Data transaction methods and devices, storage media, electronic equipment

Abstract

This application discloses a data transaction method, apparatus, storage medium, and electronic device. The method includes: verifying a first dataset published by a first object, wherein the data verification includes at least data violation verification and data infringement verification; publishing the first dataset when it passes the data verification; and, in response to a data transaction request from a second object, adding a target data watermark to the first dataset to obtain a second dataset, and trading the second dataset to the second object, wherein the target data watermark includes at least the second object's first identity information. This application addresses the technical problem in related technologies where the lack of an effective management mechanism for data transactions leads to serious data infringement issues.

Description

Technical Field

[0001] This application relates to the field of data transaction technology, and more specifically, to a data transaction method and apparatus, storage medium, and electronic device. Background Technology

[0002] With the rapid development of the internet, an increasing amount of transaction data needs to be stored and distributed online. Because these transactions often contain significant social and economic value, the verification and traceability of transaction data are particularly important.

[0003] Traditional data trading technologies lack effective verification and traceability mechanisms for the traded datasets, allowing buyers to conduct unauthorized secondary transactions after purchasing the datasets, creating a vicious cycle. Repeated unauthorized secondary transactions of datasets significantly diminish their value, severely infringing on the interests of the dataset owners and ultimately hindering the healthy development of the entire data trading market.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This application provides a data transaction method and apparatus, storage medium, and electronic device to at least address the technical problem in the related art of lacking an effective management mechanism for data transactions, which leads to serious data infringement.

[0006] According to one aspect of the embodiments of this application, a data transaction method is provided, comprising: performing data verification on a first dataset published by a first object, wherein the data verification includes at least data violation verification and data infringement verification; publishing the first dataset when the first dataset passes the data verification; and, in response to a data transaction request from a second object, adding a target data watermark to the first dataset to obtain a second dataset, and trading the second dataset to the second object, wherein the target data watermark includes at least the first identity information of the second object.

[0007] Optionally, before performing data verification on the first dataset published by the first object, the method further includes: performing identity verification and credit verification on the first object; continuing to perform data verification on the first dataset when the first object passes the identity verification and credit verification; and prohibiting the first object from publishing the first dataset when the first object fails the identity verification and / or credit verification.

[0008] Optionally, identity verification includes: verifying the second identity information of the first object, which includes at least one of the following: the first object's username, telephone number, email address, ID card number, affiliated institution, and unified social credit code; credit verification includes: determining the first object's credit score, and if the credit score is higher than a first preset threshold, the first object is determined to have passed the credit verification, and if the credit score is not higher than the first preset threshold, the first object is determined to have failed the credit verification; wherein, the credit score is positively correlated with the number of successful data transactions by the first object, positively correlated with the number of data published by the first object that has passed data verification, negatively correlated with the number of illegal data published by the first object, and negatively correlated with the number of infringing data published by the first object.

[0009] Optionally, the data violation verification includes: checking whether the first dataset contains violation information; if so, the first dataset fails the data violation verification; if not, the first dataset passes the data violation verification. Violation information includes at least one of the following: illegal information, sensitive information, or classified information. The data quality of the first dataset is judged according to a data quality verification algorithm. If the quality judgment result is substandard, the first dataset fails the data violation verification; if the quality judgment result is satisfactory, the first dataset passes the data violation verification. The data infringement verification includes: checking whether the first dataset contains data watermark information; if so, the first dataset fails the data infringement verification; if not, the first dataset passes the data infringement verification. The data duplication verification is performed on the first dataset according to a data deduplication algorithm. If the duplication rate is higher than a second preset threshold, the first dataset fails the data infringement verification; if the duplication rate is not higher than the second preset threshold, the first dataset passes the data infringement verification.

[0010] Optionally, after verifying the first dataset published by the first object, the method further includes: if the first dataset fails the data violation verification, prohibiting the first object from publishing the first dataset, issuing a data violation warning message, recording the first object's behavior of publishing the violation data, and updating the first object's credit score; if the first dataset fails the data infringement verification, prohibiting the first object from publishing the first dataset, issuing a data infringement warning message, recording the first object's behavior of publishing the infringement data, and updating the first object's credit score.

[0011] Optionally, the first dataset is published, including: storing the first dataset in the transaction database; displaying a brief description of the contents of the first dataset; and displaying preset previewable content in the first dataset.

[0012] Optionally, a second dataset is obtained by adding a target data watermark to the first dataset, including: obtaining the first identity information of the second object; generating a binary target data watermark based on the first identity information and preset encryption information, saving the target data watermark to the database; and embedding the target data watermark into the target position in the first dataset to obtain the second dataset.

[0013] Optionally, trading the second dataset to the second object includes: adding the second object's first identity information to the data use authorization list corresponding to the first dataset; and sending the second dataset to the second object in response to the second object's data transfer request.

[0014] According to another aspect of the embodiments of this application, a data transaction apparatus is also provided, comprising: a data verification module, configured to perform data verification on a first dataset published by a first object, wherein the data verification includes at least data violation verification and data infringement verification; a data publishing module, configured to publish the first dataset when the first dataset passes the data verification; and a data transaction module, configured to, in response to a data transaction request from a second object, add a target data watermark to the first dataset to obtain a second dataset, and trade the second dataset to the second object, wherein the target data watermark includes at least the identity information of the second object.

[0015] According to another aspect of the embodiments of this application, an electronic device is also provided, the electronic device including: a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-described data transaction method through the computer program.

[0016] In this embodiment, a first dataset published by a first object is verified, including at least data violation verification and data infringement verification. When the first dataset passes verification, it is published. In response to a data transaction request from a second object, a target data watermark is added to the first dataset to obtain a second dataset, which is then traded to the second object. The target data watermark includes at least the second object's first identity information. By verifying the first dataset published by the first object, the legality and compliance of the dataset are ensured, preventing the publication of illegal datasets. Furthermore, adding a target data watermark to the published first dataset allows for traceability of the published dataset without compromising its quality, thus solving the technical problem in related technologies where the lack of an effective management mechanism for data transactions leads to serious data infringement issues. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 This is a flowchart of an optional data transaction method according to an embodiment of this application;

[0019] Figure 2 This is a schematic diagram of the structure of an optional data transaction device according to an embodiment of this application;

[0020] Figure 3 This is a schematic diagram of another optional data transaction device according to an embodiment of this application. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first," "second," etc., used in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. Example 1

[0023] According to an embodiment of this application, a data transaction method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0024] Figure 1 This is a flowchart illustrating an optional data transaction method according to an embodiment of this application, such as... Figure 1As shown, the method includes at least steps S102-S106, wherein:

[0025] Step S102: Perform data verification on the first dataset published by the first object, wherein the data verification includes at least data violation verification and data infringement verification.

[0026] In the technical solution provided by step S102 of the present invention, the first object may be, but is not limited to, users, accounts, etc. In order to clarify the ownership and copyright protection of the first dataset, it is necessary to verify the first dataset. Data verification can be divided into two verification methods according to whether the data is illegal or infringing, thereby improving the legality and compliance of the first dataset and preventing the first object from publishing an illegal first dataset, which would affect the healthy development of the data trading market.

[0027] Step S104: When the first dataset passes data verification, publish the first dataset.

[0028] In the technical solution provided by step S104 of the present invention, when the first dataset published by the first object passes the data verification, it indicates that the first dataset has no illegal or infringing content, and it can be published at this time. After the publication is completed, the first dataset is stored in the transaction database.

[0029] Step S106: In response to the data transaction request of the second object, a target data watermark is added to the first dataset to obtain a second dataset, and the second dataset is traded to the second object, wherein the target data watermark includes at least the first identity information of the second object.

[0030] In the technical solution provided in step S106 of the present invention, when the second object initiates a data transaction request for the first dataset, in order to prevent the second object from conducting unauthorized secondary transactions on the first dataset, a target data watermark is added to the first dataset, thereby effectively protecting the copyright interests of the first object.

[0031] In this embodiment, a first dataset published by a first object is verified, including at least data violation verification and data infringement verification. When the first dataset passes verification, it is published. In response to a data transaction request from a second object, a target data watermark is added to the first dataset to obtain a second dataset, which is then traded to the second object. The target data watermark includes at least the second object's first identity information. By verifying the first dataset published by the first object, the legality and compliance of the dataset are ensured, preventing the publication of illegal datasets. Furthermore, adding a target data watermark to the published first dataset allows for traceability of the published dataset without compromising its quality, thus solving the technical problem in related technologies where the lack of an effective management mechanism for data transactions leads to serious data infringement issues.

[0032] The method described in this embodiment will be further described below.

[0033] As an optional implementation, in the technical solution provided by step S102 of the present invention, before performing data verification on the first dataset published by the first object, the method further includes: performing identity verification and credit verification on the first object; continuing to perform data verification on the first dataset when the first object passes the identity verification and credit verification; and prohibiting the first object from publishing the first dataset when the first object fails the identity verification and / or credit verification.

[0034] In this embodiment, identity verification verifies the identity information of the first object, thereby enabling the traceability of the first published dataset, while credit verification verifies the credit record of the first object in the data trading market, thereby ensuring the legality of the first dataset published by the first target object.

[0035] Optionally, identity verification includes: verifying the second identity information of the first object, which includes at least one of the following: the first object's username, telephone number, email address, ID card number, affiliated institution, and unified social credit code; credit verification includes: determining the first object's credit score, and if the credit score is higher than a first preset threshold, the first object is determined to have passed the credit verification, and if the credit score is not higher than the first preset threshold, the first object is determined to have failed the credit verification; wherein, the credit score is positively correlated with the number of successful data transactions by the first object, positively correlated with the number of data published by the first object that has passed data verification, negatively correlated with the number of illegal data published by the first object, and negatively correlated with the number of infringing data published by the first object.

[0036] In this embodiment, the credit of the first object is calculated based on the historical behavior of the entity corresponding to the first object, such as a natural person or a legal person. The historical behavior includes: the number of data verified, the number of successful data transactions, the number of data violations, and the number of data infringements. Therefore, the credit score of the first object can be calculated using the following formula:

[0037]

[0038] The weighting coefficients 1, 2, and 3 can be set according to actual circumstances, and no specific restrictions are imposed here. Next, the relationship between the credit score and the first preset threshold is determined. If the credit score is greater than the first preset threshold, the first object is determined to have passed the credit verification, that is, the credit of the first object meets the data release standard.

[0039] Optionally, the data violation verification includes: checking whether the first dataset contains violation information; if so, determining that the first dataset has failed the data violation verification; if not, determining that the first dataset has passed the data violation verification. The violation information includes at least one of the following: illegal information, sensitive information, or classified information. The data quality of the first dataset is judged according to a data quality verification algorithm; if the quality judgment result is that the quality is substandard, determining that the first dataset has failed the data violation verification; if the quality judgment result is that the quality meets the standards, determining that the first dataset has passed the data violation verification.

[0040] Optionally, the data infringement verification includes: checking whether the first dataset contains data watermark information; if it does, the first dataset fails the data infringement verification; if it does not, the first dataset passes the data infringement verification; and performing data duplication verification on the first dataset according to the data deduplication algorithm. If the duplication rate is higher than a second preset threshold, the first dataset fails the data infringement verification; if the duplication rate is not higher than the second preset threshold, the first dataset passes the data infringement verification.

[0041] As an optional implementation, in the technical solution provided in step S102 of the present invention, after verifying the data of the first dataset published by the first object, the method further includes: when the first dataset fails the data violation verification, prohibiting the first object from publishing the first dataset, issuing a data violation warning message, recording the behavior of the first object in publishing the violation data, and updating the credit score of the first object; when the first dataset fails the data infringement verification, prohibiting the first object from publishing the first dataset, issuing a data infringement warning message, recording the behavior of the first object in publishing the infringement data, and updating the credit score of the first object.

[0042] In this embodiment, when the first dataset published by the first object fails the data violation verification, the publication request of the first object's violating first dataset needs to be rejected first, and a data violation report should be generated to inform the first object. Simultaneously, the first object's behavior of publishing violating data needs to be recorded, and the first object's credit score should be updated based on the violation behavior to ensure real-time monitoring of the first object's credit and prevent the first object from publishing violating datasets. Conversely, when the first dataset published by the first object fails the data infringement verification, the publication request of the first object's infringing first dataset needs to be rejected first, and a data infringement report should be generated to inform the first object. Simultaneously, the first object's behavior of publishing infringing data needs to be recorded, and the first object's credit score should be updated based on the infringing behavior to ensure real-time monitoring of the first object's credit and prevent the first object from publishing infringing datasets. Furthermore, based on the data watermark information and data deduplication algorithm embedded in the first dataset, a corresponding infringement warning report can be generated to notify the copyright holder of the first dataset, thereby protecting the copyright holder's rights.

[0043] In this embodiment of the application, the quality of the first dataset can be effectively improved by evaluating the quality of the first dataset using the above method.

[0044] As an optional implementation, in the technical solution provided by step S104 of the present invention, the method includes: storing the first dataset in the transaction database; displaying a brief description of the contents of the first dataset, and displaying preset previewable content in the first dataset.

[0045] In this embodiment, after the first dataset completes the publishing process, it can be stored in the transaction database and made visible to other objects. Other objects can purchase the first dataset through online payment or other methods. Before purchasing the first dataset, other objects can only preview its overview and preset previewable data information. After purchasing the first dataset, other users gain the right to use it, i.e., they can download and use it. The first data resource published by the first object can obtain all the revenue during the data transaction process, or obtain corresponding revenue according to the data tiers with the transaction platform. Furthermore, each dataset has one and only one owner.

[0046] As an optional implementation, in the technical solution provided by step S106 of the present invention, the method includes: obtaining the first identity information of the second object; generating a binary target data watermark based on the first identity information and preset encryption information, saving the target data watermark to a database; embedding the target data watermark into a target position in the first dataset to obtain a second dataset.

[0047] In this embodiment, a binary target data watermark is generated by combining the first identity information and encrypted information of the second object. This watermark is used to determine whether the first dataset is an unauthorized secondary transaction dataset. Since the target data watermark is binary data designed by an algorithm, it has the characteristics of high concealment, high security, detectability, high robustness, and high simulation. The target data watermark is then embedded into the target position of the first dataset to obtain a second dataset for data transactions. This allows for the verification of the copyright and traceability of the first dataset based on the target data watermark.

[0048] Optionally, when responding to a data transaction request from a second object, the data transaction request can be parsed to obtain a first dataset to be embedded. Then, a watermark generation algorithm obtains the first identity information of the second object, which includes at least one of the following: the second object's username, phone number, email address, ID number, affiliated organization, and unified social credit code, etc., without specific limitations. Next, the watermark generation algorithm generates actual binary data (i.e., encrypted information) to be embedded, and combines it with the first identity information to generate a target data watermark. Finally, the target data watermark is stored in a database for persistent storage.

[0049] Specifically, by generating a binary target data watermark from the first identity information and encrypted information of the second object, the data quality of the first dataset is not affected after the target data watermark is embedded in the first dataset. At the same time, the target data watermark does not have obvious data characteristics, so it is not easy to detect when the target data watermark is embedded in the first dataset. In addition, the target data watermark information used for embedding will not be destroyed when the first dataset is damaged in various ways, such as adding rows and columns, deleting or modifying some data in the dataset, and it can still be correctly extracted.

[0050] As an optional implementation, in the technical solution provided by step S106 of the present invention, the method includes: adding the first identity information of the second object to the data usage authorization list corresponding to the first dataset; and sending the second dataset to the second object in response to the data transaction download request of the second object.

[0051] In this embodiment, after obtaining the second dataset, the first identity information of the second object can be added to the resource authorization list corresponding to the first dataset, and the second dataset can be sent to the second object when the second object initiates a data transaction download request.

[0052] In this embodiment, by verifying the compliance and legality of the data, the legality and compliance of the first dataset published by the first object are guaranteed; by using a credit evaluation system related to historical behavior, the data quality of the first dataset published by the first object can be effectively improved, and illegal and non-compliant datasets in the data trading market can be reduced; by generating a binary target data watermark using the first identity information and encrypted information of the second object, the target data watermark has stronger security and concealment, and avoids the dataset being maliciously cycled. Example 2

[0053] According to an embodiment of this application, a data transaction apparatus for implementing the data transaction method in Embodiment 1 is also provided. Figure 2 This is a schematic diagram of the structure of an optional data transaction device according to an embodiment of this application, such as... Figure 2 As shown, the data trading device includes at least a data verification module 21, a data publishing module 22, and a data trading module 23, wherein:

[0054] The data verification module 21 is used to verify the first dataset published by the first object, wherein the data verification includes at least data violation verification and data infringement verification.

[0055] The first object can be, but is not limited to, users, accounts, etc. To clarify the ownership and copyright protection of the first dataset, the first dataset can be verified through the data verification module 21. Data verification can be divided into two verification methods based on whether the data is illegal or infringing, thereby improving the legality and compliance of the first dataset and preventing the first object from publishing illegal first datasets, which would affect the healthy development of the data trading market.

[0056] As an optional implementation method, Figure 3 Is Figure 2 Based on this, a more detailed structural diagram of the data transaction device is provided. Figure 3 It is understood that the data verification module 21 also includes a data violation verification module 211, which is used to check whether the first dataset contains violation information. If so, it is determined that the first dataset has failed the data violation verification; if not, it is determined that the first dataset has passed the data violation verification. The violation information includes at least one of the following: illegal information, sensitive information, or classified information. The data quality of the first dataset is judged according to the data quality verification algorithm. If the quality judgment result is that the quality is substandard, it is determined that the first dataset has failed the data violation verification; if the quality judgment result is that the quality is up to standard, it is determined that the first dataset has passed the data violation verification.

[0057] As another optional implementation method, by Figure 3It is known that the data verification module 21 also includes a data infringement verification module 212, which is used to check whether the first dataset contains data watermark information. If it does, the first dataset is determined to have failed the data infringement verification; if it does not, the first dataset is determined to have passed the data infringement verification. The data duplication algorithm is used to check the data duplication of the first dataset. If the duplication is higher than the second preset threshold, the first dataset is determined to have failed the data infringement verification; if the duplication is not higher than the second preset threshold, the first dataset is determined to have passed the data infringement verification.

[0058] Optionally, after verifying the first dataset published by the first object, the data verification module 21 may also prohibit the first object from publishing the first dataset, issue a data violation warning message, record the first object's behavior of publishing violation data, and update the first object's credit score when the first dataset fails the data violation verification; and prohibit the first object from publishing the first dataset, issue a data infringement warning message, record the first object's behavior of publishing infringing data, and update the first object's credit score when the first dataset fails the data infringement verification.

[0059] In this embodiment, when the first dataset published by the first object fails the data violation verification, the publication request for the violating first dataset by the first object needs to be rejected first, and a data violation report should be generated to inform the first object. Simultaneously, the first object's behavior of publishing violating data needs to be recorded, and the first object's credit score should be updated based on the violation behavior, thereby ensuring real-time monitoring of the first object's credit and preventing the first object from publishing violating datasets. Conversely, when the first dataset published by the first object fails the data infringement verification, the publication request for the infringing first dataset by the first object needs to be rejected first, and a data infringement report should be generated to inform the first object. Simultaneously, the first object's behavior of publishing infringing data needs to be recorded, and the first object's credit score should be updated based on the infringing behavior, thereby ensuring real-time monitoring of the first object's credit and preventing the first object from publishing infringing datasets. In this embodiment, evaluating the quality of the first dataset using the above method can effectively improve the data quality of the first dataset.

[0060] The data publishing module 22 is used to publish the first dataset when the first dataset passes data verification.

[0061] As an optional implementation, the data publishing module 22 can store the first dataset in the transaction database; display a brief description of the contents of the first dataset; and display preset previewable content in the first dataset.

[0062] In this embodiment, after the first dataset completes the publishing process, it can be stored in the transaction database and made visible to other objects. Other objects can purchase the first dataset through online payment or other methods. Before purchasing the first dataset, other objects can only preview its overview and preset previewable data information. After purchasing the first dataset, other users gain the right to use it, i.e., they can download and use it. The first data resource published by the first object can obtain all the revenue during the data transaction process, or obtain corresponding revenue according to the data tiers with the transaction platform. Furthermore, each dataset has one and only one owner.

[0063] As an optional implementation, the data publishing module 22 also includes a data watermarking module 221, which is used to obtain the first identity information of the second object; generate a binary target data watermark based on the first identity information and preset encryption information; save the target data watermark to the database; and embed the target data watermark into the target position in the first dataset to obtain the second dataset.

[0064] In this embodiment, a binary target data watermark is generated by combining the first identity information and encrypted information of the second object. This watermark is used to determine whether the first dataset is an unauthorized secondary transaction dataset. Since the target data watermark is binary data designed by an algorithm, it has the characteristics of high concealment, high security, detectability, high robustness, and high simulation. The target data watermark is then embedded into the target position of the first dataset to obtain a second dataset for data transactions. This allows for the verification of the copyright and traceability of the first dataset based on the target data watermark.

[0065] Optionally, when responding to a data transaction request from the second object, the data publishing module 22 can parse the data transaction request to obtain the first dataset to be embedded. Then, the watermark generation algorithm obtains the first identity information of the second object, which includes at least one of the following: the second object's username, phone number, email address, ID number, affiliated organization, and unified social credit code, etc., without specific limitations. Next, the watermark generation algorithm generates actual binary data (i.e., encrypted information) to be embedded, and combines it with the first identity information to generate a target data watermark. Finally, the target data watermark is stored in the database for persistent storage.

[0066] Specifically, by generating a binary target data watermark from the first identity information and encrypted information of the second object, the data quality of the first dataset is not affected after the target data watermark is embedded in the first dataset. At the same time, the target data watermark does not have obvious data characteristics, so it is not easy to detect when the target data watermark is embedded in the first dataset. In addition, the target data watermark information used for embedding will not be destroyed when the first dataset is damaged in various ways, such as adding rows and columns, deleting or modifying some data in the dataset, and it can still be correctly extracted.

[0067] The data transaction module 23 is used to respond to the data transaction request of the second object, add a target data watermark to the first dataset to obtain a second dataset, and trade the second dataset to the second object, wherein the target data watermark includes at least the identity information of the second object.

[0068] As an optional implementation, the data transaction module 23 can add the first identity information of the second object to the data usage authorization list corresponding to the first dataset; in response to the data transaction download request of the second object, it can send the second dataset to the second object.

[0069] In this embodiment, after obtaining the second dataset, the first identity information of the second object can be added to the resource authorization list corresponding to the first dataset, and the second dataset can be sent to the second object when the second object initiates a data transaction download request.

[0070] As an optional implementation, the data transaction device further includes an object verification module 24, which is used to perform identity verification and credit verification on the first object before the data verification module 21 performs data verification on the first dataset published by the first object; when the first object passes the identity verification and credit verification, the data verification on the first dataset continues; when the first object fails the identity verification and / or credit verification, the first object is prohibited from publishing the first dataset.

[0071] In this embodiment, identity verification verifies the identity information of the first object, thereby enabling the traceability of the first published dataset, while credit verification verifies the credit record of the first object in the data trading market, thereby ensuring the legality of the first dataset published by the first target object.

[0072] Optionally, identity verification includes: verifying the second identity information of the first object, which includes at least one of the following: the first object's username, telephone number, email address, ID card number, affiliated institution, and unified social credit code; credit verification includes: determining the first object's credit score, and if the credit score is higher than a first preset threshold, the first object is determined to have passed the credit verification, and if the credit score is not higher than the first preset threshold, the first object is determined to have failed the credit verification; wherein, the credit score is positively correlated with the number of successful data transactions by the first object, positively correlated with the number of data published by the first object that has passed data verification, negatively correlated with the number of illegal data published by the first object, and negatively correlated with the number of infringing data published by the first object.

[0073] In this embodiment, the credit of the first object is calculated based on the historical behavior of the entity corresponding to the first object, such as a natural person or a legal person. The historical behavior includes: the number of data verified, the number of successful data transactions, the number of data violations, and the number of data infringements. Therefore, the credit score of the first object can be calculated using the following formula:

[0074]

[0075] The weighting coefficients 1, 2, and 3 can be set according to actual circumstances, and no specific restrictions are imposed here. Next, the relationship between the credit score and the first preset threshold is determined. If the credit score is greater than the first preset threshold, the first object is determined to have passed the credit verification, that is, the credit of the first object meets the data release standard.

[0076] It should be noted that each module in the data trading device in this application embodiment corresponds one-to-one with each implementation step of the data trading method in embodiment 1. Since embodiment 1 has been described in detail, some details not shown in this embodiment can be referred to embodiment 1, and will not be elaborated further here. Example 3

[0077] According to an embodiment of this application, an electronic device is also provided, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the data transaction method of Embodiment 1 through the computer program.

[0078] Specifically, the processor is configured to execute the following steps via a computer program: performing data verification on a first dataset published by a first object, wherein the data verification includes at least data violation verification and data infringement verification; publishing the first dataset when the first dataset passes the data verification; and, in response to a data transaction request from a second object, adding a target data watermark to the first dataset to obtain a second dataset, and trading the second dataset to the second object, wherein the target data watermark includes at least the second object's first identity information.

[0079] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0080] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0081] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0082] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0084] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0085] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method of data transaction, characterized by, The method comprises: identity verification and credit verification of the first object, wherein the credit verification comprises: determining a credit score of the first object, if the credit score is higher than a first preset threshold, determining that the first object passes the credit verification, if the credit score is not higher than the first preset threshold, determining that the first object fails the credit verification, and the calculation formula of the credit score is: ， wherein the number of data passing the data verification, the number of successful data transactions, the number of violation data and the number of infringement data are historical behavior data of an entity corresponding to the first object, and the weight coefficients 1, 2 and 3 are preset values; when the first object passes the identity verification and the credit verification, performing data verification on a first data set published by the first object, wherein the data verification at least comprises data violation verification and data infringement verification; when the first data set passes the data verification, publishing the first data set; in response to a data transaction request of a second object, adding a target data watermark to the first data set to obtain a second data set, and trading the second data set to the second object, wherein the target data watermark at least includes first identity information of the second object.

2. The method of claim 1, wherein, The method further comprises: when the first object fails the identity verification and / or the credit verification, prohibiting the first object from publishing the first data set.

3. The method of claim 2, wherein, The method comprises: The identity verification comprises: verifying second identity information of the first object, and the second identity information at least includes one of the following: username, phone number, email, ID number, organization and organization unified social credit code of the first object.

4. The method of claim 1, wherein The data violation verification comprises: checking whether the first data set includes violation information, if yes, determining that the first data set fails the data violation verification, if not, determining that the first data set passes the data violation verification, wherein the violation information at least includes one of the following: illegal information, sensitive information, classified information; performing data quality determination on the first data set according to a data quality verification algorithm, if the quality determination result is that the quality is not up to standard, determining that the first data set fails the data violation verification, if the quality determination result is that the quality is up to standard, determining that the first data set passes the data violation verification; The data infringement verification comprises: checking whether the first data set includes data watermark information, if yes, determining that the first data set fails the data infringement verification, if not, determining that the first data set passes the data infringement verification; performing data redundancy verification on the first data set according to a data duplication algorithm, if the redundancy is higher than a second preset threshold, determining that the first data set fails the data infringement verification, if the redundancy is not higher than the second preset threshold, determining that the first data set passes the data infringement verification.

5. The method of claim 3, wherein, After data verification on the first data set published by the first object, the method further comprises: When the first data set fails to pass the data violation verification, the first object is prohibited from publishing the first data set, a data violation prompt information is sent out, the first object's behavior of publishing violation data is recorded, and the credit score of the first object is updated; When the first data set fails to pass the data infringement verification, the first object is prohibited from publishing the first data set, a data infringement prompt information is sent out, the first object's behavior of publishing infringement data is recorded, and the credit score of the first object is updated.

6. The method of claim 1, wherein, Publishing the first data set comprises: Storing the first data set to a transaction database; Displaying a content introduction of the first data set and displaying a preset previewable content in the first data set.

7. The method of claim 1, wherein, Adding a target data watermark to the first data set to obtain a second data set comprises: Obtaining the first identity information of the second object; Generating a binary target data watermark according to the first identity information and preset encryption information, and saving the target data watermark to a database; Embedding the target data watermark into a target position in the first data set to obtain the second data set.

8. The method of claim 1, wherein, Trading the second data set to the second object comprises: Adding the first identity information of the second object to a data use authorization list corresponding to the first data set; In response to a data download request of the second object, sending the second data set to the second object.

9. A data transaction apparatus, characterized by comprising: Comprise: A data verification module is configured to perform identity verification and credit verification on a first object, and perform data verification on a first data set published by the first object when the first object passes the identity verification and the credit verification, wherein the data verification comprises at least data violation verification and data infringement verification, the credit verification comprises determining a credit score of the first object, if the credit score is higher than a first preset threshold, determining that the first object passes the credit verification, if the credit score is not higher than the first preset threshold, determining that the first object fails to pass the credit verification, and the calculation formula of the credit score is: ， In the formula, the number of data passing the data verification, the number of successful data transactions, the number of violation data and the number of infringement data are historical behavior data of an entity corresponding to the first object, and the weight coefficient 1, the weight coefficient 2 and the weight coefficient 3 are preset values; A data publishing module is configured to publish the first data set when the first data set passes the data verification; A data transaction module is configured to add a target data watermark to the first data set to obtain a second data set in response to a data transaction request of a second object, and trade the second data set to the second object, wherein the target data watermark at least comprises identity information of the second object.

10. An electronic device, comprising: Comprise: A memory and a processor, wherein the memory has stored therein a computer program, and the processor is configured to execute the data transaction method of any one of claims 1 to 8 by the computer program.

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