Implementation method for hiding service call logic based on function

Abstract

The invention discloses an implementation method for hiding service calling logic based on a function, relates to the technical field of software engineering, and aims to more comprehensively protect key function points in a target system and improve the overall safety and stability of the system by acquiring a comprehensive evaluation coefficient and judging hiding protection. The method is beneficial to comprehensive evaluation protection, personalized protection, data protection, resource optimization, risk reduction and system stability improvement, so that the safety, performance and reliability of a software system are improved, a more stable guarantee is provided for system operation, and the method can be used for improving the safety, performance and reliability of the software system by comprehensively evaluating the value, dependency and sensitivity of each key function point in the system. Which function points need to be subjected to hidden protection can be effectively judged, and corresponding protection strategies can be formulated. Therefore, important functions in the system can be effectively protected, and the risk that the system is hostile attacked or damaged is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of software engineering, and in particular to an implementation method based on function-hiding business call logic. Background Art

[0002] In the field of software engineering, with the continuous development and application of information technology, the complexity and scale of software systems continue to increase, and they also face increasing security threats and risks. Traditional software development and protection methods can no longer fully meet these challenges. Continuous innovation and improvement of software engineering technology are needed to improve the security, stability, and reliability of software systems. Therefore, a method based on function-based hiding of business call logic is needed.

[0003] Existing software development and protection methods may not be able to fully protect key functional points in the system, making the system vulnerable to malicious attacks and data leakage threats. Obviously, this implementation method has at least the following problems: 1. As the complexity and scale of software systems increase, the stability and reliability of the system may be affected, and failures and performance problems may occur, affecting user experience and business operations. The lack of comprehensive evaluation of key functional points and the formulation of protection strategies may lead to an increased risk of sensitive data leakage, affecting user privacy and data security. The software system may face challenges such as insufficient security, stability and reliability issues, increased risk of data leakage, insufficient business logic optimization, and lack of an overall system security protection strategy;

[0004] 2. Existing technologies lack analysis and optimization of business logic influencing factors for key functional points, which may lead to poor system performance and excessive resource consumption, affecting the system's operating efficiency and response speed. At the same time, there is a lack of comprehensive evaluation and formulation of hidden protection strategies for each key functional point. The overall security protection strategy of the system is not perfect and is vulnerable to external attacks and threats. Summary of the Invention

[0005] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide an implementation method for hiding business call logic based on functions.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an implementation method based on function-hidden business call logic, including: Step 1, acquisition of value, dependency and sensitive data: Acquire the value, dependency and sensitive data corresponding to each key functional point in the target system, the value data includes revenue contribution value, user activity and market share, the dependency data includes function dependency, service dependency and system integration, and the sensitive data includes the number of data leaks, data access frequency and data sharing scope.

[0007] Step 2: Analysis of value, dependency, and sensitive data: Based on the value, dependency, and sensitive data corresponding to each key functional point in the target system, analyze and obtain the value assessment coefficient, dependency assessment coefficient, and sensitivity assessment coefficient corresponding to each key functional point in the target system.

[0008] Step 6. Obtain business logic impact factors: Obtain business logic performance data corresponding to each key functional point in the target system. Business logic performance data includes response time, processing data volume, and resource consumption. Then analyze and obtain the business logic impact factors corresponding to each key functional point in the target system.

[0009] Step 3. Obtaining comprehensive evaluation coefficients: Based on the value evaluation coefficients, dependency evaluation coefficients, and sensitivity evaluation coefficients corresponding to each key functional point in the target system, analyze and obtain the comprehensive evaluation coefficients corresponding to each key functional point in the target system.

[0010] Step 4: Determine whether to hide or protect the key function points: Based on the comprehensive evaluation coefficients corresponding to the key function points in the target system, determine whether the key function points in the target system need to be hidden or protected, and record the key function points in the target system that need to be hidden or protected as the key function points to be hidden.

[0011] Step 5: Formulate a hidden protection strategy: Based on the comprehensive evaluation coefficient corresponding to each key functional point to be hidden, analyze the hidden protection strategy corresponding to each key functional point to be hidden, and formulate each key functional point to be hidden according to the corresponding hidden protection strategy.

[0012] Preferably, the analysis obtains the value evaluation coefficient corresponding to each key function point in the target system. The specific analysis process is as follows: the revenue contribution value, user activity and market share corresponding to each key function point in the target system are recorded as Q g 、W g and E g , where g represents the number corresponding to each key function point, g=1,2......n, n is any integer greater than 2, substitute into the calculation formula The value assessment coefficient α corresponding to each key function point in the target system is obtained g , where Q ′ , W′, E′ respectively represent the standard revenue contribution value, standard user activity, and standard market share corresponding to the key functional points in the set target system; θ1, θ2, θ3 respectively represent the weight factors corresponding to the revenue contribution value, user activity, and market share of the key functional points in the set target system.

[0013] Preferably, the analysis obtains the dependency evaluation coefficient corresponding to each key function point in the target system. The specific analysis process is as follows: the function dependency, service dependency and service dependency corresponding to each key function point in the target system are respectively recorded as R g 、T g and Y g , substitute into the calculation formula In the above example, we can get the dependency evaluation coefficient β corresponding to each key function point in the target system. g , where R ′ 、T ′ 、Y ′ They are respectively expressed as the standard function dependency, standard service dependency, and standard service dependency corresponding to the key function points in the target system. They are respectively expressed as the weight factors corresponding to the functional dependency of key functional points in the set target system, the weight factors corresponding to the service dependency, and the weight factors corresponding to the service dependency.

[0014] Preferably, the analysis obtains the sensitivity assessment coefficient corresponding to each key functional point in the target system. The specific analysis process is as follows: the number of data leakage, data access frequency and data sharing range corresponding to each key functional point in the target system are respectively recorded as D g 、F g and H g , substitute into the calculation formula The sensitivity evaluation coefficient χ corresponding to each key function point in the target system is obtained g , where D ′ 、F ′ 、H ′ They are respectively represented as the standard data leakage times, standard data access frequency, and standard data sharing scope corresponding to the key functional points in the target system. They are respectively expressed as the weight factor corresponding to the number of data leakages at key functional points in the set target system, the weight factor corresponding to the data access frequency, and the weight factor corresponding to the data sharing scope.

[0015] Preferably, the analysis obtains the business logic impact factors corresponding to each key function point in the target system. The specific analysis process is as follows: the response time, processing data volume and resource consumption corresponding to each key function point in the target system are respectively recorded as Z g 、C g and V g , substitute into the calculation formula The sensitivity evaluation coefficient δ corresponding to each key function point in the target system is obtained g , where Z′, C ′ 、V ′They are respectively represented as the standard response time, standard processing data volume, and standard resource consumption corresponding to the key functional points in the set target system. They are respectively expressed as the weight factor corresponding to the response time of the key functional points in the set target system, the weight factor corresponding to the amount of processed data, and the weight factor corresponding to the resource consumption.

[0016] Preferably, the analysis obtains the comprehensive evaluation coefficient corresponding to each key function point in the target system. The specific analysis process is as follows: Substitute the value evaluation coefficient, dependency evaluation coefficient, sensitivity evaluation coefficient and business logic impact factor corresponding to each key function point in the target system into the calculation formula The comprehensive evaluation coefficient γg corresponding to each key function point in the target system is obtained, where π1, π2, and π2 are the weight factors corresponding to the value evaluation coefficient of the key function point in the set target system, the weight factor corresponding to the dependency evaluation coefficient, and the weight factor corresponding to the sensitivity evaluation coefficient, respectively, and e represents a natural constant.

[0017] Preferably, the judgment of whether each key function point in the target system needs to be hidden and protected is carried out as follows: the comprehensive evaluation coefficient corresponding to each key function point in the target system is compared with the comprehensive evaluation coefficient corresponding to the set standard key function point. If the comprehensive evaluation coefficient corresponding to a key function point in the target system is less than the comprehensive evaluation coefficient corresponding to the set standard key function point, it is judged that the key function point in the target system needs to be hidden and protected. If the comprehensive evaluation coefficient corresponding to a key function point in the target system is greater than or equal to the comprehensive evaluation coefficient corresponding to the set standard key function point, it is judged that the key function point in the target system does not need to be hidden and protected. In this way, whether each key function point in the target system needs to be hidden and protected is judged.

[0018] Preferably, the analysis of the hidden protection strategies corresponding to each key functional point to be hidden is carried out as follows: the comprehensive evaluation coefficient corresponding to each key functional point to be hidden is compared with the comprehensive evaluation coefficient corresponding to each hidden protection strategy in the database; if the comprehensive evaluation coefficient corresponding to a key functional point to be hidden is the same as the comprehensive evaluation coefficient corresponding to a hidden protection strategy in the database, then the hidden protection strategy is used as the hidden protection strategy corresponding to the key functional point to be hidden, and the hidden protection strategies corresponding to each key functional point to be hidden are analyzed in this way.

[0019] The beneficial effects of the present invention are: 1. The present invention provides an implementation method based on function-hidden business call logic. By obtaining comprehensive evaluation coefficients and hidden protection judgments, it can more comprehensively protect key functional points in the target system, improve the overall security and stability of the system, and help to comprehensively evaluate protection, personalized protection, data protection, resource optimization, risk reduction and system stability improvement, thereby improving the security, performance and reliability of the software system and providing more robust protection for system operation.

[0020] 2. By comprehensively evaluating the value, dependencies, and sensitivity of each key functional point in the system, the present invention helps effectively determine which functional points require hidden protection and formulate corresponding protection strategies. This effectively protects important system functions and reduces the risk of malicious attacks or damage. Furthermore, by analyzing business logic influencing factors, a hidden protection strategy can be customized for each key functional point to minimize the impact on system performance and resource consumption, thereby optimizing overall system performance.

[0021] 3. By analyzing sensitive data and developing a privacy protection strategy, the present invention helps protect sensitive data from unauthorized access and leakage. This is particularly important for industries involving large amounts of sensitive data, such as finance, healthcare, and personal privacy protection. It helps improve system security, performance, and compliance, providing a comprehensive and effective approach. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 The present invention is a flowchart of the steps for implementing the method. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0025] The present invention is implemented as follows Figure 1As shown, an implementation method based on function-hidden business call logic includes: Step 1, acquisition of value, dependency and sensitive data: acquiring the value, dependency and sensitive data corresponding to each key functional point in the target system, wherein the value data includes revenue contribution value, user activity and market share, the dependency data includes function dependency, service dependency and system integration, and the sensitive data includes the number of data leaks, data access frequency and data sharing scope.

[0026] It should be noted that relevant data is obtained through sales data, user behavior analysis, market research, etc., and data analysis tools and statistical methods are used to obtain the revenue contribution value, user activity and market share corresponding to each key functional point in the target system.

[0027] It should also be noted that by analyzing the calling relationship, data transmission relationship, service dependency and system integration degree between the functional modules in the system, the system architecture diagram, interface documents, etc. can be used to help obtain the functional dependency, service dependency and system integration degree corresponding to each key functional point in the target system.

[0028] Once again, it is important to note that by monitoring security logs, access records, permission settings and other information to discover data leakage, access frequency and sharing scope, this can be achieved with the help of security monitoring tools and audit systems, thereby obtaining the number of data leakage, data access frequency and data sharing scope corresponding to each key functional point in the target system.

[0029] Step 2: Analysis of value, dependency, and sensitive data: Based on the value, dependency, and sensitive data corresponding to each key functional point in the target system, analyze and obtain the value assessment coefficient, dependency assessment coefficient, and sensitivity assessment coefficient corresponding to each key functional point in the target system.

[0030] In a specific embodiment, the analysis obtains the value evaluation coefficient corresponding to each key function point in the target system. The specific analysis process is as follows: the revenue contribution value, user activity and market share corresponding to each key function point in the target system are respectively recorded as Q g 、W g and E g , where g represents the number corresponding to each key function point, g=1,2......n, n is any integer greater than 2, substitute into the calculation formula The value assessment coefficient α corresponding to each key function point in the target system is obtained g , where Q ′, W′, E′ respectively represent the standard revenue contribution value, standard user activity, and standard market share corresponding to the key functional points in the set target system; θ1, θ2, θ3 respectively represent the weight factors corresponding to the revenue contribution value, user activity, and market share of the key functional points in the set target system.

[0031] In a specific embodiment, the analysis obtains the dependency evaluation coefficient corresponding to each key function point in the target system. The specific analysis process is as follows: the function dependency, service dependency and service dependency corresponding to each key function point in the target system are respectively denoted as R g 、T g and Y g , substitute into the calculation formula In the above example, we can get the dependency evaluation coefficient β corresponding to each key function point in the target system. g , where R ′ 、T ′ 、Y ′ They are respectively expressed as the standard function dependency, standard service dependency, and standard service dependency corresponding to the key function points in the target system. They are respectively expressed as the weight factors corresponding to the functional dependency of key functional points in the set target system, the weight factors corresponding to the service dependency, and the weight factors corresponding to the service dependency.

[0032] In a specific embodiment, the analysis obtains the sensitivity evaluation coefficient corresponding to each key function point in the target system. The specific analysis process is as follows: the number of data leakage, data access frequency and data sharing range corresponding to each key function point in the target system are respectively recorded as D g 、F g and H g , substitute into the calculation formula The sensitivity evaluation coefficient χ corresponding to each key function point in the target system is obtained g , where D ′ 、F ′ 、H ′ They are respectively represented as the standard data leakage times, standard data access frequency, and standard data sharing scope corresponding to the key functional points in the target system. They are respectively expressed as the weight factor corresponding to the number of data leakages at key functional points in the set target system, the weight factor corresponding to the data access frequency, and the weight factor corresponding to the data sharing scope.

[0033] Step 3: Obtain business logic impact factors: Obtain business logic performance data corresponding to each key functional point in the target system. Business logic performance data includes response time, data processing volume, and resource consumption. Then analyze and obtain the business logic impact factors corresponding to each key functional point in the target system.

[0034] It should be noted that by recording relevant information such as response time, data processing volume and resource consumption through system logs, the logs can be analyzed using log analysis tools to extract key performance data, thereby obtaining the response time, data processing volume and resource consumption corresponding to each key functional point in the target system.

[0035] In a specific embodiment, the analysis obtains the business logic impact factors corresponding to each key function point in the target system. The specific analysis process is as follows: the response time, processing data volume and resource consumption corresponding to each key function point in the target system are respectively recorded as Z g 、C g and V g , substitute into the calculation formula The sensitivity evaluation coefficient δ corresponding to each key function point in the target system is obtained g , where Z′, C ′ 、V ′ They are respectively represented as the standard response time, standard processing data volume, and standard resource consumption corresponding to the key functional points in the set target system. They are respectively expressed as the weight factor corresponding to the response time of the key functional points in the set target system, the weight factor corresponding to the amount of processed data, and the weight factor corresponding to the resource consumption.

[0036] Step 4. Obtaining comprehensive evaluation coefficients: Based on the value evaluation coefficients, dependency evaluation coefficients, and sensitivity evaluation coefficients corresponding to each key functional point in the target system, analyze and obtain the comprehensive evaluation coefficients corresponding to each key functional point in the target system.

[0037] In a specific embodiment, the analysis obtains the comprehensive evaluation coefficient corresponding to each key function point in the target system. The specific analysis process is as follows: Substitute the value evaluation coefficient, dependency evaluation coefficient, sensitivity evaluation coefficient and business logic impact factor corresponding to each key function point in the target system into the calculation formula The comprehensive evaluation coefficient γg corresponding to each key function point in the target system is obtained, where π1, π2, and π2 are the weight factors corresponding to the value evaluation coefficient of the key function point in the target system, the weight factor corresponding to the dependency evaluation coefficient, and the weight factor corresponding to the sensitivity evaluation coefficient, respectively, and e represents a natural constant.

[0038] The embodiments of the present invention, by comprehensively evaluating the value, dependencies, and sensitivity of each key functional point in the system, help effectively determine which functional points require hidden protection and formulate corresponding protection strategies. This effectively protects important functions in the system and reduces the risk of malicious attacks or damage to the system. Furthermore, by analyzing the impact factors of business logic, a hidden protection strategy can be customized for each key functional point to minimize the impact on system performance and resource consumption, thereby optimizing overall system performance.

[0039] Step 5. Determination of hidden protection: Based on the comprehensive evaluation coefficient corresponding to each key function point in the target system, determine whether each key function point in the target system needs to be hidden and protected, and record each key function point in the target system that needs to be hidden and protected as each key function point to be hidden.

[0040] In a specific embodiment, the determination of whether each key function point in the target system needs to be hidden and protected is carried out as follows: the comprehensive evaluation coefficient corresponding to each key function point in the target system is compared with the comprehensive evaluation coefficient corresponding to the set standard key function point. If the comprehensive evaluation coefficient corresponding to a key function point in the target system is less than the comprehensive evaluation coefficient corresponding to the set standard key function point, it is determined that the key function point in the target system needs to be hidden and protected. If the comprehensive evaluation coefficient corresponding to a key function point in the target system is greater than or equal to the comprehensive evaluation coefficient corresponding to the set standard key function point, it is determined that the key function point in the target system does not need to be hidden and protected. In this way, whether each key function point in the target system needs to be hidden and protected is determined.

[0041] Step 6: Formulate a hidden protection strategy: Based on the comprehensive evaluation coefficient corresponding to each key functional point to be hidden, analyze the hidden protection strategy corresponding to each key functional point to be hidden, and formulate each key functional point to be hidden according to the corresponding hidden protection strategy.

[0042] In a specific embodiment, the analysis of the hidden protection strategies corresponding to each key functional point to be hidden is as follows: the comprehensive evaluation coefficient corresponding to each key functional point to be hidden is compared with the comprehensive evaluation coefficient corresponding to each hidden protection strategy in the database. If the comprehensive evaluation coefficient corresponding to a key functional point to be hidden is the same as the comprehensive evaluation coefficient corresponding to a hidden protection strategy in the database, then the hidden protection strategy is used as the hidden protection strategy corresponding to the key functional point to be hidden. In this way, the hidden protection strategies corresponding to each key functional point to be hidden are analyzed.

[0043] By analyzing sensitive data and developing a privacy protection strategy, the present invention helps protect sensitive data from unauthorized access and leakage. This is particularly important for industries where businesses involve large amounts of sensitive data, such as finance, healthcare, and personal privacy protection. It helps improve system security, performance, and compliance, providing a comprehensive and effective approach.

[0044] The present invention provides an implementation method based on function hidden business call logic. By obtaining a comprehensive evaluation coefficient and making hidden protection judgments, it can more comprehensively protect key functional points in the target system, improve the overall security and stability of the system, and contribute to comprehensive evaluation protection, personalized protection, data protection, resource optimization, risk reduction, and system stability improvement, thereby improving the security, performance, and reliability of the software system and providing a more robust guarantee for system operation.

[0045] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. A method for implementing function-based hidden business call logic, characterized in that: include: Step 1: Acquire value, dependency, and sensitive data: Obtain the value, dependency, and sensitive data corresponding to each key functional point in the target system. Value data includes revenue contribution, user activity, and market share. Dependency data includes functional dependency, service dependency, and system integration. Sensitive data includes the number of data leaks, data access frequency, and data sharing scope. Step 2: Analysis of value, dependency, and sensitive data: Based on the value, dependency, and sensitive data corresponding to each key function point in the target system, analyze and obtain the value assessment coefficient, dependency assessment coefficient, and sensitivity assessment coefficient corresponding to each key function point in the target system; Step 3: Obtaining business logic impact factors: Obtain business logic performance data corresponding to each key functional point in the target system. Business logic performance data includes response time, data processing volume, and resource consumption. Then, analyze and obtain the business logic impact factors corresponding to each key functional point in the target system. Step 4: Obtaining comprehensive evaluation coefficients: Based on the value evaluation coefficients, dependency evaluation coefficients, and sensitivity evaluation coefficients corresponding to each key function point in the target system, analyze and obtain the comprehensive evaluation coefficients corresponding to each key function point in the target system; Step 5: Determine whether to hide or protect the key function points in the target system: Based on the comprehensive evaluation coefficients corresponding to the key function points in the target system, determine whether the key function points in the target system need to be hidden or protected, and record the key function points in the target system that need to be hidden or protected as key function points to be hidden; Step 6: Formulate a hidden protection strategy: Based on the comprehensive evaluation coefficient corresponding to each key functional point to be hidden, analyze the hidden protection strategy corresponding to each key functional point to be hidden, and formulate each key functional point to be hidden according to the corresponding hidden protection strategy.

2. The method for implementing function-based hiding of business call logic according to claim 1, characterized in that: The analysis obtains the value assessment coefficient corresponding to each key functional point in the target system. The specific analysis process is as follows: The revenue contribution value, user activity and market share corresponding to each key functional point in the target system are respectively denoted as Q g 、W g and E g , where g represents the number corresponding to each key function point, g=1,2......n, n is any integer greater than 2, substitute into the calculation formula The value assessment coefficient α corresponding to each key function point in the target system is obtained g , where Q ′ , W′, E′ respectively represent the standard revenue contribution value, standard user activity, and standard market share corresponding to the key functional points in the set target system; θ1, θ2, θ3 respectively represent the weight factors corresponding to the revenue contribution value, user activity, and market share of the key functional points in the set target system.

3. The method for implementing function-based hidden business call logic according to claim 2, characterized in that: The analysis obtains the dependency evaluation coefficients corresponding to each key functional point in the target system. The specific analysis process is as follows: The functional dependency, service dependency and service dependency corresponding to each key functional point in the target system are respectively denoted as R g 、T g and Y g , substitute into the calculation formula In the above example, we can get the dependency evaluation coefficient β corresponding to each key function point in the target system. g , where R ′ 、T ′ 、Y ′ They are respectively expressed as the standard function dependency, standard service dependency, and standard service dependency corresponding to the key function points in the target system. They are respectively expressed as the weight factors corresponding to the functional dependency of key functional points in the set target system, the weight factors corresponding to the service dependency, and the weight factors corresponding to the service dependency.

4. The method for implementing function-based hiding of business call logic according to claim 3, characterized in that: The analysis obtains the sensitivity evaluation coefficient corresponding to each key functional point in the target system. The specific analysis process is as follows: The number of data leaks, data access frequency, and data sharing scope corresponding to each key functional point in the target system are respectively denoted as D g 、F g and H g , substitute into the calculation formula The sensitivity evaluation coefficient χ corresponding to each key function point in the target system is obtained g , where D ′ 、F ′ 、H ′ They are respectively represented as the standard data leakage times, standard data access frequency, and standard data sharing scope corresponding to the key functional points in the target system. They are respectively expressed as the weight factor corresponding to the number of data leakages at key functional points in the set target system, the weight factor corresponding to the data access frequency, and the weight factor corresponding to the data sharing scope.

5. The method for implementing function-based hiding of business call logic according to claim 4, characterized in that: The analysis obtains the business logic impact factors corresponding to each key functional point in the target system. The specific analysis process is as follows: The response time, processing data volume and resource consumption of each key functional point in the target system are respectively denoted as Z g 、C g and V g , substitute into the calculation formula The sensitivity evaluation coefficient δ corresponding to each key function point in the target system is obtained g , where Z′, C ′ 、V ′ They are respectively represented as the standard response time, standard processing data volume, and standard resource consumption corresponding to the key functional points in the set target system. They are respectively expressed as the weight factor corresponding to the response time of the key functional points in the set target system, the weight factor corresponding to the amount of processed data, and the weight factor corresponding to the resource consumption.

6. The method for implementing function-based hiding of business call logic according to claim 5, characterized in that: The analysis obtains the comprehensive evaluation coefficient corresponding to each key functional point in the target system. The specific analysis process is as follows: Substitute the value assessment coefficient, dependency assessment coefficient, sensitivity assessment coefficient and business logic impact factor corresponding to each key function point in the target system into the calculation formula The comprehensive evaluation coefficient γg corresponding to each key function point in the target system is obtained, where π1, π2, and π2 are the weight factors corresponding to the value evaluation coefficient of the key function point in the target system, the weight factor corresponding to the dependency evaluation coefficient, and the weight factor corresponding to the sensitivity evaluation coefficient, respectively, and e represents a natural constant.

7. The method for implementing function-based hiding of business call logic according to claim 6, characterized in that: The specific judgment process of whether each key functional point in the target system needs to be hidden and protected is as follows: The comprehensive evaluation coefficient corresponding to each key function point in the target system is compared with the comprehensive evaluation coefficient corresponding to the set standard key function point. If the comprehensive evaluation coefficient corresponding to a key function point in the target system is smaller than the comprehensive evaluation coefficient corresponding to the set standard key function point, it is determined that the key function point in the target system needs to be hidden and protected. If the comprehensive evaluation coefficient corresponding to a key function point in the target system is greater than or equal to the comprehensive evaluation coefficient corresponding to the set standard key function point, it is determined that the key function point in the target system does not need to be hidden and protected. In this way, whether each key function point in the target system needs to be hidden and protected is determined.

8. The method for implementing function-based hiding of business call logic according to claim 1, characterized in that: The analysis of the hidden protection strategy corresponding to each key functional point to be hidden is as follows: The comprehensive evaluation coefficient corresponding to each key function point to be hidden is compared with the comprehensive evaluation coefficient corresponding to each hidden protection strategy in the database. If the comprehensive evaluation coefficient corresponding to a key function point to be hidden is the same as the comprehensive evaluation coefficient corresponding to a hidden protection strategy in the database, then the hidden protection strategy is used as the hidden protection strategy corresponding to the key function point to be hidden. In this way, the hidden protection strategies corresponding to each key function point to be hidden are analyzed.

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