A method, device, computer device and storage medium for determining a resource to be called out

Abstract

The application relates to a method and device for determining a call-out resource, a computer device and a storage medium. The method comprises the following steps: in response to a call-out resource determination instruction for a target service object, determining a data calculation scheduling task, and determining a data processing end, a result receiving end and a data calculation logic corresponding to each data processing end according to the data calculation scheduling task; obtaining to-be-processed service data, and performing sharding encryption on the to-be-processed service data to obtain at least one ciphertext sharding data; inputting each ciphertext sharding data into at least two data processing ends; and controlling each data processing end to calculate corresponding ciphertext sharding data according to the corresponding data calculation logic to obtain call-out resource quantity information; generating a call-out resource result list according to the call-out resource quantity information, and sending the call-out resource result list to the result receiving end. The method can improve the quantity accuracy of the call-out resource of a public resource platform to an enterprise.

Description

Technical Field

[0001] This application relates to the field of big data technology, and in particular to a method, apparatus, computer equipment, and storage medium for determining available resources. Background Technology

[0002] With the development of big data technology, the Internet of Things (IoT) has emerged. Through various possible network access methods, it enables ubiquitous connectivity between things and between things and people, achieving intelligent sensing, identification, and management of objects and processes. The IoT is an information carrier based on the internet, traditional telecommunications networks, etc., allowing all independently addressable ordinary physical objects to form an interconnected network. Simultaneously, as enterprises become more capable of utilizing new data flows, big data enables real-time and predictive decision-making, thereby automating these decisions.

[0003] In traditional technologies, supply chain resource interaction models are generally based on data such as enterprise interaction records, fixed resource information, and resource interaction information. The overall amount of resources a company can accept is determined through manual review and analysis. For the penetrating management of supply chain resource acceptability, resource acceptability is typically transferred through enterprise relationship networks, and resource allocation security control relies on manual on-site tracking and spot checks. First, enterprise data is usually processed manually, making it difficult to quickly and accurately verify its authenticity and accuracy, impacting business efficiency. Second, the quantity of resources allocated is judged based on the overall operation of the enterprise, making it impossible to pinpoint the exact production interaction stage. Third, public platforms cannot obtain real-time data across the entire supply chain, and the penetrating analysis of resource acceptability cannot accurately break down the supply and allocation amounts across the entire supply chain according to actual production conditions; it can only be assessed and allocated based on the overall relationship network of enterprises. This results in low accuracy in confirming the quantity of resources allocated from public resource platforms to enterprises. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining the number of resources transferred from a public resource platform to enterprises, which can improve the accuracy of the number of resources transferred from the platform to enterprises.

[0005] Firstly, this application provides a method for determining resource allocation. The method includes: responding to a resource allocation determination instruction for a target business object, determining a data computation scheduling task corresponding to the resource allocation determination instruction, and, based on the data computation scheduling task, determining a data processing terminal, a result receiving terminal, and data computation logic corresponding to each of the data processing terminals for the target object; acquiring pending business data corresponding to the data processing terminal, and performing fragmented encryption on the pending business data corresponding to the data processing terminal to obtain at least one encrypted fragmented data; the pending business data is used to describe the data of the target business object during business execution; inputting each encrypted fragmented data into at least two of the data processing terminals; controlling each data processing terminal to perform calculations on the corresponding encrypted fragmented data according to the corresponding data computation logic to obtain the resource allocation quantity information corresponding to the resource allocation determination instruction; generating a corresponding resource allocation result list based on the resource allocation quantity information, and sending the resource allocation result list to the result receiving terminal.

[0006] In one embodiment, the step of inputting each of the encrypted fragment data into at least two of the data processing terminals, and controlling each of the data processing terminals to perform calculations on the corresponding encrypted fragment data according to the corresponding data calculation logic to obtain the resource quantity information corresponding to the resource determination instruction, includes: determining the corresponding data calculation logic based on the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal in the data calculation scheduling task; inputting each of the encrypted fragment data into the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, and performing at least one collaborative calculation according to the data calculation logic corresponding to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal to obtain the enterprise-side resource quantity information, the supplier-side resource quantity information, and the bank-side resource quantity information; merging the enterprise-side resource quantity information, the supplier-side resource quantity information, and the bank-side resource quantity information to obtain the resource quantity information corresponding to the resource determination instruction.

[0007] In one embodiment, the step of inputting each of the encrypted fragmented data to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal respectively includes: inputting the enterprise production order number, physical associated order number, enterprise order product type, physical type, and physical status information from the encrypted fragmented data to the enterprise data processing terminal; inputting the supplier agreement number, supply item agreement number, and item warehouse status from the encrypted fragmented data to the supplier data processing terminal; and inputting the number of enterprise supply item agreement resources, available resource ratio parameters, and the number of supply item resources from at least two suppliers from the encrypted fragmented data to the bank data processing terminal.

[0008] In one embodiment, the step of performing at least one collaborative calculation based on the data calculation logic corresponding to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal to obtain the enterprise terminal resource retrieval quantity information, the supplier terminal resource retrieval quantity information, and the bank terminal resource retrieval quantity information, respectively, includes: determining, based on the data calculation logic corresponding to the enterprise data processing terminal, whether the enterprise production order number is equal to the physical associated order number, and whether the enterprise order product type is equal to the physical type, so as to... The system determines whether the physical condition of the goods is normal, thereby obtaining the quantity of resources retrieved from the enterprise side. Based on the data calculation logic corresponding to the supplier data processing terminal, it determines whether the supplier agreement number is equal to the supply item agreement number and whether the item warehouse status is "sent," thereby obtaining the quantity of resources retrieved from the supplier side. Based on the data calculation logic corresponding to the bank data processing terminal, it multiplies the number of enterprise supply item agreement resources by the available resource ratio parameter to obtain the intermediate retrieved resource quantity information. Finally, it subtracts the sum of at least two supplier supply item resource quantities from the intermediate retrieved resource quantity information to obtain the bank's retrieved resource quantity information.

[0009] In one embodiment, obtaining the business data to be processed corresponding to the data processing terminal includes: extracting the enterprise production data from the enterprise data processing terminal, extracting the supplier supply data from the supplier data processing terminal, and extracting the resource interaction system data from the bank data processing terminal according to the preset data service and data field definitions of the data processing terminal; and combining the enterprise production data, the supplier supply data, and the resource interaction system data to obtain the business data to be processed corresponding to the data processing terminal.

[0010] In one embodiment, the method further includes: acquiring unprocessed business data corresponding to the resource retrieval determination instruction based on at least one Internet of Things information collection platform, wherein the unprocessed business data is obtained by standardizing digital information obtained by an object sensing device; cleaning the unprocessed business data to remove invalid data, and analyzing the data obtained from cleaning the invalid data to obtain the object status information to obtain the business data to be processed.

[0011] In one embodiment, the step of cleaning the unprocessed business data to remove invalid data and analyzing the true nature of the data obtained from the invalid data cleaning to obtain the business data to be processed includes: filtering the unchanged item digital information corresponding to the unprocessed business data to obtain unprocessed valid data; performing authenticity analysis on the item status information in the unprocessed valid data and deleting data that does not conform to authenticity after analysis to obtain unprocessed real data; and converting the unprocessed real data according to a preset standardization to obtain the business data to be processed.

[0012] Secondly, this application also provides a resource retrieval determination device. The device includes: a task determination module, configured to, in response to a resource retrieval determination instruction for a target business object, determine a data computation scheduling task corresponding to the resource retrieval determination instruction, and, based on the data computation scheduling task, determine a data processing terminal, a result receiving terminal, and data computation logic corresponding to each of the data processing terminals for the target object; a data processing module, configured to acquire pending business data corresponding to the data processing terminal, and to perform segmented encryption on the pending business data corresponding to the data processing terminal to obtain at least one encrypted segmented data; the pending business data is used to describe the data of the target business object during business execution; a data computation module, configured to input each encrypted segmented data into at least two of the data processing terminals respectively; and control each of the data processing terminals to perform calculations on the corresponding encrypted segmented data according to the corresponding data computation logic to obtain the resource retrieval quantity information corresponding to the resource retrieval determination instruction; and a resource retrieval determination module, configured to generate a corresponding resource retrieval result list based on the resource retrieval quantity information, and send the resource retrieval result list to the result receiving terminal.

[0013] In one embodiment, the data calculation module is further configured to determine the corresponding data calculation logic for each of the enterprise data processing terminal, supplier data processing terminal, and bank data processing terminal in the data calculation scheduling task; input each of the encrypted fragmented data to the enterprise data processing terminal, supplier data processing terminal, and bank data processing terminal respectively, and perform at least one collaborative calculation according to the data calculation logic corresponding to each of the enterprise data processing terminal, supplier data processing terminal, and bank data processing terminal to obtain the enterprise terminal resource retrieval quantity information, the supplier terminal resource retrieval quantity information, and the bank terminal resource retrieval quantity information; merge the enterprise terminal resource retrieval quantity information, the supplier terminal resource retrieval quantity information, and the bank terminal resource retrieval quantity information to obtain the resource retrieval quantity information corresponding to the resource retrieval determination instruction.

[0014] In one embodiment, the data calculation module is further configured to input the enterprise production order number, physical associated order number, enterprise order product type, physical type, and physical status information from the encrypted fragmented data to the enterprise data processing terminal; input the supplier agreement number, supply item agreement number, and item warehouse status from the encrypted fragmented data to the supplier data processing terminal; and input the number of enterprise supply item agreement resources, callable resource ratio parameters, and the number of supply item resources from at least two suppliers from the encrypted fragmented data to the bank data processing terminal.

[0015] In one embodiment, the data calculation module is further configured to, based on the data calculation logic corresponding to the enterprise data processing terminal, determine whether the enterprise production order number is equal to the physical associated order number, whether the enterprise order product type is equal to the physical type, and whether the physical status is normal, to obtain the enterprise-side resource quantity information; based on the data calculation logic corresponding to the supplier data processing terminal, determine whether the supplier agreement number is equal to the supply item agreement number and whether the item warehouse status is "sent", to obtain the supplier-side resource quantity information; based on the data calculation logic corresponding to the bank data processing terminal, multiply the enterprise supply item agreement resource quantity by the callable resource ratio parameter to obtain intermediate resource quantity information; and subtract the sum of at least two supplier supply item resource quantities from the intermediate resource quantity information to obtain the bank-side resource quantity information.

[0016] In one embodiment, the data processing module is further configured to extract enterprise production data from the enterprise data processing terminal, supplier supply data from the supplier data processing terminal, and resource interaction system data from the bank data processing terminal according to the preset data service and data field definitions of the data processing terminal; and combine the enterprise production data, the supplier supply data, and the resource interaction system data to obtain the business data to be processed corresponding to the data processing terminal.

[0017] In one embodiment, the data acquisition module is used to acquire unprocessed business data corresponding to the resource retrieval determination instruction based on at least one Internet of Things information collection platform. The unprocessed business data is obtained by standardizing digital information obtained by an object sensing device. The unprocessed business data is then cleaned of invalid data, and the data obtained from the invalid data cleaning is analyzed for object status information to obtain the business data to be processed.

[0018] In one embodiment, the data acquisition module is further configured to filter the unchanged item digital information corresponding to the unprocessed business data to obtain unprocessed valid data; perform authenticity analysis on the item status information in the unprocessed valid data, and delete the data that does not conform to authenticity after analysis to obtain unprocessed real data; and convert the unprocessed real data according to a preset standardization to obtain the business data to be processed.

[0019] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program, performs the following steps: in response to a resource retrieval determination instruction for a target business object, determines a data computation scheduling task corresponding to the resource retrieval determination instruction, and, based on the data computation scheduling task, determines a data processing terminal, a result receiving terminal, and data computation logic corresponding to each of the data processing terminals for the target object; acquires the business data to be processed corresponding to the data processing terminal, and performs fragmented encryption on the business data to be processed corresponding to the data processing terminal to obtain at least one encrypted fragmented data; the business data to be processed is used to describe the data of the target business object during business execution; inputs each of the encrypted fragmented data into at least two of the data processing terminals respectively; and controls each of the data processing terminals to perform calculations on the corresponding encrypted fragmented data according to the corresponding data computation logic to obtain the resource retrieval quantity information corresponding to the resource retrieval determination instruction; generates a corresponding resource retrieval result list based on the resource retrieval quantity information, and sends the resource retrieval result list to the result receiving terminal.

[0020] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps: in response to a resource retrieval determination instruction for a target business object, determines a data computation scheduling task corresponding to the resource retrieval determination instruction, and, based on the data computation scheduling task, determines a data processing terminal, a result receiving terminal, and data computation logic corresponding to each of the data processing terminals for the target object; acquires the business data to be processed corresponding to the data processing terminal, and performs fragmented encryption on the business data to be processed corresponding to the data processing terminal to obtain at least one encrypted fragmented data; the business data to be processed is used to describe the data of the target business object during business execution; inputs each of the encrypted fragmented data into at least two of the data processing terminals respectively; and controls each of the data processing terminals to perform calculations on the corresponding encrypted fragmented data according to the corresponding data computation logic to obtain the number of resources retrieved corresponding to the resource retrieval determination instruction; generates a corresponding list of retrieved resource results based on the number of retrieved resources, and sends the list of retrieved resource results to the result receiving terminal.

[0021] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps: in response to a resource retrieval determination instruction for a target business object, determines a data computation scheduling task corresponding to the resource retrieval determination instruction, and, based on the data computation scheduling task, determines a data processing terminal, a result receiving terminal, and data computation logic corresponding to each of the data processing terminals for the target object; acquires the business data to be processed corresponding to the data processing terminal, and performs fragmented encryption on the business data to be processed corresponding to the data processing terminal to obtain at least one encrypted fragmented data; the business data to be processed is used to describe the data of the target business object during business execution; inputs each of the encrypted fragmented data into at least two of the data processing terminals respectively; and controls each of the data processing terminals to perform calculations on the corresponding encrypted fragmented data according to the corresponding data computation logic to obtain the resource retrieval quantity information corresponding to the resource retrieval determination instruction; generates a corresponding resource retrieval result list based on the resource retrieval quantity information, and sends the resource retrieval result list to the result receiving terminal.

[0022] The aforementioned method, apparatus, computer equipment, storage medium, and computer program product for determining outgoing resources, in response to an outgoing resource determination instruction for a target business object, determine the data calculation scheduling task corresponding to the outgoing resource determination instruction, and, based on the data calculation scheduling task, determine the data processing end, result receiving end, and data calculation logic corresponding to each data processing end for the target object; acquire the business data to be processed corresponding to the data processing end, and encrypt the business data to be processed corresponding to the data processing end in segments to obtain at least one encrypted segment data; the business data to be processed is used to describe the data of the target business object in the process of executing business; each encrypted segment data is input into at least two data processing ends; and each data processing end is controlled to calculate the corresponding encrypted segment data according to the corresponding data calculation logic to obtain the outgoing resource quantity information corresponding to the outgoing resource determination instruction; a corresponding outgoing resource result list is generated based on the outgoing resource quantity information, and the outgoing resource result list is sent to the result receiving end.

[0023] By integrating the Internet of Things (IoT) and multi-party secure computation technology into the supply chain resource interaction service system corresponding to the public resource platform, the digital information on the quantity of supply chain enterprises and physical resources can be processed automatically, intelligently, and precisely. Through secure fusion and computation of multi-party data, while protecting the data privacy of all parties, it can overcome the shortcomings of not being able to automatically obtain effective data for business anomalies and precise control of resource allocation. It effectively supports the anomaly management of resource allocation through the supply chain, the precise calculation and splitting of resource allocation, reduces the supply chain resource allocation anomaly and management costs of the public service platform, improves the resource interaction service level of the public service platform for supply chain enterprises, and increases the accuracy of the quantity of resources allocated from the public resource platform to enterprises. Attached Figure Description

[0024] Figure 1 This is an application environment diagram of the resource determination method in one embodiment;

[0025] Figure 2 This is a flowchart illustrating a method for determining the resources to be retrieved in one embodiment;

[0026] Figure 3 This is a flowchart illustrating a method for retrieving resource quantity information in one embodiment;

[0027] Figure 4 This is a flowchart illustrating the encrypted fragmented data input data processing method in one embodiment.

[0028] Figure 5 This is a flowchart illustrating the data processing logic method executed by the data processing terminal in one embodiment.

[0029] Figure 6This is a flowchart illustrating a method for obtaining business data to be processed in one embodiment;

[0030] Figure 7 This is a flowchart illustrating a method for preprocessing unprocessed business data in one embodiment;

[0031] Figure 8 This is a flowchart illustrating the preprocessing method for unprocessed business data in another embodiment;

[0032] Figure 9 This is a flowchart illustrating the resource determination method in another embodiment;

[0033] Figure 10 This is a flowchart illustrating the method for obtaining business data to be processed in another embodiment;

[0034] Figure 11 This is a structural block diagram of the resource determination device in one embodiment;

[0035] Figure 12 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0037] The resource determination method provided in this application embodiment can be applied to, for example, Figure 1In the application environment shown, terminal 102 acquires data, server 104 receives the data from terminal 102 in response to the terminal 102's instructions, performs calculations on the acquired data, and transmits the calculation results back to terminal 102 for display. Terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed in the cloud or on other network servers. Server 104 responds to the resource retrieval instruction from terminal 102 for the target business object, determines the data computation scheduling task corresponding to the resource retrieval instruction, and, based on the data computation scheduling task, determines the data processing end, result receiving end, and data computation logic corresponding to each data processing end for the target object; acquires the business data to be processed corresponding to the data processing end, and performs fragmented encryption on the business data to be processed corresponding to the data processing end to obtain at least one encrypted fragmented data; the business data to be processed is used to describe the data of the target business object in the process of executing business; inputs each encrypted fragmented data into at least two data processing ends respectively; and controls each data processing end to perform calculations on the corresponding encrypted fragmented data according to the corresponding data computation logic to obtain the resource retrieval quantity information corresponding to the resource retrieval instruction; generates a corresponding resource retrieval result list based on the resource retrieval quantity information, and sends the resource retrieval result list to the result receiving end. Terminal 102 may be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, smart vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0038] In one embodiment, such as Figure 2 As shown, a method for determining the resources to be retrieved is provided, which is then applied to... Figure 1 Taking the server in the example, the following steps are included:

[0039] Step 202: In response to the resource allocation determination instruction for the target business object, determine the data computation scheduling task corresponding to the resource allocation determination instruction, and determine the data processing end, result receiving end, and data computation logic corresponding to each data processing end for the target object based on the data computation scheduling task.

[0040] The target business objects can be enterprises, companies, shops, offices, institutions, etc. that obtain resources from the public service platform, and the target business objects can use the obtained resources to conduct relevant resource interactions.

[0041] Among them, the resource allocation determination instruction can be a calculation instruction issued by the terminal to the server to calculate the specific number of resources to be allocated, based on the requirements of the target business object.

[0042] Among them, the data computing scheduling task can be a computing task used to calculate the amount of resources that the public service platform allocates to the target business object. To complete the computing task, at least one task condition needs to be determined, and specific logical calculations need to be performed by computing nodes.

[0043] The data processing end can be a sub-server in the server cluster used to perform computing tasks. Each data processing end corresponds to a computing node. The computing node is used to calculate the data after it has been sharded and encrypted by the server cluster, and to obtain some information about the amount of resources called up.

[0044] The result receiving end can be used to receive the calculated number of resources to be called out, and issue execution instructions to the terminal based on the resource call-out information.

[0045] Among them, the data calculation logic can be the calculation method used by each data processing end to calculate the amount of resources called out by each part based on the input data. Each data processing end has the same calculation method database, but when performing calculations, different data processing ends will call different calculation methods to perform calculations.

[0046] Specifically, the public resource platform initiates an instruction to determine the task of transferring resources from the supply chain, triggering secure calculations of multi-party data in the supply chain to determine the authenticity of the task and the quantity of resources transferred. Secure fusion calculations are performed using computer technology. The specific judgment logic is as follows: (1) Determine the authenticity and validity of the production agreement based on the status information of the physical resources. If there is authentic and reliable physical resource data and the status of the physical resources is normal, it is a reliable production agreement. (2) Cross-verify the agreement information. If the agreement information of the core production enterprise matches the agreement number of the upstream and downstream supply-transferring enterprises, and the agreement of the upstream and downstream supply-transferring enterprises matches the warehouse record of the item entry status, it is an authentic and normal production agreement. (3) Specifically calculate the resource quantity information in the agreement signed by the upstream and downstream supply-transferring enterprises. Based on the consistency matching and proportion calculation of the item proportion information of the core production enterprise's production agreement and the supply-transferring enterprise's production agreement, the core enterprise's production order evaluation of the transferred resource quantity is specifically divided into the upstream and downstream supply-transferring enterprises to guide the subsequent accurate transfer of resources by the public resource platform.

[0047] The data computation scheduling task is initiated. The scheduling task first obtains the relevant data security computation task definitions, including: the data processing end of the computation task, the data source algorithm defined by that data processing end, the result receiving end, the result data structure definition, and the data computation logic. Once the corresponding task data is acquired, the computation task is started, running the data acquisition service, the data computation service, and the result return service for each data processing end.

[0048] For example, in response to the resource allocation determination instruction order 1 for the target business object, the data calculation scheduling task A corresponding to the resource allocation determination instruction order 1 is determined, and based on the data calculation scheduling task A, the data processing terminal A1, the result receiving terminal A2, and the data calculation logic a1-a10 corresponding to each data processing terminal A1 are determined.

[0049] Step 204: Obtain the business data to be processed corresponding to the data processing terminal, and perform fragmented encryption on the business data to be processed corresponding to the data processing terminal to obtain at least one encrypted fragmented data.

[0050] The business data to be processed can be business data about enterprise production and operation extracted from IoT terminals. After processing, the data will be transmitted from the terminal to various data processing terminals of the server. Different parts of the data will be transmitted to different data processing terminals.

[0051] Among them, encrypted fragmented data can be data formed by fragmenting and encrypting the business data to be processed, which helps to reduce the risk of information leakage.

[0052] Specifically, the data acquisition service is run. (1) The data services deployed by the core production enterprise (enterprise data processing end), the upstream and downstream supplier-exporter enterprise production system end (supplier data processing end), and the bank end (bank data processing end) are run, and the business data of each data provider is read according to the data acquisition field definition configured in the system. This includes: (i) The data service deployed by the core enterprise production system end reads the following data: enterprise identity, production order number, order product type, total number of order resources, supplier agreement number, supplier agreement resource number, unique identifier of product item, product item status, and item associated order number. (ii) The data service deployed by the supplier production system end reads the following data: enterprise identity, supply agreement number, supply agreement resource number, item list, and item warehouse receipt status. (iii) The data service deployed by the bank system end reads the following data: enterprise identity, enterprise bank account, and digital information of physical assets on the Internet of Things platform. (2) The data acquired by each data provider is encrypted. After acquiring the data from the relevant data providers, the data services deployed on the production systems of each data provider perform data sharding and encryption. A secret sharing protocol for multi-party secure computation is used to encrypt and shard the data from each data provider. After encryption and sharding, the data is uploaded to the data computing nodes deployed by each participating data computing party for secure computation. Three data computing nodes are deployed: one node at the core enterprise (enterprise data processing end), a unified computing node for all suppliers (supplier data processing end), and a computing node at the bank (bank data processing end). Each party's data is encrypted and sharded into three copies, which are distributed to the three computing nodes for secure computation using the secret sharing protocol for multi-party secure computation, ensuring that no computing node can obtain the complete data and guaranteeing data security. Through the above processing steps, at least one encrypted shard of data is obtained.

[0053] Step 206: Input each encrypted fragment data into at least two data processing terminals; and control each data processing terminal to calculate the corresponding encrypted fragment data according to the corresponding data calculation logic to obtain the information on the number of resources to be retrieved corresponding to the resource retrieval determination instruction.

[0054] The resource quantity information can be obtained by calculating and analyzing the pending business data corresponding to the target business object, and is used to guide the public resource platform to allocate resources to the target business object.

[0055] Specifically, each data security computing engine node obtains all encrypted data sent by the data service, inputs each encrypted fragment into at least two data processing ends, and uses multi-party secure computing technology to achieve collaborative computing of encrypted fragment data from all parties based on the data computing logic deployed by the computing nodes corresponding to each data processing end. The specific data computing logic is as follows: (1) Verify the authenticity of the production order: Verify the order data. If [Enterprise Production Order Number] = [Physical Related Order Number] and [Enterprise Order Product Type] = [Physical Type] and [Physical Status] = "Normal", then the order is normal. Otherwise, the order is rejected from resource allocation, and the quantity of resources allocated by the enterprise is obtained. (2) Verify the production order data: If [Supplier Agreement Number] = [Supply Item Agreement Number] and the [Item Warehouse Status] of all items in the supplier's [Item List] = "Sent", then the order status is normal. Otherwise, the order is rejected from resource allocation, and the quantity of resources allocated by the supplier is obtained. (3) Calculate the total number of resources transferred out of production orders: Total number of resources transferred out M = [number of resources in the enterprise supply agreement] * R, where R is the resource ratio parameter setting for production orders in the supply chain; Calculate the total number of resources transferred out of the enterprise: Total number of resources transferred out of the first supplier M21 = [number of resources in the first supplier supply], Total number of resources transferred out of the second supplier M22 = [number of resources in the second supplier supply]; Total number of resources transferred out of the enterprise M1 = Enterprise supply agreement resource M - First supplier supply resource M21 - Second supplier supply resource M22, to obtain the information on the number of resources transferred out by the bank.

[0056] The resource quantity information from the enterprise, supplier, and bank sides is re-merged according to the data sharding rules to obtain the resource quantity information corresponding to the resource transfer confirmation instruction.

[0057] Step 208: Generate a corresponding list of retrieved resources based on the number of retrieved resources, and send the list of retrieved resources to the result receiving end.

[0058] The resource retrieval result list can be a table that records the number of resources retrieved for each target business object. It contains detailed information on the resources that can be retrieved for each target business object, so that the result receiving end can execute it.

[0059] Specifically, the bank financing results are output. Based on the enterprise and supplier [enterprise identity identifier], the public resource platform [enterprise identity identifier] is matched to obtain the corresponding enterprise's account information [enterprise bank account] on the public resource platform. The final output result list is {[enterprise bank account 1, enterprise resource allocation quantity 1], ..., [enterprise bank account X, enterprise resource allocation quantity X]}. The public resource platform's resource allocation system receives this returned result list, accurately allocates resources to the supply chain enterprises using the corresponding resource allocation method, and sends the resource allocation result list to the result receiving end for execution. The specific process and interaction for one method of determining resource allocation are as follows: Figure 9 As shown.

[0060] In the above-described method for determining outgoing resources, in response to an outgoing resource determination instruction for a target business object, the method determines the data computation scheduling task corresponding to the instruction, and based on the data computation scheduling task, determines the data processing end, result receiving end, and data computation logic corresponding to each data processing end for the target object; it acquires the business data to be processed corresponding to the data processing end, and performs fragmented encryption on the business data to be processed corresponding to the data processing end to obtain at least one encrypted fragmented data; the business data to be processed is used to describe the data of the target business object in the process of executing business; each encrypted fragmented data is input into at least two data processing ends; and each data processing end is controlled to perform calculations on the corresponding encrypted fragmented data according to the corresponding data computation logic to obtain the outgoing resource quantity information corresponding to the outgoing resource determination instruction; based on the outgoing resource quantity information, a corresponding outgoing resource result list is generated, and the outgoing resource result list is sent to the result receiving end.

[0061] By integrating the Internet of Things (IoT) and multi-party secure computation technology into the supply chain resource interaction service system corresponding to the public resource platform, the digital information on the quantity of supply chain enterprises and physical resources can be processed automatically, intelligently, and precisely. Through secure fusion and computation of multi-party data, while protecting the data privacy of all parties, it can overcome the shortcomings of not being able to automatically obtain effective data for business anomalies and precise control of resource allocation. It effectively supports the anomaly management of resource allocation through the supply chain, the precise calculation and splitting of resource allocation, reduces the supply chain resource allocation anomaly and management costs of the public service platform, improves the resource interaction service level of the public service platform for supply chain enterprises, and increases the accuracy of the quantity of resources allocated from the public resource platform to enterprises.

[0062] In one embodiment, such as Figure 3 As shown, each encrypted fragment of data is input into at least two data processing terminals; and each data processing terminal is controlled to calculate the corresponding encrypted fragment of data according to the corresponding data calculation logic to obtain the information on the number of resources to be retrieved corresponding to the resource retrieval determination instruction, including:

[0063] Step 302: Determine the corresponding data calculation logic based on the enterprise data processing end, supplier data processing end, and bank data processing end in the data calculation scheduling task.

[0064] Among them, the enterprise data processing end, the supplier data processing end, and the bank data processing end can be the calculation nodes and data acquisition points that respectively calculate enterprise data, supplier data, and bank data. All three are data processing ends, and each of them has a preset set of data calculation logic. For different data, it can traverse the set of data calculation logic to find the data calculation logic with the highest matching degree with the input data for calculation.

[0065] Specifically, each data security computing engine node obtains all encrypted data sent by the data service, inputs the field definitions of each encrypted data fragment into the enterprise data processing end, the supplier data processing end, and the bank data processing end respectively, and selects the data computing logic with the highest matching degree with the field definitions of the input encrypted data from the data computing logic set deployed by the computing nodes corresponding to the enterprise data processing end, the supplier data processing end, and the bank data processing end respectively.

[0066] For example, based on the enterprise data processing terminal A1, supplier data processing terminal A2, and bank data processing terminal A3 in data calculation scheduling task A, the corresponding data calculation logics a1, a2, and a3 are determined respectively.

[0067] Step 304: Input each encrypted fragment of data into the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal respectively, and perform at least one collaborative calculation according to the data calculation logic corresponding to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal respectively, to obtain the enterprise terminal resource retrieval quantity information, the supplier terminal resource retrieval quantity information, and the bank terminal resource retrieval quantity information.

[0068] The information on the number of resources requested by enterprises, suppliers, and banks can be obtained by dividing the pending business data corresponding to the target business object into segments according to the processing needs of the enterprise data processing end, supplier data processing end, and bank data processing end, and then performing calculation and analysis. This information is used to guide the public resource platform to allocate resources to the target business object.

[0069] Specifically, the business data to be processed corresponding to the target business object is divided according to the processing requirements of the enterprise data processing end, the supplier data processing end, and the bank data processing end. Each encrypted fragment is then input into the enterprise data processing end, the supplier data processing end, and the bank data processing end respectively. Based on the data calculation logic deployed at the computing nodes corresponding to the enterprise data processing end, the supplier data processing end, and the bank data processing end respectively, multi-party secure computing technology is used to achieve collaborative computing of the encrypted fragment data of each party. The specific data calculation logic is as follows: (1) Verify the authenticity of the production order (enterprise data processing end): Verify the order data. If [enterprise production order number] = [physical associated order number] and [enterprise order product type] = [physical type] and [physical status] = "normal", then the order is normal. Otherwise, the order is rejected from being allocated resources, and the information on the number of resources allocated by the enterprise end is obtained. (2) Verify production order data (supplier data processing end): If [supplier agreement number] = [supply item agreement number] and all items in the supplier's [item list] have [item warehouse status] = "sent", then the order status is normal; otherwise, refuse to allocate resources for the order and obtain the resource allocation quantity information from the supplier. (3) Calculate the total number of resources allocated from the production order (bank data processing end): Total number of resources allocated M = [enterprise supply item agreement resource quantity] * R, where R is the resource ratio parameter setting for the supply chain production order; calculate the total number of enterprise resources allocated: the total number of resources allocated from the first supplier M21 = [first supplier supply item resource quantity], the total number of resources allocated from the second supplier M22 = [second supplier supply item resource quantity]; the total number of enterprise resources allocated M1 = enterprise supply item agreement resource quantity M - first supplier supply item resource quantity M21 - second supplier supply item resource quantity M22, and obtain the resource allocation quantity information from the bank.

[0070] Step 306: Merge the resource quantity information from the enterprise, the supplier, and the bank to obtain the resource quantity information corresponding to the resource transfer confirmation instruction.

[0071] Specifically, the resource quantity information from the enterprise, supplier, and bank is processed in reverse order according to the data sharding rules. The calculated resource quantity information is then merged again to obtain the resource quantity information corresponding to the resource determination instruction.

[0072] In this embodiment, by clarifying the data calculation logic executed by the enterprise data processing end, the supplier data processing end, and the bank data processing end respectively, the system obtains the resource quantity information from the enterprise end, the supplier end, and the bank end after calculation. This enables effective support for risk management corresponding to the resource transfers across the supply chain, accurate calculation and breakdown of the resource quantity information, and improves the accuracy of the system's calculation of the resource transfers.

[0073] In one embodiment, such as Figure 4 As shown, each encrypted data fragment is input into the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, respectively, including:

[0074] Step 402: Input the enterprise production order number, physical associated order number, enterprise order product type, physical type, and physical status information from the encrypted fragmented data into the enterprise data processing terminal.

[0075] Specifically, the business data to be processed corresponding to the target business object is divided according to the processing needs of the enterprise data processing end, the supplier data processing end, and the bank data processing end. The enterprise production order number, physical associated order number, enterprise order product type, physical type, and physical status information in each encrypted data segment are respectively input into the enterprise data processing end. Among them, the enterprise production order number, physical associated order number, enterprise order product type, physical type, and physical status information can be used by the enterprise data processing end to verify the authenticity of the production order.

[0076] Step 404: Input the supplier agreement number, the supplied item agreement number, and the item warehouse status from the encrypted fragmented data into the supplier data processing terminal.

[0077] Specifically, the pending business data corresponding to the target business object is divided according to the processing needs of the enterprise data processing end, the supplier data processing end, and the bank data processing end. The supplier agreement number, the supply item agreement number, and the item warehouse status in each encrypted fragment are then input into the supplier data processing end. The supplier agreement number, the supply item agreement number, and the item warehouse status can be used by the supplier data processing end to verify the production order data.

[0078] Step 406: Input the number of enterprise supply item agreement resources, the proportion of callable resources, and the number of supply item resources from at least two suppliers in the encrypted fragmented data into the bank data processing terminal.

[0079] Specifically, the pending business data corresponding to the target business object is divided according to the processing needs of the enterprise data processing end, the supplier data processing end, and the bank data processing end. The number of enterprise supply item agreement resources, the ratio of callable resources, and the number of supply item resources from at least two suppliers in each encrypted fragment are then input into the bank data processing end. The number of enterprise supply item agreement resources, the ratio of callable resources, and the number of supply item resources from at least two suppliers can be used by the bank data processing end to verify the total number of resources transferred out of production orders and the total number of resources transferred out of the enterprise.

[0080] In this embodiment, by limiting the dependent variables for calculations performed by the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, and by only inputting the data that needs to be processed for each different processing terminal, the goal of classifying and processing the data at each processing terminal is achieved. This ensures that each processing terminal maintains the same processing terminal from data acquisition to data processing, reduces the interaction between different data, and improves the efficiency of the system in processing data.

[0081] In one embodiment, such as Figure 5 As shown, at least one collaborative calculation is performed based on the data calculation logic corresponding to the enterprise data processing end, the supplier data processing end, and the bank data processing end to obtain the resource quantity information of the enterprise end corresponding to the enterprise data processing end, the resource quantity information of the supplier end corresponding to the supplier data processing end, and the resource quantity information of the bank end corresponding to the bank data processing end, including:

[0082] Step 502: Based on the data calculation logic corresponding to the enterprise data processing terminal, determine whether the enterprise production order number is equal to the physical associated order number, whether the enterprise order product type is equal to the physical type, and whether the physical status is normal, and obtain the resource quantity information retrieved from the enterprise terminal.

[0083] Specifically, based on the data calculation logic corresponding to the enterprise data processing end, multi-party secure computation technology is used to achieve collaborative computation of encrypted fragmented data from all parties. The specific data calculation logic executed by the enterprise data processing end is as follows: Verify the authenticity of the production order (enterprise data processing end): Verify the order data. If [enterprise production order number] = [physical associated order number] and [enterprise order product type] = [physical type] and [physical status] = "normal", then the order is normal; otherwise, the order is rejected from being allocated resources, and the quantity information of the resources allocated by the enterprise end is obtained.

[0084] Step 504: Based on the data calculation logic corresponding to the supplier's data processing terminal, determine whether the supplier agreement number is equal to the supply item agreement number and whether the item warehouse status is "sent". Obtain the information on the quantity of resources retrieved from the supplier's terminal.

[0085] Specifically, based on the data calculation logic corresponding to the supplier's data processing end, multi-party secure computation technology is used to achieve collaborative computation of encrypted fragmented data from all parties. The specific data calculation logic executed by the supplier's data processing end is as follows: Verify production order data (supplier data processing end): If [supplier agreement number] = [supply item agreement number] and the [item warehouse status] of all items in the supplier's [item list] is "sent", then the order status is normal; otherwise, the order is rejected from resource allocation, and the quantity information of resource allocation from the supplier is obtained.

[0086] Step 506: Based on the data calculation logic corresponding to the bank's data processing terminal, multiply the number of enterprise-supplied goods agreement resources by the available resource ratio parameter to obtain the intermediate outgoing resource quantity information; subtract the sum of the number of goods supplied by at least two suppliers from the intermediate outgoing resource quantity information to obtain the bank's outgoing resource quantity information.

[0087] Specifically, based on the data calculation logic corresponding to the bank's data processing terminal, multi-party secure computation technology is used to achieve collaborative computation of encrypted fragmented data from all parties. The specific data calculation logic executed by the bank's data processing terminal is as follows: Calculate the total number of resources transferred out of production orders (bank data processing terminal): Total number of resources transferred out M = [Number of enterprise supply item agreement resources] * R, where R is the resource ratio parameter setting for supply chain production orders; Calculate the total number of enterprise resources transferred out: Total number of resources transferred out by the first supplier M21 = [Number of first supplier supply item resources], Total number of resources transferred out by the second supplier M22 = [Number of second supplier supply item resources]; Total number of enterprise resources transferred out M1 = Number of enterprise supply item agreement resources M - Number of first supplier supply item resources M21 - Number of second supplier supply item resources M22, thus obtaining the information on the number of resources transferred out by the bank.

[0088] In this embodiment, by defining the data calculation logic corresponding to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, and by effectively calculating the data input to each processing terminal according to the defined data calculation logic, the resource quantity information of multiple targets can be obtained. This enables collaborative calculation for different processing terminals, improving the system's work efficiency while ensuring data security.

[0089] In one embodiment, such as Figure 6 As shown, the business data to be processed includes enterprise production data, supplier supply data, and resource interaction system data; the business data to be processed corresponding to the data processing terminal includes:

[0090] Step 602: Based on the preset data service and data field definitions of the data processing terminal, extract enterprise production data from the enterprise data processing terminal, extract supplier supply data from the supplier data processing terminal, and extract resource interaction system data from the bank data processing terminal.

[0091] Data services can be information technology-driven services that provide various forms of data evolution, such as data collection, data transmission, data storage, data processing (including calculation, analysis, visualization, etc.), data exchange, and data destruction. They can perform corresponding calculations on data to solve pre-defined problems. Therefore, when calculating data, certain weights are set so that the calculation can focus on a specific problem.

[0092] The data field definition can be used to define the field name, field type, and field options of the data to facilitate the subsequent execution of commands by the computer.

[0093] Specifically, the data acquisition service is run. This involves running the data services deployed by the core production enterprise (enterprise data processing end), upstream and downstream supplier-exporter enterprises (supplier data processing end), and the bank (bank data processing end), and reading the business data of each data provider according to the data acquisition field definitions configured in the system. This includes: (i) Extracting enterprise production data from the enterprise data processing end, i.e., the data service deployed on the core enterprise production system end reads the following data: enterprise identity identifier, production order number, order product type, total number of order resources, supplier agreement number, number of supplier agreement resources, unique identifier of product item, product item status, and item-related order number. (ii) Extracting supplier supply data from the supplier data processing end, i.e., the data service deployed on the supplier production system end reads the following data: enterprise identity identifier, supply agreement number, number of supply agreement resources, item list, and item warehouse receipt status. (iii) Extracting resource interaction system data from the bank data processing end, i.e., the data service deployed on the bank system end reads the following data: enterprise identity identifier, enterprise bank account, and digital information of physical assets on the IoT platform.

[0094] Step 604: Combine the enterprise production data, supplier supply data, and resource interaction system data to obtain the business data to be processed at the data processing end.

[0095] Specifically, enterprise production data, supplier supply data, and resource interaction system data are combined according to the classification of the data processing terminals that acquire the data, resulting in business data to be processed corresponding to the enterprise data processing terminal, supplier data processing terminal, and bank data processing terminal.

[0096] In this embodiment, a secret sharing protocol for multi-party secure computation is used to distribute the data to three computing nodes for secure computation, ensuring that none of the computing nodes can obtain complete data and thus guaranteeing data security.

[0097] In one embodiment, such as Figure 7 As shown, the method also includes:

[0098] Step 702: Based on at least one IoT information collection platform, obtain the unprocessed business data corresponding to the resource retrieval determination instruction.

[0099] The IoT information collection platform can be an integrated platform encompassing device management, secure data communication, and message subscription capabilities. It supports connecting to a massive number of devices and collecting device data for cloud upload; it provides cloud APIs, allowing the server to send commands to devices for remote control. Furthermore, using the IoT information collection platform enables complete device communication links, requiring you to independently develop the device itself, the cloud server (including configuring the cloud SDK), the database, and the mobile app. During device and server development, you need to define and process device messages.

[0100] Among them, unprocessed business data can be electrical signal data obtained from the sensing terminal corresponding to the Internet of Things information collection platform, and the electrical signal data can be further converted into data that can be recognized by computers.

[0101] Specifically, sensing devices are added to the physical assets of core enterprises in the supply chain to acquire digital information about these devices. For example, new energy vehicles use GPS positioning modules, and bulk commodities like steel use LiDAR to scan 3D digital point cloud data. The digital information acquired by these sensing devices is further processed and analyzed to generate standardized digital status information for physical assets that can be used for business analysis. This includes, but is not limited to, RFID tag data, GPS or BeiDou positioning information, and LiDAR digital point cloud information. Based on IoT platforms such as IoT cloud platforms and financial IoT platforms, the physical asset information of core enterprises is collected, and access is supported by protocols such as HTTP, MQTT, and socket.

[0102] Step 704: Clean the unprocessed business data to remove invalid data, and analyze the data obtained from the invalid data cleaning process to obtain the business data to be processed.

[0103] Among them, the item status information can be a judgment on the inherent state of the item. For example, location data can be used to analyze whether the area where the item is located is normal, while status data can be used to analyze whether the volume, quantity, and other states are normal.

[0104] Specifically, the method for obtaining the business data to be processed is as follows: Figure 10 As shown. The digital information of the accessed items is cleaned and analyzed. The steps include: 1. Filtering duplicate data. The device collects the digital information of the items at regular intervals. After access, the data whose status of the digital information of the items has not changed is filtered. 2. Item data analysis. For the accessed and processed item data, the status of the item resources represented by the data is analyzed. For example, the location data is analyzed to see if the area is normal, and the status data is analyzed to see if the volume, quantity and other statuses are normal. The specific methods include but are not limited to the following modes: (1) Monitoring the status of item resources entering and leaving the warehouse. The item resources are embedded with RFID radio frequency tags. The information is automatically sensed and read by handheld scanning devices or RFID antennas in the process of item resources entering and leaving the warehouse. The status of the item resources is marked as in the warehouse (normal) or not in the warehouse (abnormal). (2) Monitoring the location status of item resources. The location information of item resources is collected in real time using GPS, Beidou and other positioning technologies. Digital geofence monitoring is formulated according to specific scenarios and management requirements. The map area is delineated as the electronic fence. The fence is judged according to the real-time collected geographical coordinates of the item resources. If it does not exceed the geographical fence range, it is in a normal state. Otherwise, it is marked as an abnormal state. (3) Monitoring the status of the virtual container where the item resources are located. Using LiDAR to scan 3D point clouds of bulk commodities such as steel, XYZ 3D coordinate system data of the key space of the commodity is formed. This 3D point cloud data is reconstructed to form a virtual container space for the bulk commodity. The virtual 3D point cloud data is periodically re-collected for dynamic algorithm analysis. If the matching algorithm is within the normal threshold range, it is considered normal; otherwise, it is considered abnormal. 3. Data Standardization. The analyzed item data needs to be standardized and transformed into [item type, item unique identifier, item status, item associated order number]. After processing, the business data to be processed is obtained.

[0105] In this embodiment, by cleaning invalid data from the data obtained by the IoT information collection platform, and further analyzing the item status information in the data, data that does not meet business requirements from the unprocessed business data obtained from the sensors can be effectively removed, ensuring that the data processed by the server has practical significance, improving the accuracy of the server's data processing, and making the calculation results more convincing.

[0106] In one embodiment, such as Figure 8 As shown, the unprocessed business data is cleaned to remove invalid data, and the true nature of the data obtained after the invalid data cleansing is analyzed to obtain the business data to be processed, including:

[0107] Step 802: Filter the unchanged item digital information corresponding to the unprocessed business data to obtain the unprocessed valid data.

[0108] Specifically, duplicate data is filtered out from unprocessed business data. The device periodically collects digital information of the items corresponding to unprocessed business data. After access, data whose item digital information status remains unchanged is filtered out, while data whose item digital information status has changed is retained as valid unprocessed data.

[0109] Step 804: Perform authenticity analysis on the item status information in the unprocessed valid data, and delete the data that does not conform to authenticity after analysis to obtain unprocessed real data.

[0110] Specifically, unprocessed valid data will be analyzed for item data. For the item data that has been processed, the status of the item resources represented by the data will be analyzed. For example, the location data will be analyzed to determine whether the area is normal, and the status data will be analyzed to determine whether the volume, quantity, etc. are normal. Specific methods include, but are not limited to, the following modes: (1) Monitoring the status of item resources entering and leaving the warehouse. RFID radio frequency tags will be used to embed and mark the item resources. During the entry and exit of item resources, handheld scanning devices or RFID antennas will be used to automatically sense and read information, and the status of the item resources will be marked as in the warehouse (normal) or out of the warehouse (abnormal). (2) Monitoring the location status of item resources. GPS, Beidou and other positioning technologies will be used to collect the location information of item resources in real time, and digital geofence monitoring will be formulated according to specific scenarios and management requirements. The map area will be delineated as an electronic fence. The fence will be judged according to the real-time collected geographical coordinates of the item resources. If the item is within the range of the geofence, it is in a normal state; otherwise, it is marked as an abnormal state. (3) Monitoring the status of the virtual container where the item resources are located. Using LiDAR to scan the 3D point cloud of bulk commodities such as steel, the XYZ 3D coordinate system data of the key space of the commodity is formed. The 3D point cloud data is reconstructed to form a virtual container space of bulk commodities. The virtual 3D point cloud data is periodically re-collected for dynamic algorithm analysis. If the matching algorithm is within the normal threshold range, it is in a normal state; otherwise, it is in an abnormal state. Data that meets the authenticity after the authenticity analysis is retained as unprocessed real data.

[0111] Step 806: Transform the unprocessed real data according to the preset standardization to obtain the business data to be processed.

[0112] Specifically, the unprocessed real data undergoes data standardization. The analyzed item data needs to be standardized and transformed into data in the format of [item type, item unique identifier, item status, item associated order number]. The data formed after processing is used as the business data to be processed.

[0113] In this embodiment, by further defining the specific steps and data used for invalid data cleaning, item status information analysis, and standardization transformation of unprocessed business data, it can be ensured that invalid data in unprocessed business data, the true state of the data, and standardization transformation have all been processed, avoiding data errors due to omissions of unprocessed business data and improving the accuracy of server calculations.

[0114] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0115] Based on the same inventive concept, this application also provides a resource determination apparatus for implementing the resource determination method described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the resource determination apparatus provided below can be found in the limitations of the resource determination method described above, and will not be repeated here.

[0116] In one embodiment, such as Figure 11 As shown, a resource retrieval determination device is provided, comprising: a task determination module 1102, a data processing module 1104, a data calculation module 1106, and a resource retrieval determination module 1108, wherein:

[0117] The task determination module 1102 is used to respond to the resource determination instruction for the target business object, determine the data calculation scheduling task corresponding to the resource determination instruction, and determine the data processing end, result receiving end and data calculation logic corresponding to each data processing end according to the data calculation scheduling task.

[0118] The data processing module 1104 is used to acquire the business data to be processed corresponding to the data processing terminal, and to perform fragment encryption on the business data to be processed corresponding to the data processing terminal to obtain at least one ciphertext fragment data; the business data to be processed is used to describe the data of the target business object in the process of executing business.

[0119] The data calculation module 1106 is used to input each encrypted fragment data into at least two data processing terminals; and control each data processing terminal to calculate the corresponding encrypted fragment data according to the corresponding data calculation logic to obtain the information on the number of resources to be called out corresponding to the resource call-out determination instruction.

[0120] The resource retrieval determination module 1108 is used to generate a corresponding list of retrieved resources based on the number of retrieved resources and send the list of retrieved resources to the result receiving end.

[0121] In one embodiment, the data calculation module 1106 is further configured to determine the corresponding data calculation logic for the enterprise data processing end, supplier data processing end, and bank data processing end in the data calculation scheduling task; input each encrypted fragment of data to the enterprise data processing end, supplier data processing end, and bank data processing end respectively, and perform at least one collaborative calculation according to the corresponding data calculation logic for the enterprise data processing end, supplier data processing end, and bank data processing end to obtain the enterprise end resource retrieval quantity information, the supplier end resource retrieval quantity information, and the bank end resource retrieval quantity information; merge the enterprise end resource retrieval quantity information, the supplier end resource retrieval quantity information, and the bank end resource retrieval quantity information to obtain the resource retrieval quantity information corresponding to the resource retrieval determination instruction.

[0122] In one embodiment, the data calculation module 1106 is further configured to input the enterprise production order number, physical associated order number, enterprise order product type, physical type, and physical status information from the encrypted fragmented data to the enterprise data processing terminal; input the supplier agreement number, supply item agreement number, and item warehouse status from the encrypted fragmented data to the supplier data processing terminal; and input the number of enterprise supply item agreement resources, callable resource ratio parameters, and the number of supply item resources from at least two suppliers from the encrypted fragmented data to the bank data processing terminal.

[0123] In one embodiment, the data calculation module 1106 is further configured to determine, based on the data calculation logic corresponding to the enterprise data processing terminal, whether the enterprise production order number is equal to the physical associated order number, whether the enterprise order product type is equal to the physical type, and whether the physical status is normal, to obtain the enterprise-side resource quantity information; based on the data calculation logic corresponding to the supplier data processing terminal, determine whether the supplier agreement number is equal to the supply item agreement number and whether the item warehouse status is "sent", to obtain the supplier-side resource quantity information; based on the data calculation logic corresponding to the bank data processing terminal, multiply the enterprise supply item agreement resource quantity by the available resource ratio parameter to obtain the intermediate resource quantity information; and subtract the sum of at least two supplier supply item resource quantities from the intermediate resource quantity information to obtain the bank-side resource quantity information.

[0124] In one embodiment, the data processing module 1104 is further configured to extract enterprise production data from the enterprise data processing terminal, supplier supply data from the supplier data processing terminal, and resource interaction system data from the bank data processing terminal according to the preset data service and data field definitions of the data processing terminal; and combine the enterprise production data, supplier supply data, and resource interaction system data to obtain the business data to be processed corresponding to the data processing terminal.

[0125] In one embodiment, the data acquisition module is used to acquire unprocessed business data corresponding to the resource retrieval determination instruction based on at least one Internet of Things information collection platform. The unprocessed business data is obtained by standardizing digital information obtained by the object sensing device. The unprocessed business data is cleaned of invalid data, and the data obtained from the invalid data cleaning is analyzed for object status information to obtain business data to be processed.

[0126] In one embodiment, the data acquisition module is further configured to filter the unchanged item digital information corresponding to the unprocessed business data to obtain unprocessed valid data; perform authenticity analysis on the item status information in the unprocessed valid data, and delete the data that does not conform to authenticity after analysis to obtain unprocessed real data; and convert the unprocessed real data according to a preset standardization to obtain business data to be processed.

[0127] Each module in the aforementioned resource retrieval device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can invoke and execute the operations corresponding to each module.

[0128] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 12As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores server data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a resource allocation determination method.

[0129] Those skilled in the art will understand that Figure 12 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0130] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0131] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0132] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the steps in the above method embodiments.

[0133] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0134] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0135] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining resources to be retrieved, characterized in that, The method includes: In response to a resource allocation determination instruction for a target business object, a data computation scheduling task corresponding to the resource allocation determination instruction is determined, and based on the data computation scheduling task, a data processing terminal, a result receiving terminal, and the data computation logic corresponding to each data processing terminal for the target object are determined; the data processing terminal includes an enterprise data processing terminal, a supplier data processing terminal, and a bank data processing terminal. The process involves acquiring the business data to be processed corresponding to the data processing terminal, and then encrypting the business data to be processed corresponding to the data processing terminal in segments to obtain at least one encrypted segmented data; the business data to be processed is used to describe the data of the target business object during the execution of business. The corresponding data calculation logic is determined based on the enterprise data processing end, supplier data processing end, and bank data processing end in the data calculation scheduling task. Each encrypted fragment of data is input to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, respectively. At least one collaborative calculation is performed based on the data calculation logic corresponding to each of the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal to obtain the enterprise-side resource retrieval quantity information, the supplier-side resource retrieval quantity information, and the bank-side resource retrieval quantity information. The enterprise-side resource retrieval quantity information, the supplier-side resource retrieval quantity information, and the bank-side resource retrieval quantity information can be obtained by dividing the pending business data corresponding to the target business object according to the processing requirements of the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, and then performing calculations and analyses to obtain the corresponding quantity information for each part. The resource quantity information from the enterprise, the supplier, and the bank is merged to obtain the resource quantity information corresponding to the resource determination instruction. A corresponding list of resource transfer results is generated based on the number of resources transferred, and the list of resource transfer results is sent to the result receiving end.

2. The method according to claim 1, characterized in that, The step of inputting each of the encrypted fragments of data to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal respectively includes: The enterprise production order number, physical associated order number, enterprise order product type, physical type, and physical status information in the encrypted fragmented data are input into the enterprise data processing terminal. The supplier agreement number, the supplied item agreement number, and the item warehouse status from the encrypted fragmented data are input into the supplier data processing terminal. The number of enterprise supply item agreement resources, the proportion of callable resources, and the number of supply item resources from at least two suppliers in the encrypted fragmented data are input into the bank's data processing terminal.

3. The method according to claim 2, characterized in that, The step of performing at least one collaborative calculation based on the data calculation logic corresponding to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal to obtain the resource quantity information of the enterprise terminal corresponding to the enterprise data processing terminal, the resource quantity information of the supplier terminal corresponding to the supplier data processing terminal, and the resource quantity information of the bank terminal corresponding to the bank data processing terminal includes: Based on the data calculation logic corresponding to the enterprise data processing terminal, it is determined whether the enterprise production order number is equal to the physical associated order number, whether the enterprise order product type is equal to the physical type, and whether the physical status is normal, so as to obtain the resource quantity information retrieved by the enterprise terminal; Based on the data calculation logic corresponding to the supplier data processing terminal, the supplier agreement number is determined to be equal to the supply item agreement number, and the item warehouse status is determined to be sent, thereby obtaining the resource quantity information retrieved by the supplier terminal. According to the data calculation logic corresponding to the bank's data processing terminal, the number of enterprise-supplied goods agreement resources is multiplied by the available resource ratio parameter to obtain the intermediate outgoing resource quantity information; the sum of at least two supplier-supplied goods resource quantities is subtracted from the intermediate outgoing resource quantity information to obtain the bank's outgoing resource quantity information.

4. The method according to claim 1, characterized in that, The data processing terminals include enterprise data processing terminals, supplier data processing terminals, and bank data processing terminals. The business data to be processed includes enterprise production data, supplier supply data, and resource interaction system data. The step of obtaining the business data to be processed corresponding to the data processing terminal includes: Based on the preset data service and data field definitions of the data processing terminal, the enterprise production data is extracted from the enterprise data processing terminal, the supplier supply data is extracted from the supplier data processing terminal, and the resource interaction system data is extracted from the bank data processing terminal; The enterprise production data, the supplier supply data, and the resource interaction system data are combined to obtain the business data to be processed corresponding to the data processing terminal.

5. The method according to claim 1, characterized in that, The method further includes: Based on at least one Internet of Things (IoT) information collection platform, unprocessed business data corresponding to the resource retrieval determination instruction is obtained, wherein the unprocessed business data is obtained by standardizing digital information obtained by the object sensing device; The unprocessed business data is cleaned to remove invalid data, and the data obtained from the invalid data cleaning is analyzed for item status information to obtain the business data to be processed.

6. The method according to claim 5, characterized in that, The process of cleaning the unprocessed business data to remove invalid data, and analyzing the true nature of the data obtained from the invalid data cleaning process, to obtain the business data to be processed includes: The unchanging item digital information corresponding to the unprocessed business data is filtered to obtain unprocessed valid data; The authenticity of the item status information in the unprocessed valid data is analyzed, and the data that does not conform to the authenticity after analysis is deleted to obtain the unprocessed real data; The unprocessed real data is transformed according to a preset standardization to obtain the business data to be processed.

7. A resource retrieval determination device, characterized in that, The device includes: The task determination module is used to respond to a resource allocation determination instruction for a target business object, determine the data computation scheduling task corresponding to the resource allocation determination instruction, and determine the data processing end, result receiving end, and data computation logic corresponding to each data processing end based on the data computation scheduling task; the data processing end includes an enterprise data processing end, a supplier data processing end, and a bank data processing end. The data processing module is used to acquire the business data to be processed corresponding to the data processing terminal, and to perform fragment encryption on the business data to be processed corresponding to the data processing terminal to obtain at least one ciphertext fragment data; the business data to be processed is used to describe the data of the target business object in the process of executing business. The data calculation module is used to determine the corresponding data calculation logic based on the enterprise data processing end, supplier data processing end, and bank data processing end in the data calculation scheduling task. Each encrypted fragment of data is input to the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, respectively. At least one collaborative calculation is performed based on the data calculation logic corresponding to each of the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal to obtain the enterprise-side resource retrieval quantity information, the supplier-side resource retrieval quantity information, and the bank-side resource retrieval quantity information. The enterprise-side resource retrieval quantity information, the supplier-side resource retrieval quantity information, and the bank-side resource retrieval quantity information can be obtained by dividing the pending business data corresponding to the target business object according to the processing requirements of the enterprise data processing terminal, the supplier data processing terminal, and the bank data processing terminal, and then performing calculations and analyses to obtain the corresponding quantity information for each part. The resource quantity information from the enterprise, the supplier, and the bank is merged to obtain the resource quantity information corresponding to the resource determination instruction. The resource retrieval determination module is used to generate a corresponding resource retrieval result list based on the resource retrieval quantity information, and send the resource retrieval result list to the result receiving end.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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