Multi-party data processing method, device, equipment, medium and product

Abstract

The invention discloses a multi-party data processing method, device and equipment, a medium and a product, and relates to the technical field of multi-party security computing. The method comprises the following steps: acquiring a calculation task initiated by a middle station of a task initiator; determining computing resources of a task participant according to the computing task; calculating the calculation task according to the calculation resource to obtain a task calculation result; and feeding back the task calculation result to the task initiator. According to the technical scheme, the multi-party security calculation efficiency can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of multi-party secure computation, and in particular to a multi-party data processing method, device, equipment, medium and product. BACKGROUND

[0002] Multi-party secure computation (MPC) is a cryptographic technology framework that allows mutually distrustful parties to cooperate in computing without revealing their private data, and only shares the computing result. At present, multi-party secure computation is mainly based on direct calculation of two or three parties. A middle platform needs to schedule the tasks of multi-party calculation and then start the calculation. In this way, whenever one party initiates a calculation request, the other party's middle platform needs to wait for the demand of the one party, which affects the efficiency of multi-party calculation. SUMMARY

[0003] The present application provides a multi-party data processing method, device, equipment, medium and product to improve the efficiency of multi-party secure computation.

[0004] According to an aspect of the present application, a multi-party data processing method is provided, applied to a multi-party computing platform; the method comprises:

[0005] obtaining a calculation task initiated by a middle platform of a task initiator;

[0006] determining the computing resources of a task participant according to the calculation task;

[0007] calculating the calculation task according to the computing resources to obtain a task calculation result;

[0008] feeding back the task calculation result to the task initiator.

[0009] According to another aspect of the present application, a multi-party data processing device is provided, configured in a multi-party computing platform; the device comprises:

[0010] a calculation task obtaining module for obtaining a calculation task initiated by a middle platform of a task initiator;

[0011] a computing resource determining module for determining the computing resources of a task participant according to the calculation task;

[0012] a calculation result determining module for calculating the calculation task according to the computing resources to obtain a task calculation result;

[0013] a calculation result feedback module for feeding back the task calculation result to the task initiator.

[0014] According to another aspect of the present application, there is provided an electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein

[0017] the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the multi-party data processing method according to any one of the embodiments of the present application.

[0018] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the multi-party data processing method according to any one of the embodiments of the present application when executed by the processor.

[0019] According to another aspect of the present application, there is provided a computer program product comprising a computer program for implementing the multi-party data processing method according to any one of the embodiments of the present application when executed by a processor.

[0020] The technical solution of the embodiments of the present application comprises the following steps: obtaining a computing task initiated by a task initiator; determining computing resources of a task participant according to the computing task; performing computation on the computing task according to the computing resources to obtain a task computation result; and feeding back the task computation result to the task initiator. Compared with the prior art, in which the task participant platform needs to wait for the demand of the task initiator whenever the task initiator initiates a computing request in a multi-party computing scenario, the present application introduces a multi-party computing platform to perform the computing task of the task initiator, and obtains the computing resources of the task participant through the multi-party computing platform, so that the task participant is not aware of the computing task, thereby improving the multi-party computing efficiency.

[0021] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1is a flow chart of a multi-party data processing method according to an embodiment of the present application;

[0024] Figure 2 is a flow chart of a multi-party data processing method according to an embodiment of the present application;

[0025] Figure 3 is a structural schematic diagram of a multi-party data processing device according to an embodiment of the present application;

[0026] Figure 4 is a structural schematic diagram of an electronic device implementing a multi-party data processing method according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to the process, method, product or device.

[0029] In addition, it should also be noted that in the technical solutions of the present application, the collection, storage, use, processing, transmission, provision and disclosure of related data involved in the computing tasks, etc. comply with the relevant legal regulations and do not violate public order and good customs.

[0030] Currently, multi-party secure computation mainly relies on direct computation between two or three parties. A middleware platform is needed to schedule multi-party computation tasks separately and then initiate the computation. Each party includes a middleware platform and an MPC (Multi-Party Computation) unit. Taking a two-party interaction as an example, the interaction logic is as follows: 1) Party A, as the initiator, needs to interact and confirm the relevant computation logic and data acquisition logic with Party B at the middleware platform level. 2) Both middleware platforms simultaneously call the MPC unit, passing the computation logic and data acquisition method as parameters to the MPC unit. 3) The two MPC units perform interactive computation, and then Party A returns the computation result to Party B. At this point, whenever Party A initiates a computation request, Party B's middleware platform must wait to process Party A's request. However, Party B doesn't actually need any results; it's merely a cooperating party in the computation. Party B can remain unaware of Party A's requests. Therefore, this invention provides a multi-party data processing method that enables Party B, as a participant in multi-party computation, i.e., the data provider, to remain unaware of Party A's requests.

[0031] Figure 1 This is a flowchart of a multi-party data processing method according to an embodiment of the present invention. This embodiment is applicable to scenarios of multi-party secure computation. The method can be executed by a multi-party data processing device, which can be implemented in hardware and / or software. This device can be configured in an electronic device that carries multi-party data processing functions, such as a server. Figure 1 As shown, the method includes:

[0032] S110. Obtain the computing task initiated by the task initiator's middle platform.

[0033] In this embodiment, the multi-party computing platform includes multi-party computing services and multi-party computing units from the task initiator and at least one task participant. That is, the multi-party computing platform consists of the multi-party computing services (MPC services) of each party and the multi-party computing platforms (MPC computing units) of each party. Each multi-party computing unit is configured with its own data usage rules. Optionally, the task participant and the task initiator each activate the computing platform operators; in this case, the computing units of each party jointly construct the multi-party computing platform.

[0034] The term "task initiator" refers to the party that requires computation from multiple parties. A computation task is a task initiated by the task initiator that requires the participation of other parties.

[0035] Specifically, the task initiator's middle platform sends computing tasks to the multi-party computing platform; correspondingly, the multi-party computing platform receives and receives the computing tasks.

[0036] S120. Determine the computing resources of the task participants based on the computing task.

[0037] In this embodiment, computing resources refer to the resources used to implement computing tasks, including but not limited to task computing methods and task data; wherein, task computing methods refer to the algorithms used to complete computing tasks; and task data refers to the data required to complete computing tasks.

[0038] Specifically, the multi-party computing platform parses the computing task to obtain the computing resources of the task participants; at the same time, the multi-party computing platform determines the computing resources of the task initiator.

[0039] S130. Perform calculations on the computing task based on computing resources to obtain the task calculation results.

[0040] In this embodiment, the task calculation result refers to the calculation result corresponding to the calculation task.

[0041] Specifically, the multi-party computing platform processes and calculates computing tasks based on computing resources to obtain the task calculation results.

[0042] S140. Feed back the task calculation results to the task initiator.

[0043] Specifically, the multi-party computing platform feeds back the task calculation results to the task initiator.

[0044] The technical solution of this invention involves: acquiring the computing task initiated by the task initiator's middleware; determining the computing resources of the task participants based on the computing task; performing calculations on the computing task based on the computing resources to obtain the task calculation result; and feeding back the task calculation result to the task initiator. Compared to existing technologies where, in multi-party computing scenarios, the task participant middleware needs to wait to process the task initiator's request regardless of when it is initiated, this invention introduces a multi-party computing platform to execute the task initiator's computing task and acquires the computing resources of the task participants, making the task participants unaware of the computing task and thus improving the efficiency of multi-party computing.

[0045] Based on the above embodiments, as an optional aspect of the present invention, before obtaining the computing task initiated by the task initiator's platform, the method further includes: obtaining data usage permissions for at least one task participant.

[0046] Specifically, after jointly building a multi-party computing platform, before the task initiator's middle platform launches the computing task, at least one task participant authorizes the multi-party computing platform, allowing the participants in the multi-party computing platform to have data usage rights to each other.

[0047] Understandably, after the multi-party computing platform is built, obtaining data access permissions from the participants in the multi-party computing platform can ensure that task data can be quickly obtained during subsequent multi-party computing.

[0048] Figure 2 This is a flowchart of a multi-party data processing method according to an embodiment of the present invention. Based on the above embodiments, this embodiment further optimizes the steps of "determining the computing resources of the task participants according to the computing task" and "performing calculations on the computing task according to the computing resources to obtain the task calculation result," providing an optional implementation scheme. For example... Figure 2 As shown, the method includes:

[0049] S210. Obtain the computing task initiated by the task initiator's middle platform.

[0050] S220. Determine the computing resources of the task participants based on the computing task.

[0051] S230. Perform calculations on the computing task based on computing resources to obtain the task calculation results.

[0052] S240. Feed back the task calculation results to the task initiator.

[0053] An alternative approach involves determining the computing resources of task participants based on the computing task, including: parsing the computing task to determine at least one task participant and a task computing method; obtaining task data of the task participants based on the computing task; and using the task data and task computing method as computing resources.

[0054] The computation task includes a key protocol, which includes the fields corresponding to the task parameters as shown in the table below:

[0055]

[0056] The fields are described below:

[0057] Expression: similar to y = a +b \n return y;

[0058] Param: a and b in the expression, including how a and b are retrieved. For example,

[0059] {"a":{"party":"1001","method":"http","param":{"url":"https: / / xxxx","payload":{...}}}};

[0060] Parties: The participants in the calculation, similar to ["1001","1002"];

[0061] Protocol: MPC protocol, similar to SEMI2K, ABY3, etc.

[0062] It should be noted that task parameters refer to the request parameters used to perform the computation task.

[0063] Specifically, the computation task is parsed to obtain task parameters. From the task parameters, at least one task participant and the task computation method (i.e., computation logic) are determined. The data acquisition method of the task participant is also determined from the task parameters. Task data is obtained from the task participant according to the data acquisition method. Finally, the task computation method and task data are used as computation resources.

[0064] Understandably, by identifying task participants and obtaining task data from them through a multi-party computation platform, the task participants can remain unaware of the process, thereby improving the computational efficiency of multi-party computation.

[0065] For example, obtaining task data of task participants based on a computing task includes: parsing the computing task through the multi-party computing service of the task initiator to determine the data acquisition method of the task participants; and obtaining task data of at least one task participant through the multi-party computing unit of at least one task participant according to the data acquisition method.

[0066] Specifically, for each task participant, the task initiator's multi-party computation service parses the computation task, determines the data acquisition method of the task participant from the task parameters, and then passes the data acquisition method to the task participant's multi-party computation unit. The multi-party computation unit then acquires the task data of the task participant according to the data acquisition method. At the same time, the task initiator's multi-party computation unit also acquires the task initiator's task data.

[0067] It is understandable that by obtaining the task data of the corresponding task participants through the multi-party computing unit in the multi-party computing platform, the interaction and confirmation between the task participant platform and the task initiator platform can be avoided during data exchange and acquisition, thereby improving the data acquisition speed and thus improving the efficiency of multi-party computing.

[0068] An alternative approach involves performing computation on a computational task based on computational resources to obtain the task computation result, including: obtaining the task computation result through interactive computation by multiple computational units of the task initiator and at least one task participant based on computational resources.

[0069] Specifically, based on the task calculation method, the multi-party calculation unit of the task initiator and the multi-party calculation unit of at least one task participant interact and calculate based on the task data to obtain the task calculation result. Then, the multi-party calculation unit of the task initiator feeds back the task calculation result to the task initiator's central platform.

[0070] Understandably, when implementing the computation process of a computation task, avoiding multiple interactions between the task participants and the task initiator in the middle platform, and only requiring interaction and computation between the multi-party computation units of each party in the multi-party interaction platform, can improve the efficiency of multi-party computation.

[0071] The technical solution of this invention involves: acquiring the computing task initiated by the task initiator's middleware; determining the computing resources of the task participants based on the computing task; performing calculations on the computing task based on the computing resources to obtain the task calculation result; and feeding back the task calculation result to the task initiator. Compared to existing technologies where, in multi-party computing scenarios, the task participant middleware needs to wait to process the task initiator's request regardless of when it is initiated, this invention introduces a multi-party computing platform to execute the task initiator's computing task and acquires the computing resources of the task participants, making the task participants unaware of the computing task and thus improving the efficiency of multi-party computing.

[0072] Figure 3 This is a schematic diagram of a multi-party data processing device according to an embodiment of the present invention. This embodiment is applicable to scenarios involving secure multi-party computation. The multi-party data processing device can be implemented in hardware and / or software, and can be configured in an electronic device that carries multi-party data processing functions, such as a server. Figure 3 As shown, the device includes:

[0073] The computation task acquisition module 310 is used to acquire computation tasks initiated by the task initiator's middle platform;

[0074] The computing resource determination module 320 is used to determine the computing resources of the task participants based on the computing task.

[0075] The calculation result determination module 330 is used to perform calculations on the calculation task based on the computing resources and obtain the task calculation result;

[0076] The calculation result feedback module 340 is used to feed back the task calculation results to the task initiator.

[0077] The technical solution of this invention involves: acquiring the computing task initiated by the task initiator's middleware; determining the computing resources of the task participants based on the computing task; performing calculations on the computing task based on the computing resources to obtain the task calculation result; and feeding back the task calculation result to the task initiator. Compared to existing technologies where, in multi-party computing scenarios, the task participant middleware needs to wait to process the task initiator's request regardless of when it is initiated, this invention introduces a multi-party computing platform to execute the task initiator's computing task and acquires the computing resources of the task participants, making the task participants unaware of the computing task and thus improving the efficiency of multi-party computing.

[0078] Optionally, the multi-party computing platform includes multi-party computing services and multi-party computing units for the task initiator and at least one task participant.

[0079] Optionally, the computational resource determination module 320 is used for:

[0080] The computation task is analyzed to determine at least one participant and the computation method.

[0081] Obtain task data from the task participants based on the computation task;

[0082] Task data and task calculation methods are used as computing resources.

[0083] Optionally, the computational resource determination module 320 is specifically used for:

[0084] The computation task is analyzed through the multi-party computation service of the task initiator to determine the data acquisition method of the task participants;

[0085] The task data of at least one task participant is obtained by the multi-party computing unit of at least one task participant according to the data acquisition method.

[0086] Optionally, the calculation result determination module 330 is used for:

[0087] The task calculation result is obtained by the interactive calculation of multiple computing units of the task initiator and at least one task participant based on computing resources.

[0088] Optionally, the device may also include an authorization module for:

[0089] Before acquiring the computing task initiated by the task initiator's middle platform, obtain data usage permissions from at least one task participant.

[0090] The multi-party data processing apparatus provided in the embodiments of the present invention can execute the multi-party data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0091] According to embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0092] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the multi-party data processing method of the present invention. Figure 4A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0093] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0094] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0095] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as multi-party data processing methods.

[0096] In some embodiments, the multi-party data processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the multi-party data processing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the multi-party data processing method by any other suitable means (e.g., by means of firmware).

[0097] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0098] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0099] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0100] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0101] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0102] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0103] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0104] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A multi-party data processing method, characterized by, The application is applied to a multi-party computing platform, and comprises the following steps: obtaining a computing task initiated by a task initiator of a middle platform; determining computing resources of a task participant according to the computing task; computing the computing task according to the computing resources to obtain a task computing result; feeding back the task computing result to the task initiator.

2. The method of claim 1, wherein, The multi-party computing platform comprises a multi-party computing service and a multi-party computing unit of at least one task participant.

3. The method of claim 2, wherein, The method comprises the following steps: analyzing the computing task to determine at least one task participant and a task computing mode; obtaining task data of the task participant according to the computing task; taking the task data and the task computing mode as the computing resources.

4. The method of claim 3, wherein, The method comprises the following steps: analyzing the computing task by the multi-party computing service of the task initiator to determine a data obtaining mode of the task participant; obtaining task data of at least one task participant according to the data obtaining mode by the multi-party computing unit of the at least one task participant.

5. The method of claim 2, wherein, The method comprises the following steps: interactively computing the computing task according to the computing resources by the multi-party computing unit of the task initiator and the at least one task participant to obtain the task computing result.

6. The method of claim 1, wherein, Before obtaining the computing task initiated by the task initiator of the middle platform, the method further comprises the following step: obtaining data use permissions of at least one task participant.

7. A multi-party data processing apparatus, comprising: The application is configured to a multi-party computing platform, and comprises the following steps: a computing task obtaining module, configured to obtain a computing task initiated by a task initiator of a middle platform; a computing resource determining module, configured to determine computing resources of a task participant according to the computing task; a computing result determining module, configured to compute the computing task according to the computing resources to obtain a task computing result; a computing result feeding back module, configured to feed back the task computing result to the task initiator.

8. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected with the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the multi-party data processing method in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to enable the processor to execute the data processing method in any one of claims 1-6 when executed.

10. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to implement the multi-party data processing method in any one of claims 1-6.

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