A security risk detection system and method for airborne software supply chain

Abstract

This invention belongs to the field of airborne software supply chain technology, and relates to an airborne software supply chain security risk detection system and method. The system includes a risk data acquisition module for collecting risk data in the software supply chain; a vulnerability risk data analysis module for receiving data from the vulnerability risk data acquisition unit in the risk data acquisition module, analyzing and calculating the vulnerability risk index, and transmitting it to the overall risk analysis module; a component risk data analysis module for receiving data from the component risk data acquisition unit in the risk data acquisition module, analyzing and calculating the component risk index, and transmitting it to the overall risk analysis module; an overall risk analysis module for receiving data from the vulnerability risk data analysis module and the component risk data analysis module, analyzing and calculating the overall risk index of the software supply chain, and transmitting it to the early warning module; an early warning module for receiving data from the overall risk analysis module, determining the overall risk index and issuing an early warning, and transmitting the early warning result to the human-computer interaction module, where the early warning result is either "warning required" or "warning not required"; and a human-computer interaction module for displaying the data interactively.

Description

Technical Field

[0001] This invention belongs to the field of aviation airborne software supply chain technology, and relates to an aviation airborne software supply chain security risk detection system and method. Background Technology

[0002] The airborne software supply chain is a collection of software packages organized according to calling relationships during the development or operation of a software system. In the ICT era, software is an important component and foundation of enterprise applications, playing an increasingly important role. Once a software security risk occurs, it will affect the normal operation of the entire business system. For the software supply chain, there are many risky components, among which the most important source of risk is software vulnerability risk. If a security vulnerability exists in a software product, it will have a serious impact on the security of the system involving that software product.

[0003] Software supply chain security vulnerabilities refer to security weaknesses or defects inherent in the design, development, or deployment of software itself. These vulnerabilities exist in the overall construction or design of the software and can be exploited by attackers to pose a system threat. Detection and evaluation are typically conducted using techniques such as static analysis, dynamic analysis, vulnerability scanning tools, and code review. The aim is to identify software weaknesses and potentially exploitable vulnerabilities, such as buffer overflows, code injection, and logical flaws.

[0004] Component vulnerabilities typically refer to security flaws or risks inherent in third-party components, libraries, or dependencies used in software. These components are integral parts of the overall software system. Component vulnerabilities are usually discovered using third-party vulnerability databases or specific component vulnerability detection tools, such as the various known vulnerabilities recorded in a CVE database.

[0005] Software supply chain security vulnerabilities differ from component vulnerabilities in the following ways:

[0006] 1. Different detection methods: Software security vulnerabilities are mainly detected by analyzing the software's code or execution path, while component vulnerabilities usually rely on third-party vulnerability databases or specific component security assessment tools.

[0007] 2. Different responsibilities for fixing: Software security vulnerabilities are usually the responsibility of software developers, while the responsibility for fixing component vulnerabilities may be shared by the component provider or integrator.

[0008] 3. Different risk propagation: Component vulnerabilities may spread to multiple software projects, especially popular open-source components, whose vulnerabilities may affect products in multiple software supply chains.

[0009] In practical applications, software supply chain security detection systems need to comprehensively consider both overall supply chain vulnerabilities and component vulnerabilities to fully assess software security risks. By simultaneously detecting and analyzing both system-wide and component vulnerabilities, potential risks within the software supply chain can be effectively identified and remedied, thereby improving the overall security and reliability of the software system.

[0010] A search revealed Chinese patent CN114077741B, which relates to a method and apparatus for detecting supply chain security in airborne software, as well as electronic devices and storage media. The method includes: acquiring a binary file to be detected; extracting features to be analyzed from the binary file, including intra-function features, inter-function features, and inter-module features; inputting the features to be analyzed into a feature vector generation model, outputting at least one feature vector corresponding to the binary file to be detected; obtaining the distance between each pair of the at least one feature vector to be analyzed and at least one reference feature vector corresponding to a reference file, to obtain the similarity between the binary file to be detected and the reference file; and detecting the reuse relationship between the binary file to be detected and the reference file based on the similarity. The technical solution disclosed in this patent cannot detect supply chain security risks such as reuse of third-party code, code defects, related vulnerabilities, or malicious code in binary programs.

[0011] Currently, most existing security risk detection systems for the software supply chain only detect software security vulnerabilities to determine whether there are security risks in the software, without measuring the risks of components, and therefore failing to discover high-risk components. Summary of the Invention

[0012] The purpose of this invention is to address the fact that most existing security risk detection systems for the software supply chain only detect software security vulnerabilities to determine whether there are security risks in the software, without measuring the risks of components, and thus failing to discover high-risk components.

[0013] In view of this, this application proposes an airborne software supply chain security risk detection system and method. While detecting software vulnerability risks, it also detects component risks, thereby comprehensively detecting and analyzing various risks existing in the software supply chain. By measuring the risk of components, it identifies high-risk components and aims to correct the risk of components. By measuring the risk of the component structure network, it evaluates the overall risk of the software, improves the comprehensiveness of risk detection, and increases the security of the software supply chain.

[0014] Technical solution

[0015] An airborne software supply chain security risk detection system includes:

[0016] Risk data acquisition module: Used to collect risk data in the software supply chain;

[0017] Vulnerability Risk Data Analysis Module: This module receives data from the vulnerability risk data collection unit in the risk data collection module, analyzes and calculates the vulnerability risk index, and transmits it to the overall risk analysis module.

[0018] Component Risk Data Analysis Module: This module receives data from the component risk data acquisition unit in the risk data acquisition module, analyzes and calculates the component risk index, and transmits it to the overall risk analysis module.

[0019] Overall Risk Analysis Module: This module receives data from the vulnerability risk data analysis module and the component risk data analysis module, analyzes and calculates the overall risk index of the software supply chain, and transmits it to the early warning module.

[0020] Early warning module: Used to receive data from the overall risk analysis module, determine the overall risk index and issue early warnings, and transmit the early warning results to the human-computer interaction module. The early warning results are either "warning required" or "warning not required".

[0021] Human-computer interaction module: Used for human-computer interaction display of data.

[0022] Furthermore, the risk data acquisition module includes a vulnerability risk data acquisition unit and a component risk data acquisition unit; risk data includes vulnerability risk data and component risk data; the vulnerability risk data acquisition unit collects vulnerability risk data from the software supply chain based on CVEs and transmits it to the vulnerability risk data analysis module; vulnerability risk data includes the number of vulnerabilities, vulnerability risk values, and vulnerability levels; CVEs are common vulnerabilities and exposures, a publicly known list of cybersecurity vulnerabilities and exposures, each item in the list being based on a specific vulnerability or exposure found in a specific software product, collecting known cybersecurity vulnerabilities and exposures; the component risk data acquisition unit is used to collect component risk data from the software supply chain and transmit it to the component risk data analysis module; component risk data includes, but is not limited to, component attributes, nodes, edges, and weights.

[0023] Furthermore, the component risk data analysis module includes a complexity analysis unit, a severity analysis unit, and a comprehensive analysis unit; the component risk index is a risk measurement index for the component.

[0024] The complexity analysis unit is used to analyze and calculate the complexity of the component and transmit the data to the comprehensive analysis unit; the severity analysis unit is used to analyze and calculate the severity of the component and transmit the data to the comprehensive analysis unit; the comprehensive analysis unit is used to receive the data from the complexity analysis unit and the severity analysis unit and perform comprehensive analysis and calculation of the component risk index.

[0025] Furthermore, the correspondence between vulnerability risk value and risk level in CVE is as follows: when the vulnerability risk value score is 0 to 4, excluding 4, the vulnerability level is low; when the vulnerability risk value score is 4 to 7, excluding 7, the vulnerability level is medium; and when the vulnerability risk value score is 7 to 10, the vulnerability level is high.

[0026] A method for analyzing and calculating vulnerability risk indices using a vulnerability risk data analysis module in an aviation airborne software supply chain security risk detection system.

[0027] The vulnerability risk data analysis module uses the following formula to calculate the vulnerability risk index: Where L is the vulnerability risk index, f(low) is the low-risk level risk value, f(mid) is the medium-risk level risk value, f(high) is the high-risk level risk value, k1 is the scaling factor of f(low), k2 is the scaling factor of f(mid), k3 is the scaling factor of f(high), and k1, k2 and k3 satisfy k1+k2+k3=1, and k1<k2<k3;

[0028] The formula for calculating the risk value of a low-risk level is: Where x1 is the number of low-risk vulnerabilities, m1 is the highest risk value among the low-risk vulnerabilities, and m1 satisfies 0≤m1<4;

[0029] The formula for calculating the risk value of medium-risk level is: Where x2 is the number of medium-risk vulnerabilities, m2 is the highest risk value among the medium-risk vulnerabilities, and m2 satisfies 4≤m2<7;

[0030] The formula for calculating the risk value of a high-risk level is: Where x3 is the number of high-risk vulnerabilities, m3 is the highest risk value among the high-risk vulnerabilities, and m3 satisfies 7≤m3≤10.

[0031] A method for analyzing and calculating the complexity of components in the complexity analysis unit of the component risk data analysis module in an airborne software supply chain security risk detection system. The specific process of the complexity analysis unit in the component risk data analysis module analyzing and calculating the complexity of components is as follows:

[0032] Step S01: Represent the complexity of the component as an n-ary function expression: C = f(u1, u2, u3…u ... n ), where C is the complexity of the component, and ui is the i-th attribute of the component, i = 1, 2, 3...n;

[0033] Step S02: Calculate the complexity of the j-th component based on Euclidean distance: Where Cj is the complexity of the j-th component, and if there are J components in total, then j = 1, 2, 3...J;

[0034] Simplifying formula ③, we get:

[0035] Step S03: Normalize formula ④ to obtain the new formula: Where Cj is the complexity of the j-th component, and if there are J components in total, then Cmax is the maximum complexity among the J components of the software, and Cmin is the minimum complexity among the J components of the software.

[0036] The complexity of a component describes the degree of complexity of the components and the reference relationships between them. A basic simple component is a component with no components and no reference relationships, and its complexity is 0. All indicators of a basic simple component are 0. This component is the origin of the indicator system. Therefore, the complexity of a component can be calculated by calculating the Euclidean distance from the basic simple component. The farther away from the basic simple component, that is, the larger the calculated Euclidean distance value, the higher the complexity of the component.

[0037] A method for analyzing and calculating the severity of components in the severity analysis unit of the component risk data analysis module in an airborne software supply chain security risk detection system. The formula for analyzing and calculating the severity of components in the severity analysis unit of the component risk data analysis module is as follows: Where Yj is the severity of the j-th component, and if there are J components, then j = 1, 2, 3...J; E(G) is the average network efficiency of the software topology network under normal conditions; assuming that component j fails, then the average network efficiency of the software topology network of the failed network is E(Gj) under the premise that component j fails.

[0038] If the network topology of the software contains three basic elements, namely nodes R, edges T and weights P, then the software topology network can be represented as G = (R, T, P). Therefore, for a network containing N nodes, G can be described by the connection matrix [Vab] N*N.

[0039] Therefore, G = [Vab]N*N; where Vab is the strength of the relationship between the a-th node and the b-th node, and the strength between nodes refers to the sum of the weights of the edges connecting the nodes;

[0040] N represents the total number of nodes in the software topology of the failed network when component j fails, and Vab′ represents the strength of the relationship between node a and node b in the software topology of the failed network.

[0041] A method for comprehensively analyzing and calculating the component risk index by the comprehensive analysis unit in an airborne software supply chain security risk detection system. The formula for the comprehensive analysis and calculation of the component risk index by the comprehensive analysis unit is as follows: Where Z′ is the component risk index; if there are J components, then j = 1, 2, 3...J; Z j =C j *Y j , where Zj is the risk index of component j, 0≤Cj≤1, 0≤Yj≤1.

[0042] A method for calculating the overall risk index by the overall risk analysis module in an airborne software supply chain security risk detection system. The formula for calculating the overall risk index by the overall risk analysis module is as follows: Wherein, δ is the overall risk index; the larger the value of the overall risk index δ, the higher the overall risk coefficient of the software supply chain and the lower the security.

[0043] A method for calculating the overall risk index by the overall risk analysis module in an aviation airborne software supply chain security risk detection system.

[0044] The specific process by which the early warning module determines and issues an early warning based on the overall risk index is as follows:

[0045] Step S11: If the overall risk index δ ≥ the judgment threshold IY, it is determined that an early warning is required. At this time, while transmitting data to the human-computer interaction module, an early warning instruction is sent to the management personnel.

[0046] Step S12: If the overall risk index δ < the judgment threshold IY, it is determined that no warning is needed. At this time, only data is transmitted to the human-computer interaction module, and no warning instruction is sent to the management personnel.

[0047] The threshold value IY is determined to be IY≤20%.

[0048] Beneficial effects

[0049] This invention proposes an airborne software supply chain security risk detection system and method, which facilitates the analysis and calculation of vulnerability risk indices and component risk indices. The final component risk index is obtained by comparing and analyzing the complexity and severity of components. This combined analysis of vulnerability and component risks lays the foundation for subsequent overall risk analysis of the software supply chain. Simultaneously, while detecting software vulnerability risks, it also detects component risks, thereby comprehensively detecting and analyzing various risks existing in the software supply chain. By measuring component risk, high-risk components are identified, achieving the goal of correcting component risks. Furthermore, by measuring the risk of the component structure network, the overall software risk is evaluated, improving the comprehensiveness of risk detection and increasing the security of the software supply chain. Detailed Implementation

[0050] The features and illustrative embodiments of various aspects of the present invention will now be described in detail. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention may be practiced without requiring some of these specific details. The following description of embodiments is merely intended to provide a better understanding of the invention by illustrating examples of the invention. The invention is by no means limited to any specific setup and method set forth below, but covers any improvements, substitutions, and modifications to the structures, methods, and devices without departing from the spirit of the invention. In the following description, well-known structures and techniques are not shown to avoid unnecessarily obscuring the invention.

[0051] It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other, and the various embodiments can be referenced and cited in turn. The present invention will now be described in detail with reference to the embodiments.

[0052] Example 1:

[0053] An aviation airborne software supply chain security risk detection system is provided, including a risk data acquisition module, a vulnerability risk data analysis module, a component risk data analysis module, an overall risk analysis module, an early warning module, and a human-computer interaction module;

[0054] The risk data acquisition module is used to collect risk data in the software supply chain. It includes a vulnerability risk data acquisition unit and a component risk data acquisition unit. Risk data includes vulnerability risk data and component risk data. The vulnerability risk data acquisition unit collects vulnerability risk data from the software supply chain based on CVEs and transmits it to the vulnerability risk data analysis module. Vulnerability risk data includes the number of vulnerabilities, vulnerability risk values, and vulnerability levels. CVE stands for Common Vulnerability and Exposures, a publicly known list of cybersecurity vulnerabilities and exposures. Each item in the list is based on a specific vulnerability or exposure found in a specific software product. The component risk data acquisition unit collects component risk data from the software supply chain and transmits it to the component risk data analysis module. Component risk data includes, but is not limited to, component attributes, nodes, edges, and weights.

[0055] The vulnerability risk data analysis module is used to receive data from the vulnerability risk data collection unit in the risk data collection module, analyze and calculate the vulnerability risk index, and transmit it to the overall risk analysis module.

[0056] The component risk data analysis module receives data from the component risk data acquisition unit in the risk data acquisition module, analyzes and calculates the component risk index, and transmits it to the overall risk analysis module. The component risk data analysis module includes a complexity analysis unit, a severity analysis unit, and a comprehensive analysis unit. The component risk index is a risk measurement index for the component.

[0057] The complexity analysis unit is used to analyze and calculate the complexity of components and transmit the results to the comprehensive analysis unit;

[0058] The severity analysis unit is used to analyze and calculate the severity of components and transmit the results to the comprehensive analysis unit;

[0059] The comprehensive analysis unit is used to receive data from the complexity analysis unit and the severity analysis unit, and to perform comprehensive analysis and calculation of the component risk index.

[0060] The overall risk analysis module receives data from the vulnerability risk data analysis module and the component risk data analysis module, analyzes and calculates the overall risk index of the software supply chain, and transmits it to the early warning module.

[0061] The early warning module receives data from the overall risk analysis module, determines and issues early warnings based on the overall risk index, and transmits the early warning results to the human-computer interaction module. The early warning result is either "warning required" or "warning not required."

[0062] The human-computer interaction module is used to display data in a human-computer interactive manner.

[0063] The correspondence between vulnerability risk value and risk level in CVE is as follows: when the vulnerability risk value score is 0 to 4 (excluding 4), the vulnerability level is low; when the vulnerability risk value score is 4 to 7 (excluding 7), the vulnerability level is medium; and when the vulnerability risk value score is 7 to 10, the vulnerability level is high.

[0064] The vulnerability risk data analysis module uses the following formula to calculate the vulnerability risk index: Where L is the vulnerability risk index, f(low) is the low-risk level risk value, f(mid) is the medium-risk level risk value, f(high) is the high-risk level risk value, k1 is the scaling factor of f(low), k2 is the scaling factor of f(mid), k3 is the scaling factor of f(high), and k1, k2 and k3 satisfy k1+k2+k3=1, and k1<k2<k3;

[0065] The formula for calculating the risk value of a low-risk level is: Where x1 is the number of low-risk vulnerabilities, m1 is the highest risk value among the low-risk vulnerabilities, and m1 satisfies 0≤m1<4;

[0066] The formula for calculating the risk value of medium-risk level is: Where x2 is the number of medium-risk vulnerabilities, m2 is the highest risk value among the medium-risk vulnerabilities, and m2 satisfies 4≤m2<7;

[0067] The formula for calculating the risk value of a high-risk level is: Where x3 is the number of high-risk vulnerabilities, m3 is the highest risk value among the high-risk vulnerabilities, and m3 satisfies 7≤m3≤10.

[0068] The formulas for calculating the risk values ​​of low-risk, medium-risk, and high-risk levels are all derived from the Sigmoid function. The Sigmoid function takes values ​​from 0.5 to 1 as x approaches infinity. However, this range of x values ​​does not reflect actual vulnerability risk. In practical vulnerability risk analysis, when x = 0, it indicates that the system has no vulnerability, and the risk value is 0. Therefore, it is necessary to shift the Sigmoid function curve to change the function value at x = 0 to 0. The formula is as follows: At this point, the function value S1(x) ranges from 0 to 0.5. To facilitate the calculation of the loophole, the formula value is multiplied by 2 and rounded down, so formula ① becomes: At this point, the range of the function value S2(x) is 0, which approaches 1 infinitely. According to the principle that the vulnerability risk value should not be lower than the risk value of the highest existing vulnerability and should not exceed the current range, the range of S2(x) needs to be expanded. Therefore, the value m is introduced, where m is the highest risk value among the vulnerabilities that exist in the current software.

[0069] The specific process by which the complexity analysis unit in the component risk data analysis module analyzes and calculates the complexity of a component is as follows:

[0070] Step S01: Represent the complexity of the component as an n-ary function expression: C = f(u1, u2, u3…u ... n ), where C is the complexity of the component, and ui is the i-th attribute of the component, i = 1, 2, 3...n;

[0071] Step S02: Calculate the complexity of the j-th component based on Euclidean distance: Where Cj is the complexity of the j-th component, and if there are J components in total, then j = 1, 2, 3...J;

[0072] Simplifying formula ③, we get:

[0073] Step S03: Normalize formula ④ to obtain the new formula: Where Cj is the complexity of the j-th component, and if there are J components in total, then Cmax is the maximum complexity among the J components of the software, and Cmin is the minimum complexity among the J components of the software.

[0074] The complexity of a component describes the degree of complexity of the components and the reference relationships between them. A basic simple component is a component with no components and no reference relationships, and its complexity is 0. All indicators of a basic simple component are 0. This component is the origin of the indicator system. Therefore, the complexity of a component can be calculated by calculating the Euclidean distance from the basic simple component. The farther away from the basic simple component, that is, the larger the calculated Euclidean distance value, the higher the complexity of the component.

[0075] For example, the components of a component can be its source code files and the functions contained therein. The complexity of a component can be measured by attributes such as the number and size of the source code files, the number of functions contained therein, and the number of lines of functions contained therein. The complexity of the reference relationships between components can be measured by the mutual calling relationships between the functions contained in the source code files and between the source code files.

[0076] The formula used by the severity analysis unit in the component risk data analysis module to calculate the severity of a component is as follows: Where Yj is the severity of the j-th component, and if there are J components, then j = 1, 2, 3...J; E(G) is the average network efficiency of the software topology network under normal conditions; assuming that component j fails, then the average network efficiency of the software topology network of the failed network is E(Gj) under the premise that component j fails.

[0077] If the network topology of the software contains three basic elements, namely nodes R, edges T and weights P, then the software topology network can be represented as G = (R, T, P). Therefore, for a network containing N nodes, G can be described by the connection matrix [Vab] N*N.

[0078] Therefore, G = [Vab]N*N; where Vab is the strength of the relationship between the a-th node and the b-th node, and the strength between nodes refers to the sum of the weights of the edges connecting the nodes;

[0079] N represents the total number of nodes in the software topology of the failed network when component j fails, and Vab′ represents the strength of the relationship between node a and node b in the software topology of the failed network.

[0080] The formula for the comprehensive analysis unit to calculate the component risk index is as follows: Where Z′ is the component risk index; if there are J components, then j = 1, 2, 3...J; Zj =C j *Y j , where Zj is the risk index of component j, 0≤Cj≤1, 0≤Yj≤1.

[0081] The formula for calculating the overall risk index in the overall risk analysis module is as follows: Wherein, δ is the overall risk index; the larger the value of the overall risk index δ, the higher the overall risk coefficient of the software supply chain and the lower the security.

[0082] The specific process by which the early warning module determines and issues an early warning based on the overall risk index is as follows:

[0083] Step S11: If the overall risk index δ ≥ the judgment threshold IY, it is determined that an early warning is required. At this time, while transmitting data to the human-computer interaction module, an early warning instruction is sent to the management personnel.

[0084] Step S12: If the overall risk index δ < the judgment threshold IY, it is determined that no warning is needed. At this time, only data is transmitted to the human-computer interaction module, and no warning instruction is sent to the management personnel.

[0085] The threshold value IY is determined to be IY≤20%.

[0086] This invention, by incorporating a vulnerability risk data analysis module and a component risk data analysis module, facilitates the analysis and calculation of vulnerability risk indices and component risk indices. It obtains the final component risk index by comparing and analyzing the complexity and severity of components. This combined analysis of vulnerability and component risks lays the foundation for subsequent overall risk analysis of the software supply chain. Simultaneously, it detects component risks while simultaneously detecting software vulnerability risks, thereby comprehensively detecting and analyzing various risks existing in the software supply chain. By measuring component risk, it identifies high-risk components and aims to correct their risks. Furthermore, by measuring the risk of the component structure network, it evaluates the overall risk of the software, improving the comprehensiveness of risk detection and increasing the security of the software supply chain.

[0087] Example 2:

[0088] The steps for using a software supply chain security risk detection system are as follows:

[0089] Step A1: Collect risk data in the software supply chain, including vulnerability risk data and component risk data;

[0090] Step A2: Calculate the risk values ​​for low-risk, medium-risk, and high-risk levels, and analyze and calculate the vulnerability risk index by combining the risk values ​​for low-risk, medium-risk, and high-risk levels.

[0091] Step A3: Represent the component complexity using an n-ary function, calculate the complexity based on Euclidean distance and normalize it, analyze and calculate the component severity using a formula, and then analyze and calculate the component risk index based on the complexity and severity using a formula.

[0092] The formula for analyzing and calculating the severity of a component is as follows: Where Yj is the severity of the j-th component, and if there are J components, then j = 1, 2, 3...J; E(G) is the average network efficiency of the software topology network under normal conditions; assuming that component j fails, then the average network efficiency of the software topology network of the failed network is E(Gj) under the premise that component j fails.

[0093] If the network topology of the software contains three basic elements, namely nodes R, edges T and weights P, then the software topology network can be represented as G = (R, T, P). Therefore, for a network containing N nodes, G can be described by the connection matrix [Vab] N*N.

[0094] Therefore, G = [Vab]N*N; where Vab is the strength of the relationship between the a-th node and the b-th node, and the strength between nodes refers to the sum of the weights of the edges connecting the nodes;

[0095] N is the total number of nodes in the software topology of the failed network when component j fails, and Vab′ is the strength of the relationship between the a-th node and the b-th node in the software topology of the failed network.

[0096] The formula for comprehensively analyzing and calculating the component risk index is as follows: Where Z′ is the component risk index; if there are J components, then j = 1, 2, 3...J; Z j =C j *Y j Where Zj is the risk index of component j, 0≤Cj≤1, 0≤Yj≤1;

[0097] Step A4: Analyze and calculate the overall risk index of the software supply chain using the formula;

[0098] Wherein, δ is the overall risk index; the larger the value of the overall risk index δ, the higher the overall risk coefficient of the software supply chain and the lower the security.

[0099] Step A5: Determine and issue an early warning for the overall risk index. If the overall risk index is greater than or equal to the determination threshold, it is determined that an early warning is required. If the overall risk index is less than the determination threshold, it is determined that no early warning is required.

[0100] In summary, the system and method of the present invention have the following characteristics:

[0101] 1. The vulnerability risk data analysis module calculates the vulnerability risk index from three perspectives: low risk, medium risk, and high risk. It conducts a comprehensive detection and analysis of software vulnerability risks, increases the comprehensiveness of vulnerability risk detection, improves the accuracy of vulnerability risk detection, and lays the foundation for subsequent risk analysis of the entire software supply chain.

[0102] 2. The component risk data analysis module calculates the complexity and severity of components. By comparing and analyzing the complexity and severity of components, it obtains the final component risk index. By measuring the risk of components, it identifies high risks in components and aims to correct the risk of components, laying the foundation for subsequent risk analysis of the entire software supply chain.

[0103] 3. By combining vulnerability risk and component risk analysis, the system detects both software vulnerability risks and component risks simultaneously, thereby comprehensively detecting and analyzing various risks in the software supply chain. This improves the comprehensiveness of risk detection and enhances the security of the software supply chain.

[0104] The differences between this invention and the prior art, and the significance of the invention.

[0105] 1. The difference between this invention and the prior art:

[0106] The difference between this invention and existing technologies lies in the fact that existing technologies for detecting security risks in the software supply chain mostly rely solely on detecting software security vulnerabilities to determine whether software poses a security risk, without measuring the risks of components. Consequently, they fail to identify high-risk components within the software supply chain, thus lacking comprehensiveness in the process of detecting security risks in the software supply chain. In contrast, this invention not only detects software vulnerability risks but also measures risk factors present in components. By comprehensively considering and analyzing the risk situation of the software supply chain from both software security vulnerabilities and component risks, it improves the comprehensiveness of the software supply chain risk analysis.

[0107] 2. Significance of this invention:

[0108] This invention considers component risk factors in the analysis of software supply chain risks, and further conducts a comprehensive analysis through the complexity and severity of components to obtain a risk index for component risk factors. By combining the risks of security vulnerabilities with component risks to conduct a comprehensive analysis of software supply chain risks, the invention improves the comprehensiveness of software supply chain risk analysis and makes the analysis results more accurate.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should be covered within the protection scope of the present invention.

Claims

1. A method for detecting security risks in the airborne software supply chain, characterized in that, This includes methods for analyzing and calculating vulnerability risk indices. These methods are implemented based on the analysis module of the aviation airborne software supply chain security risk detection system. The formula for calculating the vulnerability risk index using the vulnerability risk data analysis module is as follows: Where L is the vulnerability risk index, f(low) is the low-risk level risk value, f(mid) is the medium-risk level risk value, f(high) is the high-risk level risk value, k1 is the scaling factor of f(low), k2 is the scaling factor of f(mid), k3 is the scaling factor of f(high), and k1, k2 and k3 satisfy k1+k2+k3=1, and k1<k2<k3; The formula for calculating the risk value of a low-risk level is: Where x1 is the number of low-risk vulnerabilities, m1 is the highest risk value among the low-risk vulnerabilities, and m1 satisfies 0≤m1<4; The formula for calculating the risk value of medium-risk level is: Where x2 is the number of medium-risk vulnerabilities, m2 is the highest risk value among the medium-risk vulnerabilities, and m2 satisfies 4≤m2<7; The formula for calculating the risk value of a high-risk level is: Where x3 is the number of high-risk vulnerabilities, m3 is the highest risk value among the high-risk vulnerabilities, and m3 satisfies 7≤m3≤10.

2. The method for detecting security risks in the airborne software supply chain according to claim 1, characterized in that, It also includes methods for analyzing and calculating the complexity of components. These methods are implemented based on the component risk data analysis module in the airborne software supply chain security risk detection system. The specific process by which the complexity analysis unit in the component risk data analysis module analyzes and calculates the complexity of components is as follows: Step S01: Represent the complexity of the component as an n-ary function expression: Where C is the complexity of the component, and ui is the i-th attribute of the component, i = 1, 2, 3...n; Step S02: Calculate the complexity of the j-th component based on Euclidean distance: Where Cj is the complexity of the j-th component, and if there are J components in total, then j = 1, 2, 3...J; Simplifying formula ③, we get: ; Step S03: Normalize formula ④ to obtain the new formula: Where Cj is the complexity of the j-th component, and if there are J components in total, then Cmax is the maximum complexity among the J components of the software, and Cmin is the minimum complexity among the J components of the software. The complexity of a component describes the degree of complexity of the components and the reference relationships between them. A basic simple component is a component with no components and no reference relationships, and its complexity is 0. All indicators of a basic simple component are 0. This component is the origin of the indicator system. Therefore, the complexity of a component can be calculated by calculating the Euclidean distance from the basic simple component. The farther away from the basic simple component, that is, the larger the calculated Euclidean distance value, the higher the complexity of the component.

3. The method for detecting security risks in the airborne software supply chain according to claim 2, characterized in that, It also includes a method for analyzing and calculating the severity of components. This method is implemented based on the component risk data analysis module in the airborne software supply chain security risk detection system. The formula used by the severity analysis unit in the component risk data analysis module to analyze and calculate the severity of components is as follows: Where Yj is the severity of the j-th component, and if there are J components, then j = 1, 2, 3...J; E(G) is the average network efficiency of the software topology network under normal conditions; assuming that component j fails, then the average network efficiency of the software topology network of the failed network is E(Gj) under the premise that component j fails. If the network topology of the software contains three basic elements, namely nodes R, edges T and weights P, then the software topology network can be represented as G=(R,T,P). Therefore, for a network containing N nodes, G can be described by the connection matrix [Vab]N*N. Therefore, G = [Vab]N*N; where Vab is the strength of the relationship between the a-th node and the b-th node, and the strength between nodes refers to the sum of the weights of the edges connecting the nodes. N is the total number of nodes in the software topology of the failed network when component j fails, and Vab´ is the strength of the relationship between node a and node b in the software topology of the failed network.

4. The method for detecting security risks in the airborne software supply chain according to claim 3, characterized in that, It also includes a method for comprehensively analyzing and calculating the component risk index. This method is implemented based on the comprehensive analysis unit in the airborne software supply chain security risk detection system. The formula for the comprehensive analysis unit to calculate the component risk index is as follows: Where Z´ is the component risk index, and if there are J components, then j = 1, 2, 3...J; , where Zj is the risk index of component j, 0≤Cj≤1, 0≤Yj≤1.

5. The method for detecting security risks in the airborne software supply chain according to claim 4, characterized in that, It also includes a method for calculating the overall risk index. This method is implemented based on the overall risk analysis module of the airborne software supply chain security risk detection system. The formula for calculating the overall risk index by the overall risk analysis module is as follows: Where δ is the overall risk index; the larger the value of the overall risk index δ, the higher the overall risk coefficient of the software supply chain and the lower the security.

6. The method for detecting security risks in the airborne software supply chain according to claim 5, characterized in that, It also includes a method for calculating the overall risk index, which is implemented based on the overall risk analysis module in the airborne software supply chain security risk detection system. The specific process by which the early warning module determines and issues an early warning based on the overall risk index is as follows: Step S11: If the overall risk index δ ≥ the judgment threshold IY, it is determined that an early warning is required. At this time, while transmitting data to the human-computer interaction module, an early warning instruction is sent to the management personnel. Step S12: If the overall risk index δ < the judgment threshold IY, it is determined that no warning is needed. At this time, only data is transmitted to the human-computer interaction module, and no warning instruction is sent to the management personnel. The threshold value IY is determined to be IY≤20%.

7. An airborne software supply chain security risk detection system for implementing the detection method of claim 6, characterized in that, include: Risk data acquisition module: Used to collect risk data in the software supply chain; Vulnerability Risk Data Analysis Module: This module receives data from the vulnerability risk data collection unit in the risk data collection module, analyzes and calculates the vulnerability risk index, and transmits it to the overall risk analysis module. Component Risk Data Analysis Module: This module receives data from the component risk data acquisition unit in the risk data acquisition module, analyzes and calculates the component risk index, and transmits it to the overall risk analysis module. Overall Risk Analysis Module: This module receives data from the vulnerability risk data analysis module and the component risk data analysis module, analyzes and calculates the overall risk index of the software supply chain, and transmits it to the early warning module. Early warning module: Used to receive data from the overall risk analysis module, determine the overall risk index and issue early warnings, and transmit the early warning results to the human-computer interaction module. The early warning results are either "warning required" or "warning not required". Human-computer interaction module: Used for human-computer interaction display of data.

8. The airborne software supply chain security risk detection system according to claim 7, characterized in that, The risk data acquisition module includes a vulnerability risk data acquisition unit and a component risk data acquisition unit. Risk data includes vulnerability risk data and component risk data. The vulnerability risk data acquisition unit collects vulnerability risk data from the software supply chain based on CVEs and transmits it to the vulnerability risk data analysis module. Vulnerability risk data includes the number of vulnerabilities, vulnerability risk values, and vulnerability levels. CVEs are publicly known cybersecurity vulnerabilities and exposures, a list of publicly known cybersecurity vulnerabilities and exposures. Each item in the list is based on a specific vulnerability or exposure found in a specific software product. The component risk data acquisition unit collects component risk data from the software supply chain and transmits it to the component risk data analysis module. Component risk data includes, but is not limited to, component attributes, nodes, edges, and weights.

9. The airborne software supply chain security risk detection system according to claim 7, characterized in that, The component risk data analysis module includes a complexity analysis unit, a severity analysis unit, and a comprehensive analysis unit; the component risk index is a risk measurement index for the component. The complexity analysis unit is used to analyze and calculate the complexity of the component and transmit the data to the comprehensive analysis unit; the severity analysis unit is used to analyze and calculate the severity of the component and transmit the data to the comprehensive analysis unit; the comprehensive analysis unit is used to receive the data from the complexity analysis unit and the severity analysis unit and perform comprehensive analysis and calculation of the component risk index.

10. The airborne software supply chain security risk detection system according to claim 7, characterized in that, The correspondence between vulnerability risk value and risk level in CVE is as follows: when the vulnerability risk value score is 0~4, excluding 4, the vulnerability level is low; when the vulnerability risk value score is 4~7, excluding 7, the vulnerability level is medium; when the vulnerability risk value score is 7~10, the vulnerability level is high.

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