Data processing method and device based on privacy computing, equipment and storage medium

Abstract

The embodiment of the invention discloses a data processing method and device based on privacy computing, equipment and a storage medium, and the method comprises the steps: obtaining a privacy computing task; calling a first target calculation method through the first application program interface, and performing privacy calculation on the first target data by using the first target calculation method to obtain a first privacy calculation result; calling a second target calculation method through the second application program interface, and performing privacy calculation on the second target data by using the second target calculation method to obtain a second privacy calculation result; determining a final privacy calculation result based on the first privacy calculation result and the second privacy calculation result; and carrying out user feedback based on a privacy calculation final result. According to the embodiment of the invention, privacy calculation methods of different manufacturers can be called through different application program interfaces to carry out privacy calculation according to the corresponding target data, so that interconnection and intercommunication of privacy calculation on a product integration level are realized.

Description

Technical Field

[0001] The present disclosure relates to the field of data security technology, and in particular to a data processing method and apparatus, device and storage medium based on privacy computing. Background Art

[0002] Privacy computing is a technology that closely combines data protection and computing, and aims to protect user privacy and data security during data processing and information sharing. With the increasing awareness of data privacy and security, the privacy computing industry is also developing rapidly. In the process of promoting the implementation of privacy computing, the products and solutions provided by different technology vendors also have large differences in design methods and functional implementation, making it impossible for data circulation participants who deploy different technology platforms to complete the same computing task across platforms.

[0003] In order to achieve data integration between multiple data partners, users often need to pay high communication costs to coordinate the selection and implementation of product solutions, and even have to deploy multiple sets of products to adapt one by one, resulting in duplicate construction of the system. Therefore, as a key technology to promote data sharing and integration across institutions, privacy computing is expected to become the infrastructure to support the data circulation industry. However, due to the high application cost, it is not conducive to the promotion and utilization of privacy computing technology. Therefore, it is particularly important to solve the technical barriers between different products and realize the interconnection and interoperability of privacy computing. Summary of the invention

[0004] The embodiments of the present disclosure provide a data processing method and apparatus, device and storage medium based on privacy computing to solve the above problems.

[0005] A first aspect of the embodiments of the present disclosure provides a data processing method based on privacy computing, including:

[0006] Acquire a privacy computing task, wherein the privacy computing task includes first target data and second target data required for privacy computing, and a first target computing method and a second target computing method required for privacy computing;

[0007] Calling the first target calculation method through a first application program interface corresponding to the first target calculation method, and performing privacy calculation on the first target data using the first target calculation method to obtain a first privacy calculation result;

[0008] Calling the second target calculation method through a second application program interface corresponding to the second target calculation method, and performing privacy calculation on the second target data using the second target calculation method to obtain a second privacy calculation result;

[0009] Determine a final privacy calculation result based on the first privacy calculation result and the second privacy calculation result;

[0010] User feedback is provided based on the final result of the privacy calculation.

[0011] In one embodiment of the present disclosure, the step of obtaining a privacy-preserving computing task includes:

[0012] Obtaining task information of the privacy computing task created by the user through the privacy computing interactive interface, wherein the task information of the privacy computing task includes the process execution order of the privacy computing task, the database storing the first target data and the second target data, and the address of the first application program interface and the address of the second application program interface;

[0013] Based on the task information of the privacy computing task, determine the workflow canvas of the privacy computing task.

[0014] In one embodiment of the present disclosure, before calling the first target calculation method through the first application program interface corresponding to the first target calculation method, the method further includes:

[0015] The first application program interface is provided to be pluggable with the interface layer of the privacy computing scheduling layer.

[0016] In one embodiment of the present disclosure, before calling the first target calculation method through the first application program interface corresponding to the first target calculation method, the method further includes:

[0017] Acquire a first software development kit provided by a first target manufacturer and including the first target calculation method;

[0018] Based on the first software development kit, generating an image of the first target computing method;

[0019] Based on the image of the first target computing method, a calling component for calling the first application program interface is generated through the privacy computing task layer.

[0020] In one embodiment of the present disclosure, performing privacy calculation on the first target data using the first target calculation method to obtain a first privacy calculation result includes:

[0021] Detecting whether the first target data matches the communication protocol of the first application program interface;

[0022] If there is no match, converting the first target data into a protocol format that matches the first application program interface through the proxy gateway of the privacy computing task layer;

[0023] The first target calculation method is used to perform privacy calculation on the first target data after the protocol format conversion through the proxy gateway to obtain the first privacy calculation result.

[0024] In one embodiment of the present disclosure, before calling the second target calculation method through the second application program interface corresponding to the second target calculation method, the method further includes:

[0025] The second application program interface is provided to be pluggable with the interface layer of the privacy computing scheduling layer.

[0026] In one embodiment of the present disclosure, before calling the second target calculation method through the second application program interface corresponding to the second target calculation method, the method further includes:

[0027] Acquire a second software development kit provided by a second target manufacturer and including the second target calculation method;

[0028] Based on the second software development kit, generating an image of the second target computing method;

[0029] Based on the image of the second target computing method, a calling component for calling the second application program interface is generated through the privacy computing task layer.

[0030] In one embodiment of the present disclosure, performing privacy calculation on the first target data using the second target calculation method to obtain a second privacy calculation result includes:

[0031] Detecting whether the second target data matches the communication protocol of the second application program interface;

[0032] If there is no match, converting the second target data into a protocol format that matches the second application program interface through the proxy gateway of the privacy computing task layer;

[0033] The second target calculation method is used to perform privacy calculation on the second target data after the protocol format conversion through the proxy gateway to obtain the second privacy calculation result.

[0034] In one embodiment of the present disclosure, it also includes:

[0035] The proxy gateway is used to perform at least one of encryption and decryption, two-way authentication and communication audit on the communication data of the two communicating parties.

[0036] In one embodiment of the present disclosure, before obtaining the privacy computing task, the method further includes:

[0037] A privacy computing data layer is used to provide at least two data storage formats for the first target data and the second target data.

[0038] A second aspect of the embodiments of the present disclosure provides a data processing device based on privacy computing, including:

[0039] A privacy computing task acquisition module, used to acquire a privacy computing task, wherein the privacy computing task includes first target data and second target data required for privacy computing, and a first target computing method and a second target computing method required for privacy computing;

[0040] a privacy computing module, configured to call the first target computing method through a first application program interface corresponding to the first target computing method, and perform privacy computing on the first target data using the first target computing method to obtain a first privacy computing result; and to call the second target computing method through a second application program interface corresponding to the second target computing method, and perform privacy computing on the second target data using the second target computing method to obtain a second privacy computing result; and to determine a final privacy computing result based on the first privacy computing result and the second privacy computing result;

[0041] A feedback module is used to provide user feedback based on the final result of the privacy calculation.

[0042] In one embodiment of the present disclosure, the privacy computing task acquisition module is used to obtain task information of the privacy computing task created by the user through the privacy computing interactive interface, wherein the task information of the privacy computing task includes the process execution order of the privacy computing task, the database storing the first target data and the second target data, and the address of the first application interface and the address of the second application interface; the privacy computing task acquisition module is also used to determine the workflow canvas of the privacy computing task based on the task information of the privacy computing task.

[0043] In one embodiment of the present disclosure, the privacy computing module is used to provide the first application program interface that is pluggable and connected to the interface layer of the privacy computing scheduling layer.

[0044] In one embodiment of the present disclosure, the privacy computing module is used to obtain a first software development kit provided by a first target manufacturer that includes the first target computing method; the privacy computing module is also used to generate an image of the first target computing method based on the first software development kit; the privacy computing module is also used to generate a calling component for calling the first application program interface through a privacy computing task layer based on the image of the first target computing method.

[0045] In one embodiment of the present disclosure, the privacy computing module is used to detect whether the first target data matches the communication protocol of the first application interface; if not, the first target data is converted into a protocol format that matches the first application interface through the proxy gateway of the privacy computing task layer; the privacy computing module is also used to use the first target calculation method to perform privacy calculation on the first target data after the protocol format conversion through the proxy gateway to obtain the first privacy calculation result.

[0046] In one embodiment of the present disclosure, the privacy computing module is used to provide the second application program interface that is pluggable and connected to the interface layer of the privacy computing scheduling layer.

[0047] In one embodiment of the present disclosure, the privacy computing module is used to obtain a second software development kit provided by a second target manufacturer and including the second target computing method; the privacy computing module is also used to generate an image of the second target computing method based on the second software development kit; the privacy computing module is also used to generate a calling component for calling the second application program interface through a privacy computing task layer based on the image of the second target computing method.

[0048] In one embodiment of the present disclosure, the privacy computing module is used to detect whether the second target data matches the communication protocol of the second application interface; if not, the second target data is converted into a protocol format that matches the second application interface through the proxy gateway of the privacy computing task layer; the privacy computing module is also used to use the second target calculation method to perform privacy calculation on the second target data after the protocol format conversion through the proxy gateway to obtain the second privacy calculation result.

[0049] In one embodiment of the present disclosure, the privacy computing module is also used to utilize the proxy gateway to perform at least one of encryption and decryption, two-way authentication, and communication audit on the communication data of the communicating parties.

[0050] In one embodiment of the present disclosure, the privacy computing module is further used to provide at least two data storage formats for the first target data and the second target data by using a privacy computing data layer.

[0051] According to a third aspect of the present disclosure, an electronic device is provided, including:

[0052] Memory for storing computer programs;

[0053] The processor is used to execute the computer program stored in the memory, and when the computer program is executed, the method described in the first aspect above is implemented.

[0054] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0055] In the data processing method and apparatus, device and storage medium based on privacy computing of the disclosed embodiment, after the user creates a privacy computing task in the privacy computing interactive interface, the privacy computing platform determines the different target data required for privacy computing and the privacy computing methods of different manufacturers from the privacy computing task. The privacy computing platform calls the privacy computing methods of different manufacturers through different application programming interfaces to perform privacy computing according to the corresponding target data, thus achieving interconnection and interoperability at the product integration level. The privacy computing platform aggregates the privacy computing results of each part to obtain the final result of the privacy computing and feeds it back to the user so that the user can obtain the privacy computing result in a timely manner.

[0056] The technical solution of the present disclosure is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings, which constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0058] The present disclosure may be more clearly understood from the following detailed description with reference to the accompanying drawings, in which:

[0059] Figure 1 This is a flowchart of a data processing method based on privacy computing in one embodiment of the present disclosure;

[0060] Figure 2 This is a structural block diagram of a data processing device based on privacy computing in one embodiment of the present disclosure;

[0061] Figure 3 The structure block diagram of an electronic device in one embodiment of the present disclosure is shown in FIG. DETAILED DESCRIPTION

[0062] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure unless otherwise specifically stated.

[0063] Those skilled in the art can understand that the terms "first" and "second" in the embodiments of the present disclosure are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0064] It should also be understood that in the embodiments of the present disclosure, “plurality” may refer to two or more than two, and “at least one” may refer to one, two, or more than two.

[0065] It should also be understood that any component, data or structure mentioned in the embodiments of the present disclosure can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0066] In addition, the term "and / or" in the present disclosure is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present disclosure generally indicates that the associated objects before and after are in an "or" relationship.

[0067] It should also be understood that the description of the various embodiments in the present disclosure focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced to each other, and for the sake of brevity, they will not be described one by one.

[0068] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0069] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0070] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0071] The embodiments of the present disclosure can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with many other general or special computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, large computer systems, and distributed cloud computing technology environments including any of the above systems, etc.

[0072] Electronic devices such as terminal devices, computer systems, servers, etc. can be described in the general context of computer system executable instructions (such as program modules) executed by computer systems. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0073] The data processing method based on privacy computing in the embodiment of the present disclosure can be applied to a privacy computing platform. The privacy computing platform may include a privacy computing interaction layer, a privacy computing scheduling layer, a privacy computing task layer, and a privacy computing data layer.

[0074] The privacy computing interaction layer provides an interactive interface for users to interact with the privacy computing platform. Users can create privacy computing tasks in the interactive interface. Privacy computing tasks can include the privacy computing process, the target data required for privacy computing, and the privacy computing methods required.

[0075] The privacy computing scheduling layer is used to provide multiple application programming interfaces (APIs). Through different application programming interfaces, privacy computing methods of different manufacturers can be called to perform privacy computing.

[0076] The privacy computing task layer is used to access the software development kits (SDKs) of different manufacturers. Based on the SDKs of different manufacturers, the APIs required for privacy computing can be called, and then the required privacy computing methods can be used for privacy computing.

[0077] The privacy computing data layer is used for data storage. The privacy computing data layer can integrate a variety of different data storage methods, such as S3, HDFS, etc., and also provides a unified interface to provide a unified data access method for various privacy computing method components. In the privacy computing data layer, user data may come from different data systems. With the introduction of the privacy computing data layer, users do not need to care about which data system the data comes from. At the same time, the data layer provides a unified data access interface, so that algorithm components from different manufacturers can use a unified method to obtain data, so that the major privacy computing method components can share data more conveniently and use data resources more efficiently.

[0078] Figure 1 FIG. 1 is a flow chart of a data processing method based on privacy computing in one embodiment of the present disclosure. Figure 1 As shown, the data processing method based on privacy computing includes:

[0079] S1: Obtain a privacy computing task, wherein the privacy computing task includes the first target data and the second target data required for the privacy computing, as well as the first target computing method and the second target computing method required for the privacy computing.

[0080] Users can create privacy computing tasks in the interactive interface provided by the privacy computing platform, determine the privacy computing process of the privacy computing task, and select the first target data, second target data, first target calculation method and second target calculation method required for the privacy computing.

[0081] After the user creates a privacy computing task through the interactive interface, the privacy computing platform can obtain the privacy computing task through the background of the interactive interface.

[0082] S2: Call the first target calculation method through a first application program interface corresponding to the first target calculation method, and use the first target calculation method to perform privacy calculation on the first target data to obtain a first privacy calculation result.

[0083] S3: Call the second target calculation method through the second application program interface corresponding to the second target calculation method, and use the second target calculation method to perform privacy calculation on the second target data to obtain a second privacy calculation result.

[0084] It should be noted that the present disclosure does not limit the order of execution of step S2 and step S3, that is, step S2 may be executed first and then step S3, or step S3 may be executed first and then step S2, or step S2 and step S3 may be executed simultaneously.

[0085] S4: Determine a final privacy calculation result based on the first privacy calculation result and the second privacy calculation result.

[0086] The privacy computing platform establishes corresponding application programming interfaces (APIs) for each privacy computing method in advance. Through different application programming interfaces, privacy computing methods of different manufacturers can be called to perform privacy computing.

[0087] In this embodiment, the privacy computing platform calls the first target computing method through the first application interface to perform privacy computing based on the first target data to obtain a first privacy computing result, and calls the second target computing method through the second application interface to perform privacy computing based on the second target data to obtain a second privacy computing result, and then aggregates the first privacy computing result and the second privacy computing result to obtain the final privacy computing result.

[0088] S5: Provide user feedback based on the final result of privacy computing.

[0089] In this embodiment, after the user creates a privacy computing task in the privacy computing interactive interface, the privacy computing platform determines the different target data required for privacy computing and the privacy computing methods of different manufacturers from the privacy computing task. The privacy computing platform calls the privacy computing methods of different manufacturers through different application programming interfaces to perform privacy computing according to the corresponding target data, thus achieving interconnection and interoperability at the product integration level. The privacy computing platform aggregates the privacy computing results of each part to obtain the final result of the privacy computing and feeds it back to the user so that the user can obtain the privacy computing result in a timely manner.

[0090] In one embodiment of the present disclosure, step S1 may include:

[0091] S1-1: Obtain the task information of the privacy computing task created by the user through the privacy computing interactive interface. Among them, the task information of the privacy computing task includes the process execution order of the privacy computing task, the database storing the first target data and the second target data, and the address of the first application interface and the address of the second application interface. In this way, it is helpful for the privacy computing platform to read the corresponding target data (i.e., the first target data or the second target data) at the corresponding process node according to the process execution order of the privacy computing task, and call the corresponding target calculation method through the address of the corresponding application interface (i.e., the first application interface or the second application interface) to perform privacy computing.

[0092] S1-2: Based on the task information of the privacy computing task, determine the workflow canvas of the privacy computing task.

[0093] In the privacy computing interaction layer, by introducing the canvas workflow mode, a unified process merge is performed for different computing methods and integrated into the canvas. Specifically, a centralized process entry is used to integrate the platform level for privacy computing related pre-operations, such as data upload, multi-party authorization, etc. Users only need to upload data once to use the data on multiple privacy computing methods. At the same time, the privacy computing method algorithm platforms of various manufacturers are integrated at the canvas workflow level.

[0094] In this embodiment, the privacy computing interaction layer of the privacy computing platform can integrate different computing methods into the canvas by introducing the canvas workflow mode. Users can create a workflow canvas for privacy computing tasks through the interactive platform, which helps the privacy computing platform read the corresponding target data (i.e., the first target data or the second target data) at the corresponding process node according to the process execution order of the privacy computing task, and call the corresponding target computing method through the address of the corresponding application interface for privacy computing.

[0095] In one embodiment of the present disclosure, before step S2, it may also include: providing a first application interface that is pluggable and connected to the interface layer of the privacy computing scheduling layer.

[0096] In another embodiment of the present disclosure, before step S3, it may also include: providing a second application interface that is pluggable and connected to the interface layer of the privacy computing scheduling layer.

[0097] In one example of the present disclosure, the first application program interface and the first vendor server are connected in a pluggable manner, and the second application program interface and the second vendor server are connected in a pluggable manner. In this way, the existing first vendor interface, the second vendor interface and the privacy computing interface layer can be integrated together, thereby achieving interconnection and interoperability at the product integration level. Specifically, the unified API interface layer acts as a bridge to integrate the privacy computing system interface and the vendor interface.

[0098] The unified interface is used to connect to the front-end and related client API requests, and is organized and integrated with the API interfaces of various manufacturers in a pluggable manner. This pluggable approach means that the system can easily integrate and expand the interfaces of different privacy computing vendors.

[0099] Through a specific routing method, the unified API interface middle layer can route requests to the corresponding manufacturer interface. The advantage of this is that without changing the forward interface, the system can flexibly support interfaces of different manufacturers and achieve interoperability with various privacy computing solutions.

[0100] Through the pluggable interface, the interfaces of other privacy computing vendors can be quickly supported. This means that when a new privacy computing vendor emerges, the system only needs to develop the corresponding plug-in without making large-scale modifications to the main system. This plug-in architecture makes the system highly flexible and scalable, and can easily interconnect with different privacy computing vendors.

[0101] In addition, the privacy computing scheduling layer can provide functions such as data encryption, security authentication, and access control, enhancing the security and reliability of the overall system.

[0102] In this embodiment, by providing a first application interface that is pluggable with the interface layer of the privacy computing scheduling layer, there is no need to make large-scale modifications to the system of the privacy computing platform. It has high flexibility and scalability and can easily interconnect with different privacy computing vendors.

[0103] In one embodiment of the present disclosure, before step S2, it may also include: obtaining a first software development kit provided by a first target manufacturer and including a first target computing method; generating an image of the first target computing method based on the first software development kit; and generating a calling component for calling the first application program interface through the privacy computing task layer based on the image of the first target computing method.

[0104] In another embodiment of the present disclosure, before step S3, it may also include: obtaining a second software development kit provided by a second target manufacturer and including a second target computing method; generating an image of the second target computing method based on the second software development kit; and generating a calling component for calling a second application program interface through a privacy computing task layer based on the image of the second target computing method.

[0105] At the privacy computing task layer, various manufacturers usually provide various algorithm components, and the interfaces and implementation methods of different manufacturers may differ, which brings challenges to system integration and interoperability. To solve this problem, a unified encapsulation and orchestration mechanism is introduced at the privacy computing task layer, and various privacy computing methods are integrated in the form of independent images. The algorithm components are introduced through image registration, and the algorithm parameters are called and run in a unified way at the image call level.

[0106] Specifically, when each manufacturer accesses with a software development kit (SDK), it is necessary to uniformly encapsulate the input and output of the privacy computing method components and define them using a unified interface. Each manufacturer can independently encapsulate the relevant components to ensure that they meet the requirements of the unified interface. Once the encapsulation is completed, these components can be registered as images so that they can be used by upper-level applications. The privacy computing task layer is responsible for receiving task requests from the privacy computing scheduling layer and scheduling the corresponding privacy computing method components for processing as needed. The privacy computing task layer acts as the hub of the privacy computing method, coordinating calls and data flows between different privacy computing method components. Through this scheduling framework, the system can efficiently manage and schedule various algorithm tasks to ensure that they are executed as expected.

[0107] In this embodiment, the privacy computing platform allows privacy computing vendors to access via SDK. Based on the SDK provided by each vendor, an image of the privacy computing method is generated, and then a calling component of the privacy computing method is generated, so that the corresponding privacy computing method can be called based on the SDK for safe and convenient privacy computing. When a privacy computing task requires the use of privacy computing methods from multiple vendors, access via SDK helps improve data interoperability.

[0108] In one embodiment of the present disclosure, performing privacy calculation on the first target data using the first target calculation method to obtain a first privacy calculation result in step S2 may include: detecting whether the first target data matches the communication protocol of the first application interface; if not, converting the first target data into a protocol format that matches the first application interface through a proxy gateway of the privacy computing task layer; and performing privacy calculation on the first target data after the protocol format conversion through the proxy gateway using the first target calculation method to obtain a first privacy calculation result.

[0109] In another embodiment of the present disclosure, performing privacy calculation on the first target data using the second target calculation method to obtain a second privacy calculation result in step S3 may include: detecting whether the second target data matches the communication protocol of the second application interface; if not, converting the second target data into a protocol format that matches the second application interface through a proxy gateway of the privacy computing task layer; and performing privacy calculation on the second target data after the protocol format conversion through a proxy gateway using the second target calculation method to obtain a second privacy calculation result.

[0110] In the privacy computing task layer, in order to ensure the consistency and reliability of the execution environment of the privacy computing method components, a unified proxy layer that supports the national secret protocol is provided. This proxy layer can provide a reliable centralized proxy layer for the entire service, ensuring that the algorithm components can run in a safe, reliable and efficient environment. A proxy gateway is set up in the proxy layer. The proxy gateway acts as a transit station for privacy computing method communication, responsible for processing the communication protocols of different privacy computing vendors and ensuring their compatibility. Based on the proxy protocol implemented by TCP, the proxy gateway can quickly adapt to the complex multi-layer network environment within various banks. This means that even in a complex network architecture, the proxy gateway can effectively transfer algorithm communication and ensure the stability and reliability of communication. Through such a design, the proxy gateway can provide a reliable, solid and trustworthy underlying communication network for the privacy computing communications of all parties. It can adapt to the communication protocols of various algorithm vendors, handle complex network environments, and protect the security and credibility of communications by introducing security functions. Such a proxy gateway design provides a reliable basic communication architecture for privacy computing.

[0111] In this embodiment, before using the first target calculation method to perform privacy calculation on the first target data, the proxy gateway of the privacy calculation task layer can be used to convert the communication protocol of the first target data to adapt to the first application interface protocol format. Correspondingly, before using the second target calculation method to perform privacy calculation on the second target data, the proxy gateway of the privacy calculation task layer can be used to convert the communication protocol of the second target data to adapt to the second application interface protocol format. In this way, the compatibility between the target data of privacy calculation and the application interface can be improved.

[0112] In this embodiment, step S2 may also include: using a proxy gateway to perform at least one of encryption and decryption, two-way authentication, and communication audit on the communication data of the communicating parties.

[0113] The proxy gateway of the privacy computing platform introduces functions including national encryption, two-way authentication, and communication audit in a pluggable manner. These functions are introduced to enhance the security and credibility of communications. The national encryption algorithm can be used to encrypt and decrypt communication data to ensure the confidentiality of the data. Two-way authentication can verify the identities of both parties in communication and prevent interference from malicious entities. The communication audit function is used to record and monitor the data of the communication process between the two parties in communication for post-audit and tracking.

[0114] In this embodiment, the proxy gateway is used to perform at least one of encryption and decryption, two-way authentication and communication audit on the communication data of the communicating parties, which can effectively enhance the security and credibility of the communication.

[0115] In one embodiment of the present disclosure, before step S1, the method may further include: using a privacy computing data layer to provide at least two data storage formats for the first target data and the second target data.

[0116] In the privacy computing data layer, a variety of different data storage methods can be integrated, such as S3, HDFS, etc., and a unified interface is also provided to provide a unified data access method for various privacy computing method components. In the privacy computing data layer, user data may come from different data systems. With the introduction of the privacy computing data layer, users do not need to care about which data system the data comes from. At the same time, the data layer provides a unified data access interface, so that algorithm components from different manufacturers can use a unified method to obtain data, so that the major privacy computing method components can share data more conveniently and use data resources more efficiently.

[0117] In this embodiment, a variety of different data storage methods are integrated into the privacy computing data layer, which helps the privacy computing platform to use data in data storage methods that match different privacy computing methods, thereby improving the format compatibility between data and privacy computing methods.

[0118] Figure 2 FIG. 1 is a structural block diagram of a data processing device based on privacy computing in one embodiment of the present disclosure. Figure 2 As shown, a data processing device based on privacy computing includes:

[0119] The privacy computing task acquisition module 100 is used to acquire a privacy computing task, wherein the privacy computing task includes the first target data and the second target data required for the privacy computing, and the first target computing method and the second target computing method required for the privacy computing;

[0120] The privacy computing module 200 is used to call the first target computing method through a first application program interface corresponding to the first target computing method, and perform privacy computing on the first target data using the first target computing method to obtain a first privacy computing result; it is also used to call the second target computing method through a second application program interface corresponding to the second target computing method, and perform privacy computing on the second target data using the second target computing method to obtain a second privacy computing result; it is also used to determine a final privacy computing result based on the first privacy computing result and the second privacy computing result;

[0121] The feedback module 300 is used to provide user feedback based on the final result of the privacy computing.

[0122] In one embodiment of the present disclosure, the privacy computing task acquisition module 100 is used to obtain task information of a privacy computing task created by a user through a privacy computing interactive interface, wherein the task information of the privacy computing task includes the process execution order of the privacy computing task, a database storing the first target data and the second target data, and the address of the first application interface and the address of the second application interface; the privacy computing task acquisition module 100 is also used to determine the workflow canvas of the privacy computing task based on the task information of the privacy computing task.

[0123] In one embodiment of the present disclosure, the privacy computing module 200 is used to provide a first application program interface that is pluggable and connected to the interface layer of the privacy computing scheduling layer.

[0124] In one embodiment of the present disclosure, the privacy computing module 200 is used to obtain a first software development kit provided by a first target manufacturer that includes a first target computing method; the privacy computing module 200 is also used to generate an image of the first target computing method based on the first software development kit; the privacy computing module 200 is also used to generate a calling component for calling the first application program interface through the privacy computing task layer based on the image of the first target computing method.

[0125] In one embodiment of the present disclosure, the privacy computing module 200 is used to detect whether the first target data matches the communication protocol of the first application interface; if not, the first target data is converted into a protocol format that matches the first application interface through the proxy gateway of the privacy computing task layer; the privacy computing module 200 is also used to use the first target calculation method to perform privacy calculation on the first target data after the protocol format conversion through the proxy gateway to obtain a first privacy calculation result.

[0126] In one embodiment of the present disclosure, the privacy computing module 200 is used to provide a second application program interface that is pluggable and connected to the interface layer of the privacy computing scheduling layer.

[0127] In one embodiment of the present disclosure, the privacy computing module 200 is used to obtain a second software development kit provided by a second target manufacturer that includes a second target computing method 200; the privacy computing module 200 is also used to generate an image of the second target computing method based on the second software development kit; the privacy computing module 200 is also used to generate a calling component for calling the second application program interface through the privacy computing task layer based on the image of the second target computing method.

[0128] In one embodiment of the present disclosure, the privacy computing module 200 is used to detect whether the second target data matches the communication protocol of the second application interface; if not, the second target data is converted into a protocol format that matches the second application interface through the proxy gateway of the privacy computing task layer; the privacy computing module 200 is also used to use the second target calculation method to perform privacy calculation on the second target data after the protocol format conversion through the proxy gateway to obtain a second privacy calculation result.

[0129] In one embodiment of the present disclosure, the privacy computing module 200 is also used to utilize a proxy gateway to perform at least one of encryption and decryption, two-way authentication, and communication auditing on the communication data of the communicating parties.

[0130] In one embodiment of the present disclosure, the privacy computing module 200 is further configured to use the privacy computing data layer to provide at least two data storage formats for the first target data and the second target data.

[0131] It should be noted that the specific implementation of the data processing device based on privacy computing in the embodiment of the present disclosure is similar to the specific implementation of the data processing method based on privacy computing in the embodiment of the present disclosure. Please refer to the description of the data processing method based on privacy computing for details. In order to reduce redundancy, it will not be repeated here.

[0132] In addition, an embodiment of the present disclosure further provides an electronic device, including:

[0133] Memory for storing computer programs;

[0134] A processor is used to execute the computer program stored in the memory, and when the computer program is executed, the data processing method based on privacy computing described in any of the above embodiments of the present disclosure is implemented.

[0135] Figure 3 FIG. 1 is a structural block diagram of an electronic device in one embodiment of the present disclosure. Figure 3 As shown, the electronic device includes one or more processors and memory.

[0136] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0137] The memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor may execute the program instructions to implement the point cloud matching method of each embodiment of the present disclosure described above and / or other desired functions.

[0138] In one example, the electronic device may further include: an input device and an output device, and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0139] In addition, the input device may also include, for example, a keyboard, a mouse, and the like.

[0140] The output device can output various information to the outside, including the determined distance information, direction information, etc. The output device can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0141] Of course, to simplify, Figure 3 Only some of the components related to the present disclosure in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device may further include any other appropriate components.

[0142] In addition to the above-mentioned methods and devices, an embodiment of the present disclosure may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the data processing method based on privacy computing according to various embodiments of the present disclosure described in the above part of this specification.

[0143] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the disclosed embodiments, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0144] In addition, an embodiment of the present disclosure may also be a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the steps of the data processing method based on privacy computing according to various embodiments of the present disclosure described in the above part of this specification.

[0145] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0146] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0147] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to the necessity of adopting the above specific details to be implemented.

[0148] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0149] The block diagrams of the devices, apparatuses, equipment, and systems involved in this disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including," "comprising," "having," and the like are open words, referring to "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or," and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0150] The method and apparatus of the present disclosure may be implemented in many ways. For example, the method and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present disclosure may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present disclosure. Therefore, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

[0151] It should also be noted that in the apparatus, device and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0152] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0153] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A data processing method based on privacy computing, It is characterized in that include: Acquire a privacy computing task, wherein the privacy computing task includes first target data and second target data required for privacy computing, and a first target computing method and a second target computing method required for privacy computing; Calling the first target calculation method through a first application program interface corresponding to the first target calculation method, and performing privacy calculation on the first target data using the first target calculation method to obtain a first privacy calculation result; Calling the second target calculation method through a second application program interface corresponding to the second target calculation method, and performing privacy calculation on the second target data using the second target calculation method to obtain a second privacy calculation result; Determine a final privacy calculation result based on the first privacy calculation result and the second privacy calculation result; User feedback is provided based on the final result of the privacy calculation.

2. The method according to claim 1, It is characterized in that The obtaining of the privacy computing task includes: Obtaining task information of the privacy computing task created by the user through the privacy computing interactive interface, wherein the task information of the privacy computing task includes the process execution order of the privacy computing task, the database storing the first target data and the second target data, and the address of the first application program interface and the address of the second application program interface; Based on the task information of the privacy computing task, determine the workflow canvas of the privacy computing task.

3. The method according to claim 1, It is characterized in that Before calling the first target calculation method through the first application program interface corresponding to the first target calculation method, the method further includes: The first application program interface is provided to be pluggable with the interface layer of the privacy computing scheduling layer.

4. The method according to claim 1, It is characterized in that Before calling the first target calculation method through the first application program interface corresponding to the first target calculation method, the method further includes: Acquire a first software development kit provided by a first target manufacturer and including the first target calculation method; Based on the first software development kit, generating an image of the first target computing method; Based on the image of the first target computing method, a calling component for calling the first application program interface is generated through the privacy computing task layer.

5. The method according to claim 4, It is characterized in that The using the first target calculation method to perform privacy calculation on the first target data to obtain a first privacy calculation result includes: Detecting whether the first target data matches the communication protocol of the first application program interface; If there is no match, converting the first target data into a protocol format that matches the first application program interface through the proxy gateway of the privacy computing task layer; The first target calculation method is used to perform privacy calculation on the first target data after the protocol format conversion through the proxy gateway to obtain the first privacy calculation result.

6. The method according to claim 5, It is characterized in that Also includes: The proxy gateway is used to perform at least one of encryption and decryption, two-way authentication and communication audit on the communication data of the two communicating parties.

7. The method according to any one of claims 1 to 6, It is characterized in that Before obtaining the privacy computing task, it also includes: A privacy computing data layer is used to provide at least two data storage formats for the first target data and the second target data.

8. A data processing device based on privacy computing, It is characterized in that include: A privacy computing task acquisition module, used to acquire a privacy computing task, wherein the privacy computing task includes first target data and second target data required for privacy computing, and a first target computing method and a second target computing method required for privacy computing; a privacy computing module, configured to call the first target computing method through a first application program interface corresponding to the first target computing method, and perform privacy computing on the first target data using the first target computing method to obtain a first privacy computing result; and to call the second target computing method through a second application program interface corresponding to the second target computing method, and perform privacy computing on the second target data using the second target computing method to obtain a second privacy computing result; and to determine a final privacy computing result based on the first privacy computing result and the second privacy computing result; A feedback module is used to provide user feedback based on the final result of the privacy calculation.

9. An electronic device, It is characterized in that include: Memory for storing computer programs; A processor is used to execute the computer program stored in the memory, and when the computer program is executed, the method described in any one of claims 1 to 7 is implemented.

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

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