Data use control method, device, equipment and product

Abstract

The invention provides a data use control method, device, equipment and product, which are applied to a computing platform and comprise the following steps: acquiring to-be-computed data on a block chain and an executable computing contract of the to-be-computed data; wherein the executable calculation contract is generated by signing provided data information for calculation of the to-be-calculated data according to a plurality of participants of the to-be-calculated data; obtaining a calculation result of the to-be-calculated data according to the to-be-calculated data and the data information; verifying the calculation result and the data information, and generating a contract execution verification result; and when the contract execution verification result is that verification is passed, uploading the calculation result to the block chain for storage. According to the invention, finer-grained management and control of the privacy calculation process are realized, the data provider can accurately control the use of the acquired data by the demander in real time, and the use security and traceability of the data in the privacy calculation process are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of data circulation technology, and in particular to a data usage control method, apparatus, equipment and product. Background Technology

[0002] Privacy-preserving computation is a set of techniques for performing data analysis computations while protecting the data itself from external disclosure. Its goal is to protect data privacy while allowing data to be computed and analyzed by multiple parties without revealing sensitive information. It allows multiple participants to collaboratively complete a computational task while protecting their respective data privacy, thus achieving the goal of data being "usable but invisible." The mainstream technical approaches to privacy-preserving computation include: Multi-Party Secure Computation (MPC), Privacy-Preserving Intersection (PSI), Profound Identification Query (PIR), and Federated Learning (FL). Multi-Party Secure Computation is a branch of cryptography that distributes computation among multiple participants, allowing them to collaboratively complete computational tasks without revealing their individual private data. However, existing technical implementations, even if the data is usable but invisible, do not equate to data being controllable and measurable. For example, we might use privacy-preserving computation techniques to convert data into ciphertext, then have the participants perform collaborative computations, and finally produce a result. But what exactly is being computed? How many times was the computation performed? Is it a joint statistical calculation or a joint modeling calculation? These are difficult to control. Data providers may not know what calculations the data requester performs after acquiring the data. They need to control and authorize what their data can be used to calculate—whether it's a previously agreed-upon function or an arbitrarily generated function. Therefore, data being usable but invisible is not entirely equivalent to data being controllable and measurable. Summary of the Invention

[0003] The purpose of this invention is to provide a data usage control method, device, equipment, and product to solve the problem in the prior art where data is available but not visible in multi-party secure computation, resulting in data that is neither controllable nor measurable.

[0004] To achieve the above objectives, embodiments of the present invention provide a data usage control method, which is applied to a computing platform and includes:

[0005] Obtain the data to be computed on the blockchain and the executable computation contract for the data to be computed; wherein, the executable computation contract is generated by signing the data information provided for computing the data to be computed by multiple participants in the data to be computed.

[0006] Based on the data to be calculated and the data information, the calculation result of the data to be calculated is obtained;

[0007] The calculation results and the data information are verified to generate a contract execution verification result;

[0008] If the contract execution verification result is successful, the calculation result will be uploaded to the blockchain for storage.

[0009] Optionally, in the method, the data information includes first data information of the data to be calculated, second data information provided by the data provider, and / or third data information provided by the data requester;

[0010] The participating parties include the data provider and the data requester.

[0011] Optionally, in the method, the first data information includes one or more of the following:

[0012] The identity identifier of the data to be calculated;

[0013] The data type of the data to be calculated;

[0014] The data dictionary of the data to be calculated;

[0015] The identity identifier of the computation operator to be used;

[0016] Number of requirement calculations;

[0017] The number of times the data to be calculated is used;

[0018] The validity period of the data to be calculated.

[0019] Optionally, in the method, the second data information includes one or more of the following:

[0020] The identity identifier of the data provider;

[0021] The signature information of the data provider.

[0022] Optionally, in the method, the third data information includes one or more of the following:

[0023] The identity identifier of the data requester;

[0024] The signature information of the data requester.

[0025] Optionally, the method further includes:

[0026] Obtain resource information and a list of computational operator libraries for the data resources;

[0027] Determine the data to be computed in the data resource, and the computational operators to be used in the computational operator library list;

[0028] The computational contract to be signed is obtained based on the data to be calculated and the computational operator to be used.

[0029] After the participating parties sign the computation contract to be signed, the executable computation contract is generated.

[0030] Optionally, the method, wherein verifying the calculation result with the data information to generate a contract execution result, includes:

[0031] The data information is collected through sensors;

[0032] The data information is verified against the calculation results by the metric engine to generate the contract execution result.

[0033] Optionally, the method further includes:

[0034] If the contract execution result is verified as successful, the calculation result is output to the participating party.

[0035] Optionally, the method further includes, after obtaining the calculation result of the data to be calculated, the method further comprising:

[0036] The calculation results are sent to the data regulator.

[0037] The regulatory authority obtains the data and verifies the calculation results using digital regulatory rules.

[0038] To achieve the above objectives, embodiments of the present invention provide a data usage control device, which is applied to a computing platform and includes:

[0039] The first acquisition module is used to acquire the data to be calculated on the blockchain and the executable computing contract of the data to be calculated; wherein, the executable computing contract is generated by signing the data information provided for computing the data to be calculated by multiple participants in the data to be calculated.

[0040] The first processing module is used to obtain the calculation result of the data to be calculated based on the data to be calculated and the data information;

[0041] The first generation module is used to verify the calculation results and the data information, and generate a contract execution verification result;

[0042] The second processing module is used to upload the calculation result to the blockchain for storage if the contract execution verification result is successful.

[0043] To achieve the above objectives, embodiments of the present invention provide an electronic device, including: a transceiver, a processor, a memory, and a program or instructions stored in the memory and executable on the processor; wherein, when the processor executes the program or instructions, it implements the data usage control method described above.

[0044] To achieve the above objectives, embodiments of the present invention provide a readable storage medium having a program or instructions stored thereon, wherein the program or instructions, when executed by a processor, implement the steps of the data usage control method described above.

[0045] To achieve the above objectives, embodiments of the present invention provide a computer program product, which includes computer instructions that, when executed by a processor, implement the steps of the data usage control method described above.

[0046] The beneficial effects of the above-described technical solution of the present invention are as follows:

[0047] In this embodiment of the invention, the calculation result is obtained based on the data to be calculated obtained from the blockchain and the corresponding executable calculation contract. The data information of the calculation result and the data to be calculated is verified. If the verification is successful, the calculation result is uploaded to the blockchain for storage. This enables more granular control over the privacy computing process, allowing data providers to accurately and in real time control the use of the acquired data by the requesting party, and effectively improves the security and traceability of data use in the privacy computing process. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the data usage control method according to an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of the participants in the data usage control method described in an embodiment of the present invention;

[0050] Figure 3 This is one of the flowcharts of the data usage control method described in this embodiment of the invention;

[0051] Figure 4 This is a second flowchart of the data usage control method according to an embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram of the data usage control device according to an embodiment of the present invention. Detailed Implementation

[0053] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0054] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of the invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0055] In various embodiments of the present invention, it should be understood that the sequence number of each process described below does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0056] In addition, the terms "system" and "network" are often used interchangeably in this article.

[0057] In the embodiments provided in this application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0058] For ease of understanding, the following describes some aspects of the embodiments of the present invention:

[0059] like Figure 1 As shown, an embodiment of the present invention provides a data usage control method, which is applied to a computing platform and includes:

[0060] S10, Obtain the data to be computed on the blockchain and the executable computing contract for the data to be computed; wherein, the executable computing contract is generated by signing the data information provided for computing the data to be computed by multiple participants in the data to be computed.

[0061] It should be noted that, as Figure 2 As shown, in step 2, contract code and on-chain data are obtained through the privacy computing gateway. In step 3, contract execution is sent to the computing platform, i.e., the data to be computed on the blockchain and the executable computing contract for the data to be computed are obtained. The executable computing contract is a smart contract. In data circulation, the smart contract can automatically execute data exchange and transaction terms, reducing the risk of human intervention. The four core capabilities of privacy computing are: secure intersection, concealed query, multi-party secure computation, and joint modeling. The executable computing contract is designed to record relevant information of multiple participating parties during the privacy computing process.

[0062] S20, based on the data to be calculated and the data information, obtain the calculation result of the data to be calculated;

[0063] It should be noted that, as Figure 2 As shown, the computing platform executes a computing contract through a privacy computing engine, and obtains the computing result of the data to be computed based on the data to be computed and the data information. S30: The computing result and the data information are verified to generate a contract execution verification result;

[0064] It should be noted that, as Figure 4 As shown, a data sandbox environment is set up within the computing platform. In step A5, the calculation results are verified against the executable computing contract collected in step A4, that is, the calculation results and the data information are verified to generate a contract execution verification result.

[0065] S40, if the contract execution verification result is successful, the calculation result is uploaded to the blockchain for storage;

[0066] It should be noted that, as Figure 3 As shown, in step 4, the computing platform returns the execution result to the privacy computing gateway. In step 5, it initiates the action of uploading the execution result to the blockchain, that is, if the contract execution verification result is verified, the computing result is uploaded to the blockchain for storage.

[0067] In this embodiment, the calculation result is obtained based on the data to be calculated obtained from the blockchain and the corresponding executable calculation contract. The calculation result is verified against the data information of the data to be calculated. If the verification is successful, the calculation result is uploaded to the blockchain for storage. This enables more granular control over the privacy computing process, allowing data providers to accurately and in real time control the use of the acquired data by data requesters, effectively improving the security and traceability of data use during the privacy computing process.

[0068] To prevent tampering with the executable computing contract, blockchain technology is used to ensure the security and traceability of the entire privacy computing process. After the executable computing contract is signed, the data to be computed and the executable computing contract including the data information are stored on the blockchain. The executable computing contract is then sent to the computing platform for execution. After execution, the user can obtain the computation result by accessing the privacy computing gateway. Simultaneously, the computation result is also uploaded to the blockchain using encryption or hashing methods and stored encrypted through the blockchain.

[0069] Optionally, in the method, the data information includes first data information of the data to be calculated, second data information provided by the data provider, and / or third data information provided by the data requester;

[0070] The participating parties include the data provider and the data requester.

[0071] In this embodiment, such as Figure 2 As shown, the participants include the data provider and the data requester, and a regulator can be set to oversee the computation results. The data provider provides the data (and may also include an algorithm provider), the regulator controls privacy-preserving computation before, during, and after the computation, and the operator provides the computation platform.

[0072] Optionally, in the method, the first data information includes one or more of the following:

[0073] The identity identifier of the data to be calculated;

[0074] The data type of the data to be calculated;

[0075] The data dictionary of the data to be calculated;

[0076] The identity identifier of the computation operator to be used;

[0077] Number of requirement calculations;

[0078] The number of times the data to be calculated is used;

[0079] The validity period of the data to be calculated.

[0080] Optionally, in the method, the second data information includes one or more of the following:

[0081] The identity identifier of the data provider;

[0082] The signature information of the data provider.

[0083] Optionally, in the method, the third data information includes one or more of the following:

[0084] The identity identifier of the data requester;

[0085] The signature information of the data requester.

[0086] In this embodiment, the executable computing contract is a contract form based on a computer protocol, which is disseminated, verified, and executed in an information-based manner, supporting trusted transactions without the need for third parties and ensuring the traceability and irreversibility of transactions. Figure 4As shown, the computation contract template structure is designed as follows. The core information (i.e., data information) includes: data resource identity identifier (i.e., the identity identifier of the data to be computed), identity identifiers of each participant (i.e., the identity identifier of the data requester and the identity identifier of the data requester), computation operator identity identifier (i.e., the identity identifier of the computation operator to be used), computation count (i.e., the required computation count), data resource usage count (i.e., the usage count of the data to be computed), data resource usage validity period (i.e., the usage validity period of the data to be computed), and signature information of each participant (i.e., the signature information of the data provider and the signature information of the data requester).

[0087] The code for the data information in the executable computation contract is as follows:

[0088] #Computation Contract

[0089] calculateContract=$( / opt / confidential-containers / bin / dataSandbox.py\

[0090] --resoIDs"${resource_ids...}"\ #Data Resource IDs

[0091] --participantIDs"${participant_ids...}"\ #IDs of each participant

[0092] --calAlgos"${calculate_algorithms...}"\ #Calculation operator ID

[0093] --calNum"${calculate_number}" #Calculate the number of times

[0094] --resoUseNum"${resource_use_number}" #Number of times data resources are used

[0095] --resoExpire"${resource_expire}" # Data resource usage validity period

[0096] --partSigns"${participants_signitures...}"\ #Participant signature information

[0097] ).

[0098] Optionally, the method further includes:

[0099] Obtain resource information and a list of computational operator libraries for the data resources;

[0100] Determine the data to be computed in the data resource, and the computational operators to be used in the computational operator library list;

[0101] The computational contract to be signed is obtained based on the data to be calculated and the computational operator to be used.

[0102] After the participating parties sign the computation contract to be signed, the executable computation contract is generated.

[0103] In this embodiment, such as Figure 4 As shown, in step A1, the data provider provides resource information and a list of computational operators, i.e., obtains the resource information and the list of computational operators for the data resources; in step A2, the data requester confirms the data to be computed and the operators to be used, i.e., determines the data to be computed in the data resources and the computational operators to be used in the list of computational operators; in step A3, the participants sign, i.e., after multiple participants sign the computational contract to be signed, the executable computational contract is generated and introduced into the data sandbox environment for verification.

[0104] After all participating parties log into the platform operator's computing platform, the data provider provides a list of executable computing operator libraries according to the computing contract template. These libraries include machine learning algorithm libraries, basic MPC operator libraries, encryption algorithm libraries, and some data preprocessing component libraries. It is important to note that the data provider only provides partial information about its data, including the data type and data dictionary; the original data is not visible. The data requester specifies the data resources and computing information they wish to use, including: the identity of the computing operator to be used, the required number of calculations, the number of times the data to be calculated will be used, and the validity period of the data to be calculated. Once all information for the computing contract to be signed is clear, all participating parties jointly sign to form the formal executable computing contract. Afterward, the executable computing contract enters a data sandbox environment and is stored in the sandbox database.

[0105] Data sandboxes create an application-layer isolated environment, allowing data users to analyze and process data within a secure and controlled area. This effectively prevents data leaks and misuse, ensuring data security. The trust measurement capabilities of the data sandbox guarantee that all data requesters strictly adhere to the computational contract during actual calculations. A data sandbox is a security mechanism that provides an isolated environment for data processing and analysis.

[0106] Optionally, the method, wherein verifying the calculation result with the data information to generate a contract execution result, includes:

[0107] The data information is collected through sensors;

[0108] The data information is verified against the calculation results by the metric engine to generate the contract execution result.

[0109] In this embodiment, such as Figure 4 As shown, in step A4, the data information is collected by a sensor. The sensor is responsible for capturing important operational data or status information in the system, such as system calls, key operations, and external inputs, and transmits this information to the measurement engine. In step A5, the measurement engine verifies the data information against the calculation results to generate the contract execution result. The measurement engine processes the data captured by the sensor, executes a predefined measurement algorithm and verification process, and generates a measurement value using a hash function. In steps A4 and A5, the data information is stored in a reference database. This reference database stores trusted measurement benchmark values ​​or signatures, which are compared with the results generated by the measurement engine to verify the credibility of the current system state.

[0110] Optionally, the method further includes:

[0111] If the contract execution result is verified as successful, the calculation result is output to the participating party.

[0112] In this embodiment, the decision-making and control module within the data sandbox environment of the computing platform makes a decision on whether to allow the system to continue running or perform certain operations based on the contract execution result. Specifically, if the contract execution result passes verification, the calculation result is output to the participating party. After the computing requirement enters the data sandbox environment, the sensors collect important operational data and transmit it to the measurement engine. The measurement engine calculates the measurement value and compares it with the key information of the executable computing contract (i.e., the data information) previously stored in the database. If the verification is successful, the calculation result is output from the sandbox and returned to the participating party; if the verification fails, the calculation result is not returned.

[0113] Optionally, the method further includes, after obtaining the calculation result of the data to be calculated, the method further comprising:

[0114] The calculation results are sent to the data regulator.

[0115] The regulatory authority obtains the data and verifies the calculation results using digital regulatory rules.

[0116] In this embodiment, such as Figure 2As shown, the data regulator verifies the calculation results using digital regulatory rules to obtain the regulatory results. Digital regulatory rules transform regulatory rules into executable algorithmic logic. However, since the data being processed is encrypted text, regulatory rules need to be run on the encrypted text. These regulatory rules are abstracted into an algorithm, parsed into corresponding algorithmic logic, and then run on the encrypted text to see if they meet the regulatory requirements. First, the calculation results of the encrypted text need to be obtained, and then used as input parameters into the algorithmic model abstracted from the regulatory rules. The abstracted regulatory rules can evaluate the encrypted results from multiple dimensions to obtain the approximate range of the results. If the results do not exceed the regulatory range, the calculation results are allowed to be given to the data requester. If violations or abnormal numerical ranges are found, the delivery of the calculation results can be terminated at any time.

[0117] Here's an example: the regulatory rule simply checks if the input amount is greater than 10 million. This is an `if` statement. We convert this into an algorithmic logic, then input it into a cryptographic computing platform to verify whether the provided amount is indeed greater than 10 million. Whether the specific amount is 10 million, 20 million, or 9 million is confidential data; we don't know that. However, we can know whether it's greater than 10 million. This is one example of using digital regulatory rules on a cryptographic computing platform.

[0118] The following is the algorithmic logic for digital regulatory rules:

[0119]

[0120] like Figure 5 As shown, to achieve the above objectives, embodiments of the present invention provide a data usage control device, which is applied to a computing platform and includes:

[0121] The first acquisition module 501 is used to acquire the data to be calculated on the blockchain and the executable computing contract of the data to be calculated; wherein, the executable computing contract is generated by signing the data information provided for computing the data to be calculated by multiple participants in the data to be calculated.

[0122] The first processing module 502 is used to obtain the calculation result of the data to be calculated based on the data to be calculated and the data information;

[0123] The first generation module 503 is used to verify the calculation results and the data information, and generate a contract execution verification result;

[0124] The second processing module 504 is used to upload the calculation result to the blockchain for storage if the contract execution verification result is successful.

[0125] Optionally, in the aforementioned apparatus, the data information includes first data information of the data to be calculated, second data information provided by the data provider, and / or third data information provided by the data requester;

[0126] The participating parties include the data provider and the data requester.

[0127] Optionally, in the aforementioned apparatus, the first data information includes one or more of the following:

[0128] The identity identifier of the data to be calculated;

[0129] The data type of the data to be calculated;

[0130] The data dictionary of the data to be calculated;

[0131] The identity identifier of the computation operator to be used;

[0132] Number of requirement calculations;

[0133] The number of times the data to be calculated is used;

[0134] The validity period of the data to be calculated.

[0135] Optionally, in the aforementioned apparatus, the second data information includes one or more of the following:

[0136] The identity identifier of the data provider;

[0137] The signature information of the data provider.

[0138] Optionally, in the aforementioned apparatus, the third data information includes one or more of the following:

[0139] The identity identifier of the data requester;

[0140] The signature information of the data requester.

[0141] Optionally, the device further includes:

[0142] The second acquisition module is used to acquire resource information and a list of computational operators for data resources;

[0143] The first determining module is used to determine the data to be calculated in the data resources, and the computing operators to be used in the computing operator library list;

[0144] The third acquisition module is used to acquire the computing contract to be signed based on the data to be calculated and the computing operator to be used.

[0145] The second generation module is used to generate the executable computing contract after the multiple participating parties have signed the computing contract to be signed.

[0146] Optionally, in the aforementioned apparatus, the first generation module 503 includes:

[0147] The first processing unit is used to collect the data information through sensors;

[0148] The first generation unit is used to verify the data information with the calculation results through the metric engine and generate the contract execution result.

[0149] Optionally, the device further includes:

[0150] The first output module is used to output the calculation result to the participating party if the contract execution result is verified as successful.

[0151] Optionally, the device further includes:

[0152] The first sending module is used to send the calculation results to the data supervisor;

[0153] The fourth acquisition module is used to acquire the regulatory results of the data regulator verifying the calculation results through digital regulatory rules.

[0154] To achieve the above objectives, embodiments of the present invention provide an electronic device, including: a transceiver, a processor, a memory, and a program or instructions stored in the memory and executable on the processor; wherein, when the processor executes the program or instructions, it implements the data usage control method described above.

[0155] To achieve the above objectives, embodiments of the present invention provide a readable storage medium having a program or instructions stored thereon, wherein the program or instructions, when executed by a processor, implement the steps of the data usage control method described above.

[0156] To achieve the above objectives, embodiments of the present invention provide a computer program product, which includes computer instructions that, when executed by a processor, implement the steps of the data usage control method described above.

[0157] It should be further noted that the terminals described in this specification include, but are not limited to, smartphones, tablets, etc., and many of the functional components described are referred to as modules in order to emphasize the independence of their implementation.

[0158] In this embodiment of the invention, the module can be implemented in software so that it can be executed by various types of processors. For example, an identified executable code module may include one or more physical or logical blocks of computer instructions, which may be constructed as objects, procedures, or functions. Nevertheless, the executable code of the identified module does not need to be physically located together, but may include different instructions stored in different bits, which, when logically combined, constitute the module and achieve the module's intended purpose.

[0159] In practice, an executable code module can be a single instruction or many instructions, and can even be distributed across multiple different code segments, different programs, and across multiple memory devices. Similarly, operational data can be identified within the module and can be implemented in any suitable form and organized within any suitable type of data structure. This operational data can be collected as a single dataset or distributed across different locations (including different storage devices), and can exist, at least in part, solely as electronic signals within the system or network.

[0160] When a module can be implemented using software, considering the current level of hardware technology, modules that can be implemented in software can be implemented using hardware circuits by those skilled in the art to achieve the corresponding functions, without considering cost. These hardware circuits include conventional very-large-scale integrated circuits (VLSI) or gate arrays, as well as existing semiconductors such as logic chips and transistors, or other discrete components. Modules can also be implemented using programmable hardware devices, such as field-programmable gate arrays, programmable array logic, and programmable logic devices.

[0161] The exemplary embodiments described above are with reference to the accompanying drawings. Many different forms and embodiments are feasible without departing from the spirit and teachings of the invention. Therefore, the invention should not be construed as limiting the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided to make the invention complete and convey the scope of the invention to those skilled in the art. In these drawings, component dimensions and relative dimensions may be exaggerated for clarity. The terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. As used herein, unless clearly indicated otherwise, the singular forms “a,” “an,” and “the” are intended to include all such forms. It will be further understood that the terms “comprising” and / or “including”, when used in this specification, indicate the presence of the stated features, integers, steps, operations, components, and / or elements, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, and / or groups thereof. Unless otherwise indicated, when stated, a range of values ​​includes the upper and lower limits of the range and any subranges in between.

[0162] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A data usage control method, characterized in that, Applied to computing platforms, including: Obtain the data to be computed on the blockchain and the executable computation contract for the data to be computed; wherein, the executable computation contract is generated by signing the data information provided for computing the data to be computed by multiple participants in the data to be computed. Based on the data to be calculated and the data information, the calculation result of the data to be calculated is obtained; The calculation results and the data information are verified to generate a contract execution verification result; If the contract execution verification result is successful, the calculation result will be uploaded to the blockchain for storage.

2. The method according to claim 1, characterized in that, The data information includes first data information of the data to be calculated, second data information provided by the data provider, and / or third data information provided by the data requester; The participating parties include the data provider and the data requester.

3. The method according to claim 2, characterized in that, The first data information includes one or more of the following: The identity identifier of the data to be calculated; The data type of the data to be calculated; The data dictionary of the data to be calculated; The identity identifier of the computation operator to be used; Number of requirement calculations; The number of times the data to be calculated is used; The validity period of the data to be calculated.

4. The method according to claim 2, characterized in that, The second data information includes one or more of the following: The identity identifier of the data provider; The signature information of the data provider.

5. The method according to claim 2, characterized in that, The third data information includes one or more of the following: The identity identifier of the data requester; The signature information of the data requester.

6. The method according to claim 1, characterized in that, The method further includes: Obtain resource information and a list of computational operator libraries for the data resources; Determine the data to be computed in the data resource, and the computational operators to be used in the computational operator library list; The computational contract to be signed is obtained based on the data to be calculated and the computational operator to be used. After the participating parties sign the computation contract to be signed, the executable computation contract is generated.

7. The method according to claim 1, characterized in that, The calculation results are verified against the data information to generate the contract execution result, including: The data information is collected through sensors; The data information is verified against the calculation results by the metric engine to generate the contract execution result.

8. The method according to claim 1, characterized in that, The method further includes: If the contract execution result is verified as successful, the calculation result is output to the participating party.

9. The method according to claim 1, characterized in that, After obtaining the calculation result of the data to be calculated, the method further includes: The calculation results are sent to the data regulator. The regulatory authority obtains the data and verifies the calculation results using digital regulatory rules.

10. A data usage control device, characterized in that, Applied to computing platforms, including: The first acquisition module is used to acquire the data to be calculated on the blockchain and the executable computing contract of the data to be calculated; wherein, the executable computing contract is generated by signing the data information provided for computing the data to be calculated by multiple participants in the data to be calculated. The first processing module is used to obtain the calculation result of the data to be calculated based on the data to be calculated and the data information; The first generation module is used to verify the calculation results and the data information, and generate a contract execution verification result; The second processing module is used to upload the calculation result to the blockchain for storage if the contract execution verification result is successful.

11. An electronic device, comprising: A transceiver, a processor, a memory, and a program or instructions stored in the memory and executable on the processor; characterized in that, when the processor executes the program or instructions, it implements the data usage control method as described in any one of claims 1-9.

12. A readable storage medium having a program or instructions stored thereon, characterized in that, When the program or instructions are executed by the processor, they implement the steps of the data usage control method as described in any one of claims 1-9.

13. A computer program product, characterized in that, It includes computer instructions that, when executed by a processor, implement the steps of the data usage control method as described in any one of claims 1-9.

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