hash encryption algorithm, the compliance management and control of sample use can be strengthened, and the security of core confidential data can be ensured while sharing resources, thereby improving data security.

[0135] It should be noted that the blockchain-based artificial intelligence sample data traceability method provided in the embodiment of the present application is generally executed by the server 705, and accordingly, the blockchain-based artificial intelligence sample data traceability device is generally set in the server 705.

[0136] It should be understood that Figure 7 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to the implementation requirements.

[0137] Reference below Figure 8 , which shows a schematic diagram of the structure of a computer system 800 of a terminal device suitable for implementing an embodiment of the present application. Figure 8 The terminal device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0138] like Figure 8As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage part 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the computer system 800 are also stored. The CPU 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0139] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed, so that a computer program read therefrom is installed into the storage section 808 as needed.

[0140] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above-mentioned functions defined in the system of the present application are executed.

[0141] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. Computer-readable storage media may include, for example, but are not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0142] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0143] The units involved in the embodiments described in the present application may be implemented by software or hardware. The units described may also be set in a processor, for example, it may be described as: a processor includes a sample data object generation unit, a sample data fingerprint generation unit, a priority determination unit, a sample data flow tracking unit, and a sample data full-process traceability unit. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0144] As another aspect, the present application further provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The computer-readable medium carries one or more programs. When the one or more programs are executed by a device, the device generates a sample data object based on the artificial intelligence sample data when the generated artificial intelligence sample data is detected; the sample data object is encrypted using a hash encryption algorithm to generate a sample data fingerprint, the sample data fingerprint and the sample data object are added to the blockchain account book, and a first evidence number is generated; the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data are determined, and the priority of the sample traceability key nodes is determined according to the flow sequence of the key links corresponding to the entire life cycle; according to the sample data fingerprint, the first evidence number, the key link, the flow sequence and the priority, each data object corresponding to the sample traceability key node is generated, each data object is added to the blockchain account book according to the time sequence and each second evidence number is generated, and the corresponding second evidence number is returned to each sample traceability key node; when receiving an artificial intelligence sample data traceability request, the corresponding evidence number is obtained, and on-chain evidence is obtained based on the evidence number, the first evidence number and the second evidence number to obtain evidence content data, and the evidence content data is returned to the user.

[0145] The computer program product of the present application includes a computer program, which, when executed by a processor, implements the blockchain-based artificial intelligence sample data traceability method in the embodiment of the present application.

[0146] According to the technical solution of the embodiment of the present application, by introducing the first evidence number and the second evidence number and tracing the artificial intelligence sample data based on the blockchain, the transparency of the flow of artificial intelligence sample data can be enhanced, the quality of artificial intelligence sample data can be improved, the efficiency and accuracy of data traceability can be improved, and the training effect of related models can be improved. In addition, by encrypting the sample data object with a hash encryption algorithm, the compliance management and control of sample use can be strengthened, and the security of core confidential data can be ensured while sharing resources, thereby improving data security.

[0147] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A blockchain-based artificial intelligence sample data traceability method, characterized in that: include: Upon detecting the generated artificial intelligence sample data, generating a sample data object based on the artificial intelligence sample data; Encrypting the sample data object using a hash encryption algorithm to generate a sample data fingerprint, adding the sample data fingerprint and the sample data object to a blockchain account book, and generating a first evidence storage number; Determine the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data, and determine the priority of the sample traceability key nodes according to the flow order of the key links corresponding to the entire life cycle; According to the sample data fingerprint, the first evidence number, the key link, the flow order and the priority, generate each data object corresponding to the sample traceability key node, add each data object to the blockchain account book according to the time sequence and generate each second evidence number, and return the corresponding second evidence number to each sample traceability key node; When a request for tracing the artificial intelligence sample data is received, the corresponding evidence number is obtained, and on-chain evidence is collected based on the evidence number, the first evidence number, and the second evidence number to obtain evidence content data, and the evidence content data is returned to the user.

2. The method according to claim 1, characterized in that: The generating a sample data object based on the artificial intelligence sample data includes: Extracting metadata information of the artificial intelligence sample data, and generating a metadata object according to the metadata information; A sample data object is generated based on the metadata object and the artificial intelligence sample data.

3. The method according to claim 1, characterized in that The adding the sample data fingerprint and the sample data object to the blockchain ledger includes: Generate a data block according to the sample data fingerprint and the sample data object; The data block is integrity verified based on the blockchain smart contract, and in response to passing the integrity verification, the data block is added to the blockchain ledger.

4. The method according to claim 1, characterized in that: The returning the forensic content data to the user includes: Based on the forensic content data, a third data object is generated, and the third data object is returned to the user.

5. The method according to claim 1, characterized in that The key links include an upload link and a distribution link, the flow order is upload first and then distribution, the sample traceability key nodes include a collection terminal-level sample library, a business-level sample library and a headquarters-level sample library, the priority includes a priority in the upload link and a priority in the distribution link, wherein the priority in the upload link is that the priority of the collection terminal-level sample library is greater than the priority of the business-level sample library, which is greater than the priority of the headquarters-level sample library, and the priority in the distribution link is that the priority of the headquarters-level sample library is greater than the priority of the business-level sample library; and The method of generating data objects corresponding to the key nodes of the sample traceability according to the sample data fingerprint, the first evidence number, the key links, the flow order and the priority, adding the data objects to the blockchain account book according to the time sequence and generating the second evidence numbers includes: In response to the acquisition terminal-level sample library completing the addition of the sample data fingerprint and the sample data object to the blockchain account book, a corresponding data object B is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the first evidence number, the acquisition terminal-level sample library, the business-level sample library, the upload link and the current time, and the data object B is added to the blockchain account book through the business-level sample library and a corresponding second evidence number No2 is generated; In response to the business-level sample library completing the addition of the data object B to the blockchain ledger, a corresponding data object B' is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No2, the business-level sample library, the headquarters-level sample library, the upload link and the current time, and the data object B' is added to the blockchain ledger through the headquarters-level sample library and a corresponding second evidence number No3 is generated; In response to the headquarters-level sample library completing the addition of the data object B' to the blockchain ledger, a corresponding data object B'' is generated based on the metadata information of the artificial intelligence sample data, the sample data fingerprint, the second evidence number No3, the headquarters-level sample library, the business-level sample library, the distribution link and the current time. The data object B'' is added to the blockchain ledger through the business-level sample library and a corresponding second evidence number No4 is generated.

6. The method according to claim 1, characterized in that The on-chain evidence collection based on the evidence storage number, the first evidence storage number and the second evidence storage number to obtain evidence content data includes: The evidence number is matched with the first evidence number and each of the second evidence numbers, and the corresponding evidence content data is queried in the blockchain ledger based on the matched first evidence number or second evidence number. If the queried evidence content data also contains the evidence number, the corresponding evidence content data is continued to be queried based on the contained evidence number until the queried evidence content data no longer contains the evidence number, and all the queried evidence content data are summarized in time series to obtain the evidence content data.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: When data flows at each key sample traceability node and each key link in the entire life cycle of the artificial intelligence sample data, the smart contract is automatically executed to determine whether the data flow is reasonable. When the data flow is unreasonable, the corresponding data flow is not executed and an error message is given.

8. An artificial intelligence sample data tracing device based on blockchain, characterized in that: include: a sample data object generation unit configured to generate a sample data object based on the artificial intelligence sample data when the generated artificial intelligence sample data is detected; A sample data fingerprint generating unit is configured to encrypt the sample data object using a hash encryption algorithm to generate a sample data fingerprint, add the sample data fingerprint and the sample data object to a blockchain account book, and generate a first evidence storage number; A priority determination unit is configured to determine the sample traceability key nodes corresponding to the entire life cycle of the artificial intelligence sample data, and determine the priority of the sample traceability key nodes according to the flow order of the key links corresponding to the entire life cycle; The sample data circulation tracking unit is configured to generate each data object corresponding to the sample traceability key node according to the sample data fingerprint, the first evidence number, the key link, the circulation order and the priority, add each data object to the blockchain account book according to the time sequence and generate each second evidence number, and return the corresponding second evidence number to each sample traceability key node; The sample data full-process traceability unit is configured to obtain the corresponding evidence number when receiving an artificial intelligence sample data traceability request, perform on-chain evidence collection based on the evidence number, the first evidence number and the second evidence number to obtain evidence content data, and return the evidence content data to the user.

9. An artificial intelligence sample data traceability electronic device based on blockchain, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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