A method and apparatus for processing trusted data
By working in collaboration with multiple trusted collaborative computing platforms, the problem of inaccurate calculation results from a single platform is solved, enabling multi-platform access to trusted data and improving the accuracy and comprehensiveness of the calculation results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA UNITED NETWORK COMM GRP CO LTD
- Filing Date
- 2022-08-16
- Publication Date
- 2026-05-19
AI Technical Summary
Existing trusted collaborative computing platforms can only perform calculations based on a single trusted data set, resulting in calculation results that fail to accurately and comprehensively reflect the characteristics of the trusted data set.
By communicating with multiple trusted collaborative computing platforms through a virtualized trusted collaborative computing platform, and using a preset matching model to obtain the target computing model and platform, trusted data can be circulated and computed between multiple platforms.
It improves the accuracy and comprehensiveness of reliable data calculation results, and enhances the user experience.
Smart Images
Figure CN115438346B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of information technology, and in particular to a method and apparatus for processing trusted data. Background Technology
[0002] Trusted collaborative computing technology is a type of computing technology that analyzes and computes trusted data while ensuring data security. It ensures that trusted data is "usable but not visible" throughout the entire computational flow process, including generation, storage, application, and destruction, thus effectively resolving the conflict between data circulation and data security.
[0003] Currently, various manufacturers have launched different trusted collaborative computing platforms based on trusted collaborative computing technology. These platforms can utilize computational models to process trusted data, providing users with trusted data processing services.
[0004] However, each trusted collaborative computing platform provides different trusted data. The trusted collaborative computing platform can only use the computing model of that trusted collaborative computing platform to perform calculations on the trusted data provided by that trusted collaborative computing platform. As a result, each trusted collaborative computing platform can only perform calculations based on a single trusted data, which leads to the calculation results of the trusted data failing to accurately and comprehensively reflect the characteristics of the trusted data. Summary of the Invention
[0005] This application provides a method and apparatus for processing trusted data, which addresses the problem in the prior art that each trusted collaborative computing platform can only perform calculations based on a single piece of trusted data provided by the trusted collaborative computing platform, resulting in the calculation results of trusted data failing to accurately and comprehensively reflect the characteristics of trusted data.
[0006] In a first aspect, this application provides a method for processing trusted data, applied to a virtualized trusted collaborative computing platform, wherein the virtualized trusted collaborative computing platform is communicatively connected to multiple trusted collaborative computing platforms; the method includes:
[0007] The system receives a trusted data computation request sent by a terminal device. The trusted data computation request includes the identifier of the trusted data to be computed and the key information corresponding to the computation model to be used.
[0008] Based on the trusted data calculation request, a preset matching model is used to obtain the identifier of the target calculation model that matches the key information corresponding to the calculation model to be used;
[0009] The system queries and retrieves a first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and queries and retrieves a second trusted collaborative computing platform that matches the identifier of the target computing model.
[0010] The system obtains the trusted data to be calculated corresponding to the identifier of the trusted data to be calculated from the first trusted collaborative computing platform, and requests the second trusted collaborative computing platform to perform calculation processing on the trusted data to be calculated according to the target computing model corresponding to the identifier of the target computing model, and obtain the trusted data calculation result.
[0011] The calculation result of the trusted data is sent to the terminal device;
[0012] The first trusted collaborative computing platform and the second trusted collaborative computing platform may be the same or different.
[0013] The aforementioned methods for processing trusted data also include:
[0014] Establish an initial matching model;
[0015] The identifiers of the computing models uploaded by the multiple trusted collaborative computing platforms, as well as the key information corresponding to the computing models, are obtained respectively.
[0016] The initial matching model is trained based on the identifier of the computing model and the key information corresponding to the computing model to obtain the preset matching model.
[0017] In the aforementioned method for processing trusted data, the key information corresponding to the computing model includes the identifier of the computing model, the input format of the computing model, the algorithm used by the computing model, and the application scenario of the computing model.
[0018] Secondly, this application provides a trusted data processing apparatus, comprising:
[0019] The receiving module is used to receive a trusted data calculation request sent by the terminal device. The trusted data calculation request includes the identifier of the trusted data to be calculated and the key information corresponding to the calculation model to be used.
[0020] The processing module is used to obtain the identifier of the target computing model that matches the key information corresponding to the computing model to be used, based on the trusted data computing request and using a preset matching model.
[0021] The processing module is further configured to query and obtain a first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and to query and obtain a second trusted collaborative computing platform that matches the identifier of the target computing model.
[0022] The processing module is further configured to obtain the trusted data to be calculated corresponding to the identifier of the trusted data to be calculated from the first trusted collaborative computing platform, and request the second trusted collaborative computing platform to perform calculation processing on the trusted data to be calculated according to the target computing model corresponding to the identifier of the target computing model, and obtain the trusted data calculation result.
[0023] A sending module is used to send the calculation result of the trusted data to the terminal device;
[0024] The first trusted collaborative computing platform and the second trusted collaborative computing platform may be the same or different.
[0025] In the aforementioned trusted data processing apparatus,
[0026] The processing module is also used to establish an initial matching model;
[0027] The receiving module is also used to obtain the identifiers of the computing models uploaded by multiple trusted collaborative computing platforms, as well as the key information corresponding to the computing models.
[0028] The processing module is further configured to train the initial matching model based on the identifier of the computing model and the key information corresponding to the computing model, so as to obtain the preset matching model.
[0029] In the aforementioned trusted data processing device, the key information corresponding to the computing model includes the identifier of the computing model, the input format of the computing model, the algorithm used by the computing model, and the application scenario of the computing model.
[0030] Thirdly, this application provides an electronic device, comprising:
[0031] Processor, memory, communication interface;
[0032] The memory is used to store executable instructions that can be executed by the processor;
[0033] The processor is configured to execute the trusted data processing method according to any one of claims 1 to 3 by executing the executable instructions.
[0034] Fourthly, this application provides a trusted data processing system, including a virtualized trusted collaborative computing platform and multiple trusted collaborative computing platforms, wherein the virtualized trusted collaborative computing platform is communicatively connected to the multiple trusted collaborative computing platforms;
[0035] The virtualized trusted collaborative computing platform is used to execute the trusted data processing method described in the first aspect.
[0036] Fifthly, this application provides a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the trusted data processing method described in the first aspect.
[0037] Sixthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the trusted data processing method described in the first aspect.
[0038] This application provides a method and apparatus for processing trusted data. In this method, a virtualized trusted collaborative computing platform receives a trusted data computation request sent by a terminal device. The trusted data computation request includes an identifier of the trusted data to be computed and key information corresponding to the computation model to be used. The virtualized trusted collaborative computing platform can use a preset matching model to obtain the identifier of a target computation model that matches the key information corresponding to the computation model to be used. It then queries and obtains a first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and a second trusted collaborative computing platform that matches the identifier of the target computation model. After obtaining the trusted data to be computed corresponding to the identifier of the trusted data to be computed from the first trusted collaborative computing platform, the platform sends the trusted data to be computed to the second trusted collaborative computing platform and requests the second trusted collaborative computing platform to perform computation processing on the trusted data to be computed according to the target computation model corresponding to the identifier of the target computation model, thereby obtaining the trusted data computation result sent by the second trusted collaborative computing platform. The virtualized trusted collaborative computing platform sends the trusted data computation result to the terminal device so that the user can be informed of the trusted data computation result. Furthermore, in this method, the first trusted collaborative computing platform and the second trusted collaborative computing platform can be the same trusted collaborative computing platform or different trusted collaborative computing platforms. Compared to existing technologies where each trusted collaborative computing platform can only perform calculations based on a single piece of trusted data provided by that platform, resulting in calculation results that fail to accurately and comprehensively reflect the characteristics of the trusted data, this application establishes a virtualized trusted collaborative computing platform that communicates with multiple trusted collaborative computing platforms. This allows trusted data from the trusted collaborative computing platform to circulate among these platforms, enabling the computing model provided by the platform that is best suited to process the trusted data to handle it. Consequently, the calculation results can accurately and comprehensively reflect the characteristics of the trusted data, thereby improving the user experience. Attached Figure Description
[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0040] Figure 1 A system architecture diagram of a trusted data processing method provided in this application;
[0041] Figure 2 A flowchart illustrating an embodiment of a trusted data processing method provided in this application;
[0042] Figure 3 A flowchart illustrating a second embodiment of a trusted data processing method provided in this application;
[0043] Figure 4 A flowchart illustrating a third embodiment of a trusted data processing method provided in this application;
[0044] Figure 5 A schematic diagram of the structure of an embodiment of a trusted data processing apparatus provided in this application;
[0045] Figure 6 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation
[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments made by those skilled in the art under the guidance of these embodiments are within the scope of protection of this application.
[0047] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0048] In the existing technology, each trusted collaborative computing platform provides different trusted data. The trusted collaborative computing platform can only use the computing model of the trusted collaborative computing platform to perform calculations on the trusted data provided by the trusted collaborative computing platform. As a result, each trusted collaborative computing platform can only perform calculations based on a single trusted data, which leads to the calculation results of the trusted data failing to accurately and comprehensively reflect the characteristics of the trusted data.
[0049] To address the problems existing in the prior art, the technical concept of this application is as follows: A virtualized trusted collaborative computing platform is used to uniformly manage trusted collaborative computing platforms provided by multiple vendors, so that trusted data from multiple trusted collaborative computing platforms can flow between them. This allows the computing model provided by the trusted collaborative computing platform that is more suitable for processing the trusted data to process the trusted data and obtain trusted data computing results.
[0050] The following is a detailed description of a trusted data processing scheme proposed in this application.
[0051] Figure 1 A system architecture diagram of a trusted data processing method provided in this application is shown below. Figure 1 As shown, the system architecture may include: terminal device 101, virtualized trusted collaborative computing platform 102, and multiple trusted collaborative computing platforms ( Figure 1 Three trusted collaborative computing platforms are shown, namely trusted collaborative computing platform 103, trusted collaborative computing platform 104, and trusted collaborative computing platform 105. Among them, the virtualized trusted collaborative computing platform 102 is communicatively connected to trusted collaborative computing platform 103, trusted collaborative computing platform 104, and trusted collaborative computing platform 105, respectively.
[0052] Additionally, it should be noted that the virtualized trusted collaborative computing platform 102 is a platform that uses software definition to virtualize and manage multiple trusted collaborative computing platforms, ultimately providing unified external service capabilities.
[0053] In addition, it should be noted that the trusted collaborative computing platform 103, trusted collaborative computing platform 104 and trusted collaborative computing platform 105 can be different trusted collaborative computing platforms provided by three different manufacturers, or they can be different trusted collaborative computing platforms provided by the same manufacturer.
[0054] It should be noted that, Figure 1 This is merely a system architecture diagram of a trusted data processing method provided in an embodiment of this application. This embodiment does not represent... Figure 1 The document does not limit the actual form of the various devices included, nor does it specify the form of the devices. Figure 1 The interaction methods between devices are limited, and can be set according to actual needs in the specific application of the solution.
[0055] The technical solution of this application will now be described in detail through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.
[0056] Figure 2 This is a flowchart illustrating an embodiment of a trusted data processing method provided in this application.
[0057] See Figure 2 The specific steps for processing this trusted data include:
[0058] Step S201: Receive a trusted data calculation request sent by the terminal device.
[0059] In this embodiment, the virtualized trusted collaborative computing platform can receive trusted data computing requests sent by terminal devices through interfaces such as APIs and SDKs. The trusted data computing request includes the identifier of the trusted data to be computed and the key information corresponding to the computing model to be used.
[0060] It should be noted that the terminal device can be equipped with a visual interface displaying multiple selectable parameters. The user determines the required parameters based on their trusted data computation needs. The terminal device then obtains the trusted data computation requirement information based on the user's selected parameters and generates a trusted data computation request accordingly.
[0061] Step S202: Based on the trusted data calculation request, use a preset matching model to obtain the identifier of the target calculation model that matches the key information corresponding to the calculation model to be used.
[0062] The virtualized trusted collaborative computing platform stores a preset matching model, which has been pre-trained and processed. The platform can use this preset matching model to process the key information of the computing model to be used in a trusted data computing request, and obtain the identifier of the target computing model that matches the key information of the computing model to be used.
[0063] Understandably, the identifier of the target computing model is a unique ID of the target computing model. Optionally, the identifier of the target computing model can be the name of the target computing model, for example, the name of the target computing model is "Deep Model"; alternatively, the identifier of the target computing model can be the serial number of the target computing model, for example, the identifier of the target computing model can be "3,2" to indicate that the target computing model is the second computing model in the third trusted collaborative computing platform.
[0064] It should be noted that the embodiments of this application do not specifically limit the identifier of the target computing model, and can be selected according to the actual situation.
[0065] Step S203: Query and obtain the first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and query and obtain the second trusted collaborative computing platform that matches the identifier of the target computing model.
[0066] The trusted collaborative computing platform stores trusted data and identifiers representing that trusted data. It also stores computational models and identifiers representing those models. The trusted collaborative computing platform sends the identifiers of the trusted data and computational models stored on its platform to the virtualized trusted collaborative computing platform, enabling the virtualized platform to establish a mapping between the identifiers of the trusted data and the platform itself, and vice versa. Additionally, the trusted collaborative computing platform can also send its own name to the virtualized platform.
[0067] After the virtualized trusted collaborative computing platform obtains the identifier of the trusted data to be computed sent by the terminal device, it can query the relationship between the identifier of the trusted data and the trusted collaborative computing platform, and obtain the first trusted collaborative computing platform that matches the identifier of the trusted data to be computed.
[0068] After obtaining the identifier of the target computing model on the virtualized trusted collaborative computing platform, the correspondence between the identifier of the above computing model and the trusted collaborative computing platform can be queried to obtain the second trusted collaborative computing platform that matches the identifier of the target computing model.
[0069] It should be noted that the trusted collaborative computing platform that matches the identifier of the target computing model and the trusted collaborative computing platform that matches the identifier of the trusted data to be computed can be the same trusted collaborative computing platform or different trusted collaborative computing platforms. That is, the first trusted collaborative computing platform and the second trusted collaborative computing platform may be the same or different.
[0070] Step S204: Obtain the trusted data to be computed corresponding to the identifier of the trusted data to be computed from the first trusted collaborative computing platform, and request the second trusted collaborative computing platform to perform computation processing on the trusted data to be computed according to the target computing model corresponding to the identifier of the target computing model, and obtain the trusted data computation result.
[0071] After determining the first trusted collaborative computing platform to which the trusted data to be computed belongs, the virtualized trusted collaborative computing platform can send a trusted data acquisition request to the first trusted collaborative computing platform to obtain the trusted data to be computed sent by the first trusted collaborative computing platform. The trusted data acquisition request includes the identifier of the trusted data to be computed.
[0072] After receiving the trusted data to be computed from the first trusted collaborative computing platform, the virtualized trusted collaborative computing platform can generate a computing model usage request. This request includes the trusted data to be computed and an identifier for the target computing model. The virtualized trusted collaborative computing platform then sends the computing model usage request to a second trusted collaborative computing platform that matches the target computing model. This allows the second trusted collaborative computing platform to perform computation on the trusted data according to the target computing model corresponding to the identifier, thereby obtaining the computation result.
[0073] After the virtualized trusted collaborative computing platform processes the trusted data to be computed provided by the first trusted collaborative computing platform with the help of the second trusted collaborative computing platform, it can obtain the trusted data computation results sent by the second trusted collaborative computing platform.
[0074] Step S205: Send the trusted data calculation results to the terminal device.
[0075] After obtaining the trusted data calculation results sent by the second trusted collaborative computing platform, the virtualized trusted collaborative computing platform can send the trusted data calculation results to the terminal device so that the terminal device's visual interface can display the trusted data calculation results.
[0076] In addition, when the virtualized trusted collaborative computing platform sends trusted data computing results to the terminal device, it can also send the name of the first trusted collaborative computing platform, the name of the second trusted collaborative computing platform, and the identifier (name) of the target computing model to the terminal device, so that the above information can be displayed on the visual interface of the terminal device.
[0077] In this embodiment, the virtualized trusted collaborative computing platform receives a trusted data computation request sent by a terminal device. The trusted data computation request includes an identifier of the trusted data to be computed and key information corresponding to the computation model to be used. Based on the trusted data computation request, the virtualized trusted collaborative computing platform uses a preset matching model to obtain the identifier of a target computation model that matches the key information corresponding to the computation model to be used. The virtualized trusted collaborative computing platform queries and obtains a first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and queries and obtains a second trusted collaborative computing platform that matches the identifier of the target computation model. After obtaining the trusted data to be computed corresponding to the identifier of the trusted data to be computed from the first trusted collaborative computing platform, the platform sends the trusted data to be computed to the second trusted collaborative computing platform and requests the second trusted collaborative computing platform to perform computation processing on the trusted data to be computed according to the target computation model corresponding to the identifier of the target computation model, thereby obtaining the trusted data computation result sent by the second trusted collaborative computing platform. The virtualized trusted collaborative computing platform sends the trusted data computation result to the terminal device so that the user can know the trusted data computation result. Furthermore, in this method, the first and second trusted collaborative computing platforms can be the same trusted collaborative computing platform or different trusted collaborative computing platforms. Compared to existing technologies where each trusted collaborative computing platform can only perform calculations based on a single trusted data provided by that platform, resulting in the calculation results failing to accurately and comprehensively reflect the characteristics of the trusted data, this application allows the use of multiple computational models from multiple trusted collaborative computing platforms to perform calculations on trusted data provided by multiple trusted collaborative computing platforms. This enables multi-platform access to trusted data from multiple trusted collaborative computing platforms, facilitating the flow of trusted data across multiple trusted collaborative computing platforms. This allows the computational model provided by the trusted collaborative computing platform best suited for processing the trusted data to handle it, ensuring that the calculation results accurately and comprehensively reflect the characteristics of the trusted data, thus improving the user experience.
[0078] The training process of the matching model will be explained below through Example 2.
[0079] Figure 3 A flowchart illustrating a second embodiment of a trusted data processing method provided in this application; the trusted data processing method specifically includes the following steps:
[0080] Step S301: Establish the initial matching model.
[0081] In this embodiment, a long short-term memory network model can be used as the initial matching model.
[0082] Specifically, the Long Short-Term Memory (LSTM) network model includes four gating systems: the forget gate, the input gate, the candidate memory cells, and the output gate. Each gating system is calculated using the following formula:
[0083] h (t) =o t *tanh(c t (1)
[0084] o t =sigmoid(W o x t +U o h (t-1) (2)
[0085]
[0086] f t =sigmoid(W f x t +U f h (t-1) (4)
[0087] i t =sigmoid(W i x t +U i h (t-1) (5)
[0088]
[0089] Among them, W o The input weights for the output gate; W f W represents the input weights for the forget gate. i The input weights of the input gate; W c Input weights for candidate memory cells; U o U represents the loop weight of the output gate; f U represents the circular weight of the forget gate; i U represents the recurrent weights of the input gate; c h represents the recurrent weights of candidate memory cells. (t-1) c is the previous output of the Long Short-Term Memory network model; (t-1) For the previous memory in the Long Short-Term Memory network model; c t For the current memory in the Long Short-Term Memory network model; x t This is the current input to the Long Short-Term Memory (LSTM) network model; h (t) This is the current output of the Long Short-Term Memory (LSTM) network model.
[0090] Step S302: Obtain the identifiers of the computing models uploaded by multiple trusted collaborative computing platforms, as well as the key information corresponding to the computing models.
[0091] Each trusted collaborative computing platform contains one or more computing models. The virtualized trusted collaborative computing platform can obtain the identifiers of each computing model uploaded by multiple trusted collaborative computing platforms through API or SDK interfaces, and obtain the key information of each computing model uploaded by multiple trusted collaborative computing platforms through API or SDK interfaces. The key information of the computing model includes the identifier of the computing model, the input format of the computing model, the algorithm used by the computing model, and the use case of the computing model.
[0092] Step S303: Train the initial matching model according to the identifier of the calculation model and the key information corresponding to the calculation model to obtain the preset matching model.
[0093] After obtaining the key information corresponding to the computing model uploaded by the virtualized trusted collaborative computing platform, each piece of information in the key information of the computing model can be segmented and labeled, and useless information can be removed, while key words can be retained, so as to form a keyword set of key words corresponding to the key information of the computing model.
[0094] After obtaining the identifiers of the computing models uploaded by the virtualized trusted collaborative computing platform and determining the keyword set based on the key information corresponding to the computing models, correlation analysis can be performed on the identifiers of multiple computing models and the multiple keyword sets determined based on the key information of multiple computing models to establish the correspondence between the identifiers of computing models and the keyword sets.
[0095] Furthermore, the virtualized trusted collaborative computing platform can perform matrix transformation on the keyword set to obtain a keyword matrix, and construct a multi-dimensional vector based on this keyword matrix. The platform can then input this multi-dimensional vector into an initial matching model to obtain an actual output result. Based on the correspondence between the identifiers of the computing models and the keyword sets, the platform can determine the identifier of the computing model corresponding to the keyword set corresponding to the multi-dimensional vector, and compare this identifier with the actual output result of the matching model to obtain the error. The platform can then adjust the weights of the initial matching model based on the error until the error is below a preset threshold, thereby obtaining a preset matching model.
[0096] In this embodiment, the virtualized trusted collaborative computing platform can establish an initial matching model and acquire the identifiers of computing models uploaded by multiple trusted collaborative computing platforms, as well as the key information corresponding to the computing models. Based on the identifiers and key information of the computing models, the initial matching model is trained to obtain a preset matching model. The virtualized trusted collaborative computing platform can directly determine the target computing model that meets the user's needs based on the trained matching model and the trusted data computing request, improving the accuracy of determining the computing model and ensuring that the computing results of the trusted data accurately and comprehensively reflect the characteristics of the trusted data.
[0097] Figure 4 This is a flowchart illustrating a third embodiment of a trusted data processing method provided in this application.
[0098] See Figure 4 The specific steps for processing this trusted data include:
[0099] Step S401: Receive a trusted data calculation request sent by the terminal device.
[0100] The trusted data computation request includes the identifier of the trusted data to be computed, as well as the key information corresponding to the computation model to be used.
[0101] Step S402: Based on the trusted data calculation request, use a preset matching model to obtain the identifier of the first target calculation model that matches the key information corresponding to the calculation model to be used.
[0102] Step S403: Send the identifier of the first target calculation model to the terminal device.
[0103] In this embodiment, when the virtualized trusted collaborative computing platform obtains the identifier of the first target computing model, it can send the identifier of the first target computing model to the terminal device so that the visual interface of the terminal device displays the identifier of the first target computing model, so that the user can know the computing model matched by the virtualized trusted collaborative computing platform.
[0104] In addition, the virtualized trusted collaborative computing platform can also send the input format of the first target computing model, the algorithm used by the first target computing model, and the application scenario of the first target computing model to the terminal device so that the terminal device's visual interface can display the above information.
[0105] Step S404: Receive the calculation model confirmation information sent by the terminal device.
[0106] After the terminal device obtains the identifier of the computing model of the user's input, it generates computing model confirmation information based on the identifier of the computing model of the user's input, and sends the computing model confirmation information to the virtualized trusted collaborative computing platform.
[0107] Step S405: Determine whether the identifier of the user requirement calculation model is the same as the identifier of the first target calculation model.
[0108] If it is determined that the identifier of the computational model for user needs is different from the identifier of the first target computational model, then proceed to step S406; if it is determined that the identifier of the computational model for user needs is the same as the identifier of the first target computational model, then proceed to step S412.
[0109] Step S406: Adjust the preset matching model.
[0110] In this embodiment, if the virtualization trusted collaborative computing platform determines that the identifier of the computing model required by the user is different from the identifier of the first target computing model, it indicates that the computing model matched by the current matching model based on the trusted data computing request does not meet the user's requirements. The virtualization trusted collaborative computing platform adjusts the preset matching model based on the identifier of the computing model required by the user and the key information corresponding to the computing model to be used, so that the computing model matched by the adjusted matching model based on the trusted data computing request meets the user's requirements.
[0111] Step S407: Based on the trusted data calculation request, use the adjusted matching model to obtain the identifier of the second target calculation model that matches the key information corresponding to the calculation model to be used.
[0112] The virtualized trusted collaborative computing platform can process the key information corresponding to the computing model to be used based on the acquired trusted data computing request, using an adjusted matching model, and obtain the identifier of the second target computing model that matches the key information corresponding to the computing model to be used.
[0113] Step S408: Query and obtain the first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and query and obtain the third trusted collaborative computing platform that matches the identifier of the second target computing model.
[0114] The virtualized trusted collaborative computing platform can query and obtain the first trusted collaborative computing platform whose identifier matches the trusted data to be computed, in order to obtain the identifier of the first trusted collaborative computing platform.
[0115] The virtualized trusted collaborative computing platform can query and obtain the identifier of the third trusted collaborative computing platform that matches the second target computing model.
[0116] In addition, the virtualized trusted collaborative computing platform can also query and obtain the input format of the second target computing model, the algorithm used by the second target computing model, and the application scenarios of the second target computing model.
[0117] Step S409: Obtain the trusted data to be computed from the first trusted collaborative computing platform, which corresponds to the identifier of the trusted data to be computed.
[0118] Step S410: Request the third trusted collaborative computing platform to perform computation processing on the trusted data to be computed according to the second target computing model corresponding to the identifier of the second target computing model, and obtain the trusted data computation result.
[0119] Step S411: Send the trusted data calculation results to the terminal device.
[0120] In this embodiment, when the virtualized trusted collaborative computing platform obtains the trusted data calculation results, it can send the trusted data calculation results to the terminal device so that the terminal device's visual interface can display the trusted data calculation results.
[0121] In addition, the virtualized trusted collaborative computing platform can also send the identifier of the first trusted collaborative computing platform, the identifier of the third trusted collaborative computing platform to which the second target computing model belongs, the input format of the second target computing model, the algorithm used by the second target computing model, and the usage scenario of the second target computing model to the terminal device, so that the terminal device's visualization interface displays the above information when displaying trusted data computing results.
[0122] Step S412: Query and obtain the first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and query and obtain the second trusted collaborative computing platform that matches the identifier of the target computing model.
[0123] Step S413: Obtain the trusted data to be computed from the first trusted collaborative computing platform, which corresponds to the identifier of the trusted data to be computed.
[0124] Step S414: Request the second trusted collaborative computing platform to perform computation processing on the trusted data to be computed according to the first target computing model corresponding to the identifier of the first target computing model, and obtain the trusted data computation result.
[0125] Step S415: Send the trusted data calculation results to the terminal device.
[0126] In this embodiment, the identifier of the target computing model matched by the preset matching model according to the trusted data computing request can be sent to the terminal device so that the user can judge whether the target computing model meets the expected requirements. If the target computing model does not meet the user's expected requirements, the matching model can be adjusted according to the computing model required by the user. This makes the computing model for processing trusted data more in line with the user's needs, and the computing results of trusted data can accurately and comprehensively reflect the characteristics of trusted data, thereby improving the user experience.
[0127] The following are embodiments of the apparatus of this application, which can be used to execute the embodiments of the method of this application. For details not disclosed in the embodiments of the apparatus of this application, please refer to the embodiments of the method of this application.
[0128] Figure 5 This is a schematic diagram of the structure of an embodiment of a trusted data processing device provided in this application; as shown below. Figure 5 As shown, the trusted data processing device 50 includes a receiving module 51, a processing module 52, and a sending module 53. The receiving module 51 receives a trusted data calculation request sent by a terminal device. The trusted data calculation request includes an identifier of the trusted data to be calculated and key information corresponding to the calculation model to be used. The processing module 52, according to the trusted data calculation request, uses a preset matching model to obtain the identifier of a target calculation model that matches the key information corresponding to the calculation model to be used. The processing module 52 is also used to query and obtain a first trusted collaborative computing platform that matches the identifier of the trusted data to be calculated, and to query and obtain a second trusted collaborative computing platform that matches the identifier of the target calculation model. The processing module 52 is also used to obtain the trusted data to be calculated corresponding to the identifier of the trusted data to be calculated from the first trusted collaborative computing platform, and to request the second trusted collaborative computing platform to perform calculation processing on the trusted data to be calculated according to the target calculation model corresponding to the identifier of the target calculation model, and obtain the trusted data calculation result. The sending module 53 sends the trusted data calculation result to the terminal device. The first trusted collaborative computing platform and the second trusted collaborative computing platform may be the same or different.
[0129] The trusted data processing apparatus provided in this application embodiment can execute the technical solutions shown in the above method embodiments. Its implementation principle and beneficial effects are similar, and will not be repeated here.
[0130] In a preferred embodiment, the processing module 52 is further configured to establish an initial matching model; the receiving module 51 is further configured to acquire the identifiers of the computing models uploaded by multiple trusted collaborative computing platforms, as well as the key information corresponding to the computing models; the processing module 52 is further configured to train the initial matching model based on the identifiers of the computing models and the key information corresponding to the computing models, so as to obtain a preset matching model.
[0131] The trusted data processing apparatus provided in this application embodiment can execute the technical solutions shown in the above method embodiments. Its implementation principle and beneficial effects are similar, and will not be repeated here.
[0132] In a preferred embodiment, the key information corresponding to the computational model includes the identifier of the computational model, the input format of the computational model, the algorithm used by the computational model, and the application scenario of the computational model.
[0133] The trusted data processing apparatus provided in this application embodiment can execute the technical solutions shown in the above method embodiments. Its implementation principle and beneficial effects are similar, and will not be repeated here.
[0134] Figure 6 This is a schematic diagram of the structure of an electronic device provided in this application. Figure 6 As shown, the electronic device 60 includes a processor 61, a memory 62, and a communication interface 63. The memory 62 is used to store executable instructions that can be executed by the processor 61. The processor 61 is configured to execute the technical solution of the virtualized trusted collaborative computing platform in any of the foregoing method embodiments by executing the executable instructions.
[0135] In a preferred embodiment, the memory 62 can be either standalone or integrated with the processor 61.
[0136] In a preferred embodiment, when the memory 62 is a device independent of the processor 61, the electronic device 60 may further include a bus for connecting the aforementioned devices.
[0137] The electronic device is used to execute the technical solution of the virtualized trusted collaborative computing platform in any of the aforementioned method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.
[0138] This application also provides a trusted data processing system, including a virtualized trusted collaborative computing platform and multiple trusted collaborative computing platforms, wherein the virtualized trusted collaborative computing platform is communicatively connected to the multiple trusted collaborative computing platforms; wherein, the virtualized trusted collaborative computing platform is used to execute the technical solution of the virtualized trusted collaborative computing platform in any of the foregoing method embodiments, and its implementation principle and technical effect are similar, and will not be described again here.
[0139] This application also provides a readable storage medium storing a computer program thereon, which, when executed by a processor, implements the technical solutions provided in any of the foregoing embodiments.
[0140] This application also provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the technical solutions provided in any of the foregoing method embodiments.
[0141] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.
Claims
1. A method for processing reliable data, characterized in that, The method is applied to a virtualized trusted collaborative computing platform, which is communicatively connected to multiple trusted collaborative computing platforms; the method includes: The system receives a trusted data computation request sent by a terminal device. The trusted data computation request includes the identifier of the trusted data to be computed and the key information corresponding to the computation model to be used. Based on the trusted data calculation request, a preset matching model is used to obtain the identifier of the target calculation model that matches the key information corresponding to the calculation model to be used; The system queries and retrieves a first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and queries and retrieves a second trusted collaborative computing platform that matches the identifier of the target computing model. The system obtains the trusted data to be calculated corresponding to the identifier of the trusted data to be calculated from the first trusted collaborative computing platform, and requests the second trusted collaborative computing platform to perform calculation processing on the trusted data to be calculated according to the target computing model corresponding to the identifier of the target computing model, and obtain the trusted data calculation result. The calculation result of the trusted data is sent to the terminal device; The first trusted collaborative computing platform and the second trusted collaborative computing platform may be the same or different.
2. The method for processing trusted data according to claim 1, characterized in that, Also includes: Establish an initial matching model; The identifiers of the computing models uploaded by the multiple trusted collaborative computing platforms, as well as the key information corresponding to the computing models, are obtained respectively. The initial matching model is trained based on the identifier of the computing model and the key information corresponding to the computing model to obtain the preset matching model.
3. The method for processing trusted data according to claim 1 or 2, characterized in that, The key information corresponding to the computing model includes the identifier of the computing model, the input format of the computing model, the algorithm used by the computing model, and the application scenario of the computing model.
4. A reliable data processing device, characterized in that, include: A virtualized trusted collaborative computing platform, which is communicatively connected to multiple trusted collaborative computing platforms; The receiving module is used to receive a trusted data calculation request sent by the terminal device. The trusted data calculation request includes the identifier of the trusted data to be calculated and the key information corresponding to the calculation model to be used. The processing module is used to obtain the identifier of the target computing model that matches the key information corresponding to the computing model to be used, based on the trusted data computing request and using a preset matching model. The processing module is further configured to query and obtain a first trusted collaborative computing platform that matches the identifier of the trusted data to be computed, and to query and obtain a second trusted collaborative computing platform that matches the identifier of the target computing model. The processing module is further configured to obtain the trusted data to be calculated corresponding to the identifier of the trusted data to be calculated from the first trusted collaborative computing platform, and request the second trusted collaborative computing platform to perform calculation processing on the trusted data to be calculated according to the target computing model corresponding to the identifier of the target computing model, and obtain the trusted data calculation result. A sending module is used to send the calculation result of the trusted data to the terminal device; The first trusted collaborative computing platform and the second trusted collaborative computing platform may be the same or different.
5. The trusted data processing apparatus according to claim 4, characterized in that, The processing module is also used to establish an initial matching model; The receiving module is also used to obtain the identifiers of the computing models uploaded by multiple trusted collaborative computing platforms, as well as the key information corresponding to the computing models. The processing module is further configured to train the initial matching model based on the identifier of the computing model and the key information corresponding to the computing model, so as to obtain the preset matching model.
6. The trusted data processing apparatus according to claim 4 or 5, characterized in that, The key information corresponding to the computing model includes the identifier of the computing model, the input format of the computing model, the algorithm used by the computing model, and the application scenario of the computing model.
7. An electronic device, characterized in that, include: Processor, memory, communication interface; The memory is used to store executable instructions that can be executed by the processor; The processor is configured to execute the trusted data processing method according to any one of claims 1 to 3 by executing the executable instructions.
8. A trusted data processing system, characterized in that, It includes a virtualized trusted collaborative computing platform and multiple trusted collaborative computing platforms, wherein the virtualized trusted collaborative computing platform is communicatively connected to the multiple trusted collaborative computing platforms; The virtualized trusted collaborative computing platform is used to execute the trusted data processing method according to any one of claims 1 to 3.
9. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method for processing trusted data as described in any one of claims 1 to 3.
10. A computer program product comprising a computer program that, when executed by a processor, implements the method for processing trusted data according to any one of claims 1 to 3.