Engineering data bilateral authentication method and system based on interface fusion technology

Abstract

The invention discloses an engineering data bilateral authentication method and system based on an interface fusion technology. The method comprises the following steps: S1, performing interface management on an auditing platform, and configuring a native data approval link and a twin data approval link in combination with a service type; s2, configuring a first authentication strategy for the native data approval link, and configuring a second authentication strategy for the twin data approval link; s3, obtaining an abnormal approval node of the native data approval link according to the approval result in combination with a trigger condition of a threshold trigger mechanism, and determining a target twin abnormal approval node in the twin data approval link according to the abnormal approval node and a second authentication strategy; s4, determining a correlation degree value of each approval node of the twin data approval link according to the target twin anomaly approval node; and determining an abnormal examination and approval node troubleshooting strategy according to the association degree value. According to the scheme, the interface data is analyzed and processed, and the correlation between approval items is fully examined, so that the comprehensiveness and accuracy of exception investigation are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a bilateral authentication method and system for engineering data based on interface fusion technology. Background Art

[0002] As the scale and complexity of engineering projects continue to expand, the approval of engineering approval data is a key link to ensure project compliance, effective use of funds and engineering quality, and its importance is becoming increasingly prominent. However, in the current engineering approval data management, engineering approval data involves data from multiple fields, including finance, contracts, material procurement, construction progress, etc. These data are scattered in different systems and in various formats. Traditional engineering approval data approval methods often find it difficult to effectively integrate these data; and due to the lag in approval standards and the neglect of the correlation between approval projects, it is difficult for approval personnel to quickly and accurately locate abnormal nodes when faced with a large amount of data, and it is even more difficult to effectively formulate targeted troubleshooting strategies, which not only increases the difficulty of approval work, but also reduces the credibility of approval results.

[0003] The above information disclosed in the Background section is only for enhancement of understanding of the background of the present application and therefore it may contain information that does not constitute the prior art that is already known to a person of ordinary skill in the art. Summary of the invention

[0004] The purpose of the present invention is to solve the problem that the data approval results lack correctness and comprehensiveness due to the lack of analysis of the source and correlation of the engineering approval data during engineering data approval, and proposes a bilateral authentication method and system for engineering data based on interface fusion technology; by performing interface management on the audit platform and configuring the native data approval link and the twin data approval link according to the business type, the authentication strategy is configured for the two data links and the abnormal approval nodes in the native data approval link are preliminarily identified, and then the target twin abnormal approval node in the twin data approval link is further obtained, and the final abnormality investigation strategy is determined according to the correlation between the target twin abnormal approval node and the abnormal approval node. The scheme analyzes and processes the interface data and fully considers the correlation between the approval items, which significantly improves the comprehensiveness and accuracy of the abnormality investigation and enhances the credibility of the approval results.

[0005] In a first aspect, a technical solution provided in an embodiment of the present invention is a bilateral authentication method for engineering data based on interface fusion technology, comprising the following steps: S1. Perform interface management on the audit platform to obtain standard data tuples, and configure native data approval links and twin data approval links according to the business type of the standard data tuples; S2. Configure a first authentication strategy for the native data approval link according to the first data interface; configure a second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy; S3. Determine the approval result of the native data approval link according to the first authentication strategy. When the approval result meets the trigger condition of the threshold trigger mechanism, obtain the abnormal approval node of the native data approval link, and determine the target twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy; S4. Determine the correlation value of each approval node in the twin data approval link based on the target twin abnormal approval node; determine the abnormal approval node troubleshooting strategy based on the correlation value.

[0006] In this scheme, by managing the interface of the audit platform, standard data tuples are obtained, and the native data approval link and the twin data approval link are flexibly configured according to the business type, which not only ensures the standardized processing of data, but also provides adaptability to different business scenarios; further, the first authentication strategy and the second authentication strategy are configured for the native data approval link and the twin data approval link respectively, forming a two-layer authentication mechanism, which effectively improves the security and accuracy of approval data screening; further, when the approval result of the native data approval link triggers the threshold mechanism, it can automatically identify abnormal approval nodes and locate the corresponding target twin abnormal approval nodes in the twin data approval link, realizing rapid response and precise positioning of abnormal situations; by calculating the correlation value of each approval node in the twin data approval link, it can more comprehensively analyze the impact range of abnormal approval nodes, and then formulate more effective abnormal approval node screening strategies. Through interface fusion and bilateral authentication technology, the scheme realizes standardized processing, two-layer security verification, intelligent exception processing and abnormal safety screening strategies in engineering approval data, significantly improving the efficiency, security and intelligence level of approval data processing.

[0007] Preferably, the interface management of the audit platform is performed to obtain a standard data tuple, and the native data approval link and the twin data approval link are configured according to the business type of the standard data tuple; the steps include: S11. The audit platform extracts the source characteristics and content characteristics of the interface data, and uses the source characteristics as the Key value of the standard data tuple and the content characteristics as the Value value of the standard data tuple; S12. Determine the business type based on the Key value of the standard data tuple, and match the corresponding approval node and approval path for the business type; construct the native data approval link and twin data approval link of the corresponding interface data based on the approval node, approval path and Value value.

[0008] In this solution, the audit platform can extract the source features and content features of the interface data, and use them as the Key value and Value value of the standard data tuple respectively. This step realizes the standardized processing of data, providing a basis for subsequent data processing and approval; according to the Key value of the standard data tuple, the audit platform can accurately identify the business type, and match the corresponding approval node and approval path for each business type, ensuring the close connection between the approval link and the business logic, and improving the accuracy and pertinence of the approval; based on the approval node, approval path and Value value, the audit platform can build the native data approval link and twin data approval link corresponding to the interface data; it realizes the dual-track parallel of the approval link, which not only retains the approval track of the original data, but also creates twin data for comparative approval, enhancing the reliability and security of the approval; in summary, the solution realizes the refined management of interface data and dual-track parallel approval through the steps of feature extraction, business type identification and matching, and approval link construction, improving the accuracy and pertinence of approval, enhancing the reliability and security of approval, and providing strong support for enterprise data management.

[0009] Preferably, the interface data includes data to be approved and approval specification data, and the configuring of the first authentication strategy for the native data approval link according to the first data interface includes the following steps: S201, configuring a first data interface for the data to be approved, and extracting the Value-1 value of the data to be approved; the Value-1 value at least includes a file source address and an initial approval specification; S202. Match the initial approval specifications to the corresponding approval nodes in the native data approval link in sequence to obtain a first authentication strategy.

[0010] In this solution, the first authentication strategy configuration of the native data approval link is realized by configuring data interfaces for the data to be approved, extracting key information, and matching approval specifications to approval nodes. This not only improves the accuracy and standardization of approval, but also provides strong support for the company's data security management.

[0011] Preferably, configuring the second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy comprises the following steps: S211, configuring a second data interface for the approval specification data, extracting the Value-2 value of the approval specification data; the Value-2 value at least includes the file source address and the update approval specification; S212. The initial approval specification of each approval node in the first authentication strategy is replaced in sequence by updating the approval specification to obtain a second authentication strategy belonging to the twin data approval link.

[0012] In this solution, a second data interface is configured for the approval specification data, and the Value-2 value of the approval specification data is extracted through this interface. The Value-2 value contains at least the file source address and the updated approval specification, which provides the necessary information basis for the subsequent authentication policy update; through the extracted updated approval specification, the initial approval specification of each approval node in the first authentication policy is replaced in turn, thereby obtaining the second authentication policy belonging to the twin data approval link; the flexible update of the approval policy is realized, ensuring that the twin data approval link can be adjusted in time with the changes in the approval specification, and improving the adaptability and accuracy of the approval.

[0013] Preferably, the first authentication strategy and the second authentication strategy at least include document source verification and approval verification; The document source verification at least includes document compliance verification and document integrity verification; The approval verification at least includes approval qualification verification, approval data verification and approval logic verification.

[0014] In this solution, when the data to be approved and the approval specification data are connected to the audit platform through their respective data interfaces, the first authentication strategy is configured for the native data approval link by first extracting the Value-1 value of the data to be approved, including the file source address and the initial approval specification. This strategy covers at least two aspects: file source verification and approval verification, ensuring the compliance and integrity of the file itself, as well as the accuracy of the qualifications, data and logic of the approval process. Subsequently, by extracting the Value-2 value of the approval specification data, including the file source address and the updated approval specification, this technical solution further configures the second authentication strategy for the twin data approval link; this strategy also includes file source verification and approval verification, but it is configured based on the updated approval specification, ensuring that the twin data approval link can be adjusted in time with the changes in the approval specification; specifically, file source verification ensures the compliance and integrity of the approved file, preventing illegal or damaged files from entering the approval process; while approval verification conducts a comprehensive inspection of the qualifications of the approval personnel, the accuracy of the approval data and the rationality of the approval logic, ensuring the fairness and accuracy of the approval process, and providing a more reliable and powerful guarantee for the enterprise's data security management.

[0015] Preferably, the method of determining the approval result of the native data approval link according to the first authentication strategy, and obtaining the abnormal approval node of the native data approval link when the approval result meets the triggering condition of the threshold trigger mechanism, comprises the following steps: S301, determining the approval result type according to the verification items in the first authentication strategy, the approval result type including the document source verification result and the approval verification result; setting a first threshold trigger mechanism subordinate to the document source verification result and a second threshold trigger mechanism subordinate to the approval verification result; S302: When the file source verification result meets the triggering condition of the first threshold triggering mechanism, the audit platform performs interface management to regenerate the standard data tuple and executes S1; S303: When the approval verification result meets the triggering condition of the second threshold triggering mechanism, the abnormal approval node of the native data approval link is obtained.

[0016] In this solution, when the native data approval link completes the approval according to the first authentication strategy, the corresponding approval result will be generated; the solution first determines the type of approval result according to the verification items in the first authentication strategy, which includes the file source verification result and the approval verification result. At the same time, the first threshold trigger mechanism and the second threshold trigger mechanism are set for these two results respectively, so that timely response can be made when the approval result is abnormal; if the file source verification result meets the trigger condition of the first threshold trigger mechanism, it means that there may be problems with the compliance or integrity of the approved file; at this time, the audit platform will perform interface management, regenerate standard data tuples, and execute the approval process from the beginning (i.e., execute S1) to ensure the accuracy and reliability of the approval; if the approval verification result meets the trigger condition of the second threshold trigger mechanism, it means that there may be problems such as incompatibility of qualifications, data errors, or unreasonable logic in the approval process. At this time, this technical solution will obtain the abnormal approval nodes in the native data approval link for subsequent targeted investigation and processing; in summary, this technical solution sets a threshold trigger mechanism and processes different types of approval results to achieve comprehensive monitoring and exception handling of the native data approval link; it not only improves the accuracy and reliability of approval, but also provides a more complete guarantee for the company's data security management; when an abnormality occurs in the approval result, it can respond in time and take corresponding processing measures to ensure the compliance and security of the data.

[0017] Preferably, the setting of a first threshold trigger mechanism subordinate to the file source verification result and a second threshold trigger mechanism subordinate to the approval verification result comprises the following steps: Determine the file source verification items based on the file source address extracted from the interface data and the approval file list; set the file compliance verification scope and file integrity verification scope corresponding to the file source verification items; and use failure to meet the file compliance verification scope and / or the file integrity verification scope as the trigger condition of the first threshold trigger mechanism; Determine the approval verification items based on the approval qualifications, approval data and approval logic extracted from the interface data; set the document approval qualification verification scope, approval data verification scope and approval logic verification sequence corresponding to the approval verification items; and use failure to meet the document approval qualification verification scope and / or approval data verification scope and / or approval logic verification sequence as the trigger condition for the second threshold trigger mechanism.

[0018] In this solution, by setting the first threshold trigger mechanism and the second threshold trigger mechanism in detail, accurate monitoring and management of the approval results of the native data approval link are achieved. When abnormalities occur in the approval results, timely response and corresponding processing measures can be taken to ensure the compliance and security of the data.

[0019] Preferably, the method of determining the twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy comprises the following steps: S311. Determine a twin abnormal approval node according to the node position of the abnormal approval node in the twin data approval link; S312. Re-verify the first twin exception approval node in combination with the approval verification items in the second authentication strategy to determine the second twin exception approval node; and use the twin exception approval node as the target twin exception approval node.

[0020] In this scheme, firstly, the corresponding first twin abnormal approval node can be determined in the twin data approval link according to the node position of the abnormal approval node in the original data approval link. The mapping relationship between the original data approval link and the twin data approval link is used to ensure that the node corresponding to the abnormal node in the original data approval link can be accurately found in the twin data approval link; secondly, in order to further confirm whether the first twin abnormal approval node is indeed abnormal, the scheme verifies it again in combination with the approval verification items in the second authentication strategy. By comparing the verification items in the second authentication strategy and the relevant data of the first twin abnormal approval node, it is verified whether the node is abnormal; finally, after re-verification, if it is determined that the first twin abnormal approval node is indeed abnormal, then the node will be determined as a second twin abnormal approval node, and will be used as the target twin abnormal approval node for subsequent processing. In summary, this technical solution searches for twin abnormal approval nodes in the twin data approval link through mapping relationships, and re-verifies in combination with the second authentication strategy, thereby realizing accurate search and confirmation of abnormal nodes in the twin data approval link; it not only improves the accuracy and reliability of approval, but also provides more comprehensive protection for the enterprise's data security management. When an abnormality occurs in the native data approval link, the corresponding abnormal node can be found and processed in the twin data approval link in a timely manner, thereby ensuring the compliance and security of the data.

[0021] Preferably, the method of determining the correlation value of each approval node in the twin data approval link according to the target twin abnormal approval node; and determining the abnormal approval node troubleshooting strategy according to the correlation value comprises the following steps: S41. Obtain the approval verification items corresponding to the target twin abnormal approval node; the approval verification items include the document approval qualification verification scope, the approval data verification scope and the approval logic verification sequence; S42. Construct triplet data according to the numerical characteristics in the approval and verification items; calculate the sum of the correlations between each target twin abnormal approval node and the primary twin abnormal approval node in the twin data approval link according to the triplet data; S43. Sort the target twin abnormal approval nodes from large to small according to the sum of the correlation degrees to obtain an abnormal approval node screening table, and execute the abnormal approval node screening strategy according to the abnormal approval node screening table in combination with the corresponding approval verification items.

[0022] In this scheme, first, this technical scheme will obtain the approval verification items corresponding to the target twin abnormal approval node. These verification items include the document approval qualification verification scope, the approval data verification scope and the approval logic verification order; these verification items are important bases for judging whether the approval node is normal; then, according to the numerical characteristics in the approval verification items, this technical scheme will construct triple data, and use these data to calculate the sum of the correlations between each target twin abnormal approval node and the first twin abnormal approval node in the twin data approval link; the sum of the correlations reflects the degree of correlation between each approval node and the abnormal node. The higher the correlation, the closer the relationship between the node and the abnormal node; finally, the target twin abnormal approval nodes are sorted from large to small according to the sum of the correlations to obtain an abnormal approval node troubleshooting table; this troubleshooting table provides the approval personnel with a priority order for troubleshooting abnormal nodes, so that they can conduct troubleshooting more targeted. At the same time, in combination with the corresponding approval and verification items, the approval personnel can execute the abnormal approval node screening strategy to screen and process the abnormal nodes one by one; in summary, this technical solution calculates the correlation value of each approval node in the twin data approval link and determines the abnormal approval node screening strategy, thereby realizing efficient screening and processing of abnormal nodes.

[0023] Preferably, the method constructs triple data according to the numerical characteristics in the approval verification items; calculates the sum of the correlations between each target twin abnormal approval node and the primary twin abnormal approval node in the twin data approval link according to the triple data; and comprises the following steps: S421. Extract the numerical characteristics in the approval verification items to obtain the verification item values, wherein the numerical characteristics include numerical characteristics and non-numerical characteristics; the verification item values ​​corresponding to the numerical characteristics include the document approval qualification verification scope and the approval data verification scope; the verification item values ​​corresponding to the non-numerical characteristics include the approval logic verification sequence; specifically, when the approval logic verification sequence corresponding to the approval node is correct, it is "1", and when it is wrong, it is "0"; S422. Construct a triple data set M corresponding to the target twin abnormal approval node and a triple data set N corresponding to the first twin abnormal approval node according to the approval node, the approval verification item, and the verification item value; S423. Calculate the sum of the correlation between each element in the verification item triple data set M and all elements in the triple data set N according to the correlation calculation formula.

[0024] In this solution, first, this technical solution will extract the numerical characteristics in the approval verification items to obtain the verification item values; these numerical characteristics include numerical characteristics and non-numerical characteristics; the verification item values ​​corresponding to the numerical characteristics are such as the document approval qualification verification scope and the approval data verification scope, which can be quantified by specific numerical values. The verification item value corresponding to the non-numerical characteristics is the approval logic verification order, which indicates whether the logical verification order of the approval node is correct, which is "1" for correctness and "0" for error. Then, according to the approval node, approval verification item, and verification item value, this technical solution will respectively construct the triple data set M corresponding to the target twin abnormal approval node and the triple data set N corresponding to the first twin abnormal approval node; these two sets contain all relevant information of the target twin abnormal approval node and the first twin abnormal approval node respectively; finally, the solution will use the correlation calculation formula (which can be the Pearson correlation coefficient method and the Spearman rank correlation coefficient method) to calculate the sum of the correlation between each element in the verification item triple data set M and all elements in the triple data set N. The sum of this correlation reflects the degree of correlation between the target twin abnormal approval node and the primary twin abnormal approval node. By comparing the sum of the correlations of different target twin abnormal approval nodes, the approval personnel can conduct more targeted investigations and give priority to nodes with higher correlations. In summary, by constructing triple data and calculating the sum of correlations, the degree of correlation between the abnormal node and the primary abnormal node in the twin data approval link is accurately quantified; this not only improves the efficiency and accuracy of approval, but also provides more refined protection for the enterprise's data security management.

[0025] In a second aspect, a technical solution provided in an embodiment of the present invention is a bilateral authentication system for engineering data, comprising: Approval link construction module: manage the interface of the audit platform to obtain standard data tuples, and configure native data approval links and twin data approval links according to the business type of the standard data tuples; Authentication module: configure a first authentication strategy for the native data approval link according to the first data interface; configure a second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy; Abnormal determination module: Determine the approval result of the native data approval link according to the first authentication strategy. When the approval result meets the trigger condition of the threshold trigger mechanism, obtain the abnormal approval node of the native data approval link, and determine the target twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy; Execution module: Determine the correlation value of each approval node in the twin data approval link based on the target twin abnormal approval node; determine the abnormal approval node troubleshooting strategy based on the correlation value.

[0026] In the third aspect, a technical solution provided in an embodiment of the present invention is an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the processor calls the computer program in the memory, the steps of a bilateral authentication method for engineering data based on interface fusion technology are implemented.

[0027] In a fourth aspect, a technical solution provided in an embodiment of the present invention is a storage medium, in which computer executable instructions are stored. When the computer executable instructions are loaded and executed by a processor, the steps of a bilateral authentication method for engineering data based on interface fusion technology are implemented.

[0028] The present invention has at least the following substantial technical effects: The following are three substantive technical effects selected and elaborated from the above technical solutions: (1) The solution obtains standard data tuples through interface management, and configures the original data approval link and the twin data approval link accordingly, realizing dual-track parallel approval of data; when the approval result of the original data approval link triggers the threshold mechanism, it can automatically identify abnormal approval nodes and locate the corresponding target twin abnormal approval nodes in the twin data approval link through mapping relationships; dual-track parallel approval not only retains the approval track of the original data, but also enhances the reliability and security of approval through twin data; (2) The solution configures the first authentication strategy for the native data approval link, including document source verification and approval verification; then, based on the updated approval specifications, the second authentication strategy is configured for the twin data approval link. This two-tier authentication mechanism ensures the comprehensiveness and security of the approval process. At the same time, by extracting and updating the approval specifications through the data interface, flexible updating of the authentication strategy is achieved; the two-tier authentication mechanism effectively improves the security and accuracy of the approval data, and prevents illegal or non-compliant data from entering the approval process; the flexible authentication strategy update mechanism ensures that the approval specifications can be adjusted in a timely manner as business needs change, thereby improving the adaptability and flexibility of approval; (3) The scheme constructs triple data and calculates the sum of correlations to analyze the correlation between each approval node and the target twin abnormal approval node in the twin data approval link; generates an abnormal approval node troubleshooting table based on the correlation value, providing a scientific troubleshooting order for the approval personnel; the correlation analysis technology can comprehensively evaluate the impact range of abnormal nodes, providing a scientific basis for formulating efficient abnormal troubleshooting strategies. By giving priority to nodes with higher correlations, the approval personnel can locate and solve problems more quickly, improving the efficiency and accuracy of the troubleshooting work.

[0029] The above invention content is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0031] Figure 1 The flowchart of the bilateral authentication method of engineering data based on interface fusion technology of the present invention. DETAILED DESCRIPTION

[0032] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0034] Embodiment 1: like Figure 1 As shown, a technical solution is a bilateral authentication method for engineering data based on interface fusion technology, including the following steps: S1. Manage the interface of the audit platform to obtain standard data tuples, and configure the native data approval link and the twin data approval link according to the business type of the standard data tuple.

[0035] Specifically, S1 includes the following steps: S11. The audit platform extracts the source characteristics and content characteristics of the interface data, and uses the source characteristics as the Key value of the standard data tuple and the content characteristics as the Value value of the standard data tuple; S12. Determine the business type based on the Key value of the standard data tuple, and match the corresponding approval node and approval path for the business type; construct the native data approval link and twin data approval link of the corresponding interface data based on the approval node, approval path and Value value.

[0036] In this embodiment, it can be understood that in the approval of power engineering projects, the audit platform will extract interface data from systems related to various power engineering projects. These data may come from multiple data sources such as project management systems, financial systems, and material management systems. Source features (Key values) may include project ID, data type identifier (such as contract information, material purchase orders, etc.), data source system name, etc.; content features (Value values) contain specific business data, such as contract amounts, material purchase details, invoice information, etc.; for example, the source feature (Key value) of an interface data item may be "Project ID: P12345, Data type: Contract information, Source system: Project management system", while the content feature (Value value) is the specific contract text and its related attributes (such as contract number, signing date, amount, etc.). The audit platform determines the business type to which the data item belongs based on the extracted source feature (Key value). In the field of power engineering, business types may include multiple stages such as project approval, contract signing, material procurement, construction progress payment, and completion settlement; the corresponding approval personnel and approval rules for each stage are different; assuming that the data item we are currently processing is about the business type of "material procurement", the audit platform will match the corresponding approval nodes and approval paths for this business type. Approval nodes may include "purchase application approval", "purchase contract approval", "warehousing acceptance approval", etc., and the approval path is a combination of these nodes arranged in the order of business logic. According to the approval nodes, approval paths, and content features (Value), the audit platform can construct the corresponding native data approval link B1 and twin data approval link D1. Native data approval link B1; example B1 = [b1, b2, b3] = ["Purchase application approval node", "Purchase contract approval node", "Warehouse acceptance approval node"], each node here (b1, b2, b3) corresponds to an approval link in the material procurement business, and the audit platform will approve the native data in this order; twin data approval link D1; example D1 = [d1, d2, d3] = ["Purchase application twin approval node", "Purchase contract twin approval node", "Warehouse acceptance twin approval node"], corresponding to the native data approval link, the twin data approval link (D1) contains the same approval nodes, but these nodes process twin data (that is, data that corresponds to the native data but may have undergone some processing or simulation). The purpose of this is to enhance the reliability and accuracy of approval by comparing the approval results of native data and twin data. It should be noted that in actual applications, each approval node (whether native or twin) will be associated with specific approval rules, check items, and possible data sources, which will be customized according to specific business scenarios and needs.

[0037] S2. Configure a first authentication strategy for the native data approval link according to the first data interface; configure a second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy.

[0038] Specifically, S2 includes the following steps: S201, configuring a first data interface for the data to be approved, and extracting the Value-1 value of the data to be approved; the Value-1 value at least includes a file source address and an initial approval specification; S202. Match the initial approval specifications to the corresponding approval nodes in the native data approval link in sequence to obtain a first authentication strategy.

[0039] Further, configuring the second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy includes the following steps: S211, configuring a second data interface for the approval specification data, extracting the Value-2 value of the approval specification data; the Value-2 value at least includes the file source address and the update approval specification; S212. The initial approval specification of each approval node in the first authentication strategy is replaced in sequence by updating the approval specification to obtain a second authentication strategy belonging to the twin data approval link.

[0040] Specifically, the first authentication strategy and the second authentication strategy include at least document source verification and approval verification; Specifically, the document source verification includes at least document compliance verification and document integrity verification; Specifically, the approval verification at least includes approval qualification verification, approval data verification and approval logic verification.

[0041] In this embodiment, first, the audit platform configures a first data interface for the data to be approved; the first data interface is responsible for data interaction with various systems related to the power engineering project (such as the project management system, the financial system, etc.) to extract the data to be approved. Through the first data interface, the audit platform extracts the Value-1 value of the data to be approved. In the approval of the power engineering project, the Value-1 value may include the file source address (such as the URL of a project management system) and the initial approval specification (such as the initial review requirements of the power engineering project procurement contract); the audit platform matches the extracted initial approval specifications to the corresponding approval nodes in the native data approval link B1 in sequence. For example, for the "procurement contract approval node", the audit platform will use the initial review requirements of the procurement contract as the authentication strategy of the node; the first strategy includes document compliance verification (checking whether the contract complies with relevant laws and regulations and internal company regulations), document integrity verification (ensuring that the contract content is complete), approval qualification verification (verifying whether the auditor has the corresponding qualifications), approval data verification (checking whether the contract amount, supplier information and other data are accurate) and approval logic verification (ensuring that the logical relationship between the contract terms is reasonable and correct).

[0042] Furthermore, the audit platform configures a second data interface for the approval specification data; the second data interface is used to obtain the latest approval specification update information, which may come from the company's policy updates, changes in laws and regulations, etc. Through the second data interface, the audit platform extracts the Value-2 value of the approval specification data. The Value-2 value includes the file source address (the same as or related to the file source address in the Value-1 value) and the updated approval specification (that is, the latest audit requirements and standards); the audit platform uses the extracted updated approval specification to replace the initial approval specification of each approval node in the first authentication strategy in turn. In this way, each node in the twin data approval link (D1) will apply the latest audit requirements. For example, if the latest approval specification has stricter requirements for certain terms of the procurement contract, these new requirements will be applied to the "procurement contract twin approval node" as the second authentication strategy for the node.

[0043] It is understandable that due to the irregular update of approval specification data and the large time span of the data approval process, the approval process is not completed but the approval specifications of some nodes have been updated; therefore, in order to improve the comprehensiveness and accuracy of the approval; after the approval verification of the initial data approval link, the abnormal node is found, and then the twin data approval link is updated and configured and verified through the second data interface to determine the final target twin abnormal approval node to overcome the above problems; in the approval of power projects, the file source verification ensures that all approved files are from a trusted source; the audit platform will check whether the source address of the file matches the system or database approved by the company to prevent illegal or tampered files from entering the approval process; the audit platform will check whether the content of the approved file is compliant according to the latest laws and regulations and internal company regulations. For example, the procurement contract must comply with the relevant provisions of the "Contract Law" and meet the company's internal requirements for the procurement process; the audit platform will verify the integrity of the file to ensure that the file has not been tampered with or damaged during transmission or storage; this is crucial to ensure the accuracy of the approval results; during the audit process, the audit platform will verify whether the qualifications of the auditor meet the requirements. For example, the person responsible for the review of procurement contracts must have the corresponding financial or legal background knowledge and undergo internal company training and certification. At the same time, the audit platform will verify the key data in the approved documents to ensure the accuracy and consistency of the data. In the approval of power projects, key data such as contract amount, material quantity, and supplier information may be included. Finally, the audit platform will check whether the logical relationship within the approved documents is reasonable. For example, in a procurement contract, the various clauses should be consistent and coherent, and no contradictions should occur; through the above steps, the audit platform has configured a comprehensive and flexible authentication strategy for the native data approval link and the twin data approval link in the field of power engineering, ensuring the compliance, accuracy and security of the approval process.

[0044] S3. Determine the approval result of the native data approval link according to the first authentication strategy. When the approval result meets the trigger condition of the threshold trigger mechanism, obtain the abnormal approval node of the native data approval link, and determine the target twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy.

[0045] Specifically, the approval result of the native data approval link is determined according to the first authentication strategy, and when the approval result meets the triggering condition of the threshold trigger mechanism, the abnormal approval node of the native data approval link is obtained; the steps include: S301, determining the approval result type according to the verification items in the first authentication strategy, the approval result type including the document source verification result and the approval verification result; setting a first threshold trigger mechanism subordinate to the document source verification result and a second threshold trigger mechanism subordinate to the approval verification result; S302: When the file source verification result meets the triggering condition of the first threshold triggering mechanism, the audit platform performs interface management to regenerate the standard data tuple and executes S1; S303: When the approval verification result meets the triggering condition of the second threshold triggering mechanism, the abnormal approval node of the native data approval link is obtained.

[0046] Furthermore, a first threshold trigger mechanism subordinate to the document source verification result and a second threshold trigger mechanism subordinate to the approval verification result are set; including the following steps: Determine the file source verification items based on the file source address extracted from the interface data and the approval file list; set the file compliance verification scope and file integrity verification scope corresponding to the file source verification items; and use failure to meet the file compliance verification scope and / or the file integrity verification scope as the trigger condition of the first threshold trigger mechanism; Determine the approval verification items based on the approval qualifications, approval data and approval logic extracted from the interface data; set the document approval qualification verification scope, approval data verification scope and approval logic verification sequence corresponding to the approval verification items; and use failure to meet the document approval qualification verification scope and / or approval data verification scope and / or approval logic verification sequence as the trigger condition for the second threshold trigger mechanism.

[0047] Specifically, the method of determining the twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy includes the following steps: S311. Determine a twin abnormal approval node according to the node position of the abnormal approval node in the twin data approval link; S312. Re-verify the first twin exception approval node in combination with the approval verification items in the second authentication strategy to determine the second twin exception approval node; and use the twin exception approval node as the target twin exception approval node.

[0048] In this embodiment, the audit platform divides the approval results into two categories: file source verification results and approval verification results, based on the verification items in the first authentication strategy; based on the file source address and the approval file list, the audit platform sets the file compliance verification scope and the file integrity verification scope; when the file source verification result does not meet these ranges, the first threshold mechanism is triggered. Based on the approval qualifications, approval data and approval logic, the audit platform sets the corresponding verification scope and verification order. When the approval verification result does not meet these conditions, the second threshold mechanism is triggered; if the file source verification result meets the triggering conditions of the first threshold triggering mechanism, it means that there are serious problems with the source of the file or the file itself. At this time, the audit platform will perform interface management, regenerate standard data tuples (similar to the process in S1), and execute the approval process from the beginning (i.e., execute S1). This step is designed to ensure that the source of the approval data is reliable and prevent further processing of erroneous or invalid data.

[0049] Furthermore, when the approval verification result meets the triggering condition of the second threshold trigger mechanism, the audit platform will identify and obtain the abnormal approval nodes in the original data approval link. These nodes are usually associated with specific approval issues, such as data errors, logical inconsistencies, or qualifications that do not meet the requirements; according to the position of the abnormal approval node in the original data approval link, the audit platform can find the corresponding node in the twin data approval link, that is, the first twin abnormal approval node; however, position mapping alone may not be sufficient to confirm the abnormality in the twin data; therefore, the audit platform will combine the approval verification items in the second authentication strategy (configured in S212) to re-verify the first twin abnormal approval node. This step ensures that the abnormal nodes in the twin data approval link are accurately judged based on the latest approval specifications; after re-verification, if it is confirmed that the first twin abnormal approval node is indeed abnormal, it will be regarded as the target twin abnormal approval node.

[0050] It can be understood that: the audit platform first conducts comprehensive file source verification and approval verification on the native data according to the first authentication strategy; when the verification result triggers the threshold trigger mechanism, the audit platform identifies potential problem areas, namely abnormal approval nodes; in order to confirm the prevalence and severity of the abnormality, the audit platform re-verifies the abnormal nodes through the twin data approval link; finally, the audit platform determines the target twin abnormal approval node, providing a clear direction for subsequent approval investigation and processing; through the above process, the audit platform can quickly and accurately locate problems in complex power engineering approval scenarios, and improve approval efficiency and accuracy.

[0051] S4. Determine the correlation value of each approval node in the twin data approval link based on the target twin abnormal approval node; determine the abnormal approval node troubleshooting strategy based on the correlation value.

[0052] Specifically, S4 includes the following steps: S41. Obtain the approval verification items corresponding to the target twin abnormal approval node; the approval verification items include the document approval qualification verification scope, the approval data verification scope and the approval logic verification sequence; S42. Construct triplet data according to the numerical characteristics in the approval and verification items; calculate the sum of the correlations between each target twin abnormal approval node and the primary twin abnormal approval node in the twin data approval link according to the triplet data; S43. Sort the target twin abnormal approval nodes from large to small according to the sum of the correlation degrees to obtain an abnormal approval node screening table, and execute the abnormal approval node screening strategy according to the abnormal approval node screening table in combination with the corresponding approval verification items.

[0053] Specifically, triple data is constructed according to the numerical characteristics in the approval and verification items; the sum of the correlations between each target twin abnormal approval node and the first twin abnormal approval node in the twin data approval link is calculated according to the triple data; the steps include: S421. Extract the numerical characteristics in the approval verification items to obtain the verification item values, wherein the numerical characteristics include numerical characteristics and non-numerical characteristics; the verification item values ​​corresponding to the numerical characteristics include the document approval qualification verification scope and the approval data verification scope; the verification item values ​​corresponding to the non-numerical characteristics include the approval logic verification sequence; specifically, when the approval logic verification sequence corresponding to the approval node is correct, it is "1", and when it is wrong, it is "0"; S422. Construct a triple data set M corresponding to the target twin abnormal approval node and a triple data set N corresponding to the first twin abnormal approval node according to the approval node, the approval verification item, and the verification item value; S423. Calculate the sum of the correlation between each element in the verification item triple data set M and all elements in the triple data set N according to the correlation calculation formula.

[0054] In this embodiment, first, the audit platform obtains the approval verification items corresponding to the target twin abnormal approval node. These verification items include but are not limited to the scope of document approval qualification verification, the scope of approval data verification, and the approval logic verification order. These verification items are the basis for subsequent correlation analysis and troubleshooting strategy formulation. The audit platform extracts the numerical characteristics in the approval verification items and converts them into verification item values. Numerical features (such as the scope of document approval qualification verification and the scope of approval data verification) are directly expressed in numerical form, while non-numerical features (such as approval logic verification order) are converted into numerical form through specific rules (such as "1" for correct and "0" for wrong); according to the approval node, approval verification item and verification item value, the audit platform constructs the triple data set M corresponding to the target twin abnormal approval node and the triple data set N corresponding to the first twin abnormal approval node. These triple data sets represent the key information and verification results of the approval nodes in a structured manner; the audit platform uses correlation calculation formulas (such as Pearson correlation coefficient, Spearman rank correlation coefficient, etc.) to calculate the correlation between each element in set A (representing a target twin abnormal approval node) and all elements in set B (representing all first-time twin abnormal approval nodes). Then, the correlation values ​​of each target twin abnormal approval node and all first-time twin abnormal approval nodes are summed to obtain the sum of the correlations; the audit platform sorts the target twin abnormal approval nodes from large to small according to the sum of the correlations, and generates an abnormal approval node troubleshooting table. This troubleshooting table provides a priority processing order for the approvers, helping them to first focus on those nodes that are most relevant to the anomaly; combined with the abnormal approval node troubleshooting table and the corresponding approval verification items, the audit platform formulates and implements specific troubleshooting strategies. The approvers will check each abnormal approval node one by one in the order in the troubleshooting table, and conduct detailed review and analysis according to the requirements of the verification items. During this process, the approvers may further collect evidence, communicate with relevant departments, or conduct field investigations to ensure accurate identification and handling of the problem.

[0055] It is understandable that through the implementation of step S4, the abnormal approval node troubleshooting work in the power engineering approval scenario has been significantly optimized: correlation analysis helps approval personnel quickly locate the nodes most relevant to the abnormality, reducing invalid troubleshooting work and improving overall troubleshooting efficiency; based on structured triple data and scientific correlation calculation methods, the troubleshooting strategy is more objective and accurate, reducing the risk of human misjudgment; the generated abnormal approval node troubleshooting table provides management with an intuitive overview of approval issues, helping them quickly understand the distribution and severity of the problems, and thus formulate more targeted decision-making measures.

[0056] In step S4, if the Pearson correlation coefficient method is used to calculate the correlation between the approval nodes in the twin data approval link, we can use the standard mathematical formula of the Pearson correlation coefficient. Based on the calculated correlation value, we can further generate an abnormal approval node checklist.

[0057] In this embodiment, if the Pearson correlation coefficient method is selected to calculate the correlation degree, the calculation process is as follows: The mathematical formula for the Pearson correlation coefficient r is: , in, and The values ​​of two different approval nodes (or triplet data elements) on the same verification item; and It is the average value of the same verification item at two different approval nodes. The number of abnormal approval nodes involved in the correlation calculation; since the approval verification items may contain numerical features and non-numerical features (such as the logical verification order), it is necessary to perform appropriate numerical processing on the non-numerical features (such as mapping the "correct" of the logical verification order to "1" and "error" to "0"). For each target twin abnormal approval node (element in set A) and the first twin abnormal approval node (element in set B), the correlation between them on all relevant verification items can be calculated according to the Pearson correlation coefficient method. Generally, the correlation between the two nodes on a specific verification item is first determined, and these correlation values ​​are summed or weighted averaged to obtain a comprehensive correlation value. For each target twin abnormal approval node, sum its correlation value with all the first twin abnormal approval nodes (or weighted average as needed) to obtain the total correlation of the node. Sort the target twin abnormal approval nodes from large to small according to the total correlation value. The sorted list of target twin abnormal approval nodes is used as the abnormal approval node checklist. The content of the abnormal approval node checklist may include information such as node ID, total correlation value, relevant verification items and their correlation details; Table 1 is an abnormal approval node checklist.

[0058] Table 1. Checklist of frequently used approval nodes

[0059] In Table 1, each target twin abnormal approval node has a unique node ID and a corresponding total correlation value. In addition, the verification items related to the node and their specific correlation values ​​are also shown for further analysis and processing by the approval personnel. Note that the correlation details here (such as the correlation values ​​of qualification verification, data verification, and logic verification) are exemplary, and different verification items and correlation calculation methods may be included in actual applications.

[0060] Embodiment 2: In a second aspect, a technical solution provided in an embodiment of the present invention is a bilateral authentication system for engineering data, comprising: Approval link construction module: manage the interface of the audit platform to obtain standard data tuples, and configure native data approval links and twin data approval links according to the business type of the standard data tuples; Authentication module: configure a first authentication strategy for the native data approval link according to the first data interface; configure a second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy; Abnormal determination module: Determine the approval result of the native data approval link according to the first authentication strategy. When the approval result meets the trigger condition of the threshold trigger mechanism, obtain the abnormal approval node of the native data approval link, and determine the target twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy; Execution module: Determine the correlation value of each approval node in the twin data approval link based on the target twin abnormal approval node; determine the abnormal approval node troubleshooting strategy based on the correlation value.

[0061] This embodiment has the following technical effects: by performing interface management on the audit platform, standard data tuples are obtained, and the native data approval link and the twin data approval link are flexibly configured according to the business type, which not only ensures the standardized processing of data, but also provides adaptability to different business scenarios; further, the first authentication strategy and the second authentication strategy are respectively configured for the native data approval link and the twin data approval link, forming a two-layer authentication mechanism, which effectively improves the security and accuracy of approval data screening; further, when the approval result of the native data approval link triggers the threshold mechanism, it can automatically identify abnormal approval nodes and locate the corresponding target twin abnormal approval nodes in the twin data approval link, thereby achieving rapid response and precise positioning of abnormal situations; by calculating the correlation value of each approval node in the twin data approval link, it can more comprehensively analyze the impact range of the abnormal approval node, and then formulate a more effective abnormal approval node screening strategy. The solution realizes standardized processing, two-layer security verification, intelligent exception processing and abnormal security screening strategy in engineering approval data through interface fusion and bilateral authentication technology, which significantly improves the efficiency, security and intelligence level of approval data processing.

[0062] Embodiment three: A technical solution provided in an embodiment of the present invention is an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor calls the computer program in the memory, the steps of a bilateral authentication method for engineering data based on interface fusion technology are implemented.

[0063] Embodiment 4: A technical solution provided in an embodiment of the present invention is a storage medium, in which computer executable instructions are stored. When the computer executable instructions are loaded and executed by a processor, the steps of a bilateral authentication method for engineering data based on interface fusion technology are implemented.

[0064] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the specific device can be divided into different functional modules to complete all or part of the functions described above.

[0065] In the embodiments provided in the present application, it should be understood that the disclosed structures and methods can be implemented in other ways. For example, the embodiments of the structure described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another structure, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, structures or units, which can be electrical, mechanical or other forms.

[0066] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0067] In addition, each functional unit in the embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0068] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0069] The specific implementation described above is a preferred implementation of the engineering data bilateral authentication method and system based on interface fusion technology of the present invention, and is not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to this specific implementation. All equivalent changes made in accordance with the shape and structure of the present invention are within the protection scope of the present invention.

Claims

1. A bilateral authentication method for engineering data based on interface fusion technology, characterized in that: The steps include: S1. Perform interface management on the audit platform to obtain standard data tuples, and configure native data approval links and twin data approval links according to the business type of the standard data tuples; S2. Configure a first authentication strategy for the native data approval link according to the first data interface; Configure a second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy; S3. Determine the approval result of the native data approval link according to the first authentication strategy. When the approval result meets the trigger condition of the threshold trigger mechanism, obtain the abnormal approval node of the native data approval link, and determine the target twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy; S4. Determine the correlation value of each approval node in the twin data approval link based on the target twin abnormal approval node; determine the abnormal approval node troubleshooting strategy based on the correlation value.

2. According to claim 1, the bilateral authentication method for engineering data based on interface fusion technology is characterized in that: The interface management of the audit platform is performed to obtain a standard data tuple, and the native data approval link and the twin data approval link are configured according to the business type of the standard data tuple; the steps include: S11. The audit platform extracts the source characteristics and content characteristics of the interface data, and uses the source characteristics as the Key value of the standard data tuple and the content characteristics as the Value value of the standard data tuple; S12. Determine the business type based on the Key value of the standard data tuple, and match the corresponding approval node and approval path for the business type; construct the native data approval link and twin data approval link of the corresponding interface data based on the approval node, approval path and Value value.

3. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 2 is characterized in that: The interface data includes data to be approved and approval specification data; the configuring a first authentication strategy for the native data approval link according to the first data interface includes the following steps: S201, configuring a first data interface for the data to be approved, and extracting the Value-1 value of the data to be approved; the Value-1 value at least includes a file source address and an initial approval specification; S202. Match the initial approval specifications to the corresponding approval nodes in the native data approval link in sequence to obtain a first authentication strategy.

4. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 3 is characterized in that: The method of configuring the second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy includes the following steps: S211, configuring a second data interface for the approval specification data, extracting the Value-2 value of the approval specification data; the Value-2 value at least includes the file source address and the update approval specification; S212. The initial approval specification of each approval node in the first authentication strategy is replaced in sequence by updating the approval specification to obtain a second authentication strategy belonging to the twin data approval link.

5. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 4 is characterized in that: The first authentication strategy and the second authentication strategy at least include document source verification and approval verification; The document source verification at least includes document compliance verification and document integrity verification; The approval verification at least includes approval qualification verification, approval data verification and approval logic verification.

6. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 1 is characterized in that: The method of determining the approval result of the native data approval link according to the first authentication strategy, and obtaining the abnormal approval node of the native data approval link when the approval result meets the triggering condition of the threshold trigger mechanism, comprises the following steps: S301. Determine the approval result type according to the verification items in the first authentication strategy, where the approval result type includes the document source verification result and the approval verification result; Set up a first threshold trigger mechanism affiliated with the document source verification result and a second threshold trigger mechanism affiliated with the approval verification result; S302: When the file source verification result meets the triggering condition of the first threshold triggering mechanism, the audit platform performs interface management to regenerate the standard data tuple and executes S1; S303: When the approval verification result meets the triggering condition of the second threshold triggering mechanism, the abnormal approval node of the native data approval link is obtained.

7. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 6 is characterized in that: The setting of the first threshold trigger mechanism subordinate to the document source verification result and the second threshold trigger mechanism subordinate to the approval verification result comprises the following steps: Determine the file source verification items based on the file source address extracted from the interface data and the approval file list; set the file compliance verification scope and file integrity verification scope corresponding to the file source verification items; and use failure to meet the file compliance verification scope and / or the file integrity verification scope as the trigger condition of the first threshold trigger mechanism; Determine the approval verification items based on the approval qualifications, approval data and approval logic extracted from the interface data; set the document approval qualification verification scope, approval data verification scope and approval logic verification sequence corresponding to the approval verification items; Failure to meet the document approval qualification verification scope and / or approval data verification scope and / or approval logic verification sequence will be used as the triggering condition of the second threshold trigger mechanism.

8. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 1 or 6, characterized in that: The method of determining the twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy comprises the following steps: S311. Determine a twin abnormal approval node according to the node position of the abnormal approval node in the twin data approval link; S312. Re-verify the first twin exception approval node in combination with the approval verification items in the second authentication strategy to determine the second twin exception approval node; and use the twin exception approval node as the target twin exception approval node.

9. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 1 is characterized in that: The method of determining the correlation value of each approval node in the twin data approval link according to the target twin abnormal approval node; and determining the abnormal approval node troubleshooting strategy according to the correlation value comprises the following steps: S41. Obtain the approval verification items corresponding to the target twin abnormal approval node; the approval verification items include the document approval qualification verification scope, the approval data verification scope and the approval logic verification sequence; S42. Construct triplet data according to the numerical characteristics in the approval and verification items; calculate the sum of the correlations between each target twin abnormal approval node and the primary twin abnormal approval node in the twin data approval link according to the triplet data; S43. Sort the target twin abnormal approval nodes from large to small according to the sum of the correlation degrees to obtain an abnormal approval node screening table, and execute the abnormal approval node screening strategy according to the abnormal approval node screening table in combination with the corresponding approval verification items.

10. The method for bilateral authentication of engineering data based on interface fusion technology according to claim 1 or 9, characterized in that: The method of constructing triplet data according to the numerical characteristics in the approval and verification items; and calculating the sum of the correlations between each target twin abnormal approval node and the primary twin abnormal approval node in the twin data approval link according to the triplet data; comprises the following steps: S421. Extract the numerical characteristics in the approval verification items to obtain the verification item values, wherein the numerical characteristics include numerical characteristics and non-numerical characteristics; the verification item values ​​corresponding to the numerical characteristics include the document approval qualification verification scope and the approval data verification scope; the verification item values ​​corresponding to the non-numerical characteristics include the approval logic verification sequence; specifically, when the approval logic verification sequence corresponding to the approval node is correct, it is "1", and when it is wrong, it is "0"; S422. Construct a triple data set M corresponding to the target twin abnormal approval node and a triple data set N corresponding to the first twin abnormal approval node according to the approval node, the approval verification item, and the verification item value; S423. Calculate the sum of the correlation between each element in the verification item triple data set M and all elements in the triple data set N according to the correlation calculation formula.

11. A bilateral authentication system for engineering data, applicable to the bilateral authentication method for engineering data based on interface fusion technology as claimed in any one of claims 1 to 10, characterized in that: Included are: Audit link construction module: manage the interface of the audit platform to obtain standard data tuples, and configure native data approval links and twin data approval links according to the business type of the standard data tuples; Authentication module: configuring a first authentication strategy for the native data approval link according to the first data interface; Configure a second authentication strategy for the twin data approval link according to the second data interface and the first authentication strategy; Abnormal determination module: Determine the approval result of the native data approval link according to the first authentication strategy. When the approval result meets the trigger condition of the threshold trigger mechanism, obtain the abnormal approval node of the native data approval link, and determine the target twin abnormal approval node in the twin data approval link according to the abnormal approval node and the second authentication strategy; Execution module: Determine the correlation value of each approval node in the twin data approval link based on the target twin abnormal approval node; determine the abnormal approval node troubleshooting strategy based on the correlation value.

12. An electronic device, characterized in that: It comprises a memory and a processor, wherein the memory stores a computer program, and when the processor calls the computer program in the memory, it implements the steps of the bilateral authentication method for engineering data based on interface fusion technology as described in any one of claims 1 to 10.

13. A storage medium, characterized in that: The storage medium stores computer executable instructions, which, when loaded and executed by the processor, implement the steps of the bilateral authentication method for engineering data based on interface fusion technology as described in any one of claims 1 to 10.

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