Automatic rating method and system for automobile information safety risk influence
Through matrix calculation and operation combined with fine-tuning of automotive parts databases, fine-grained and multi-dimensional evaluation of the impact of automotive information security risks is achieved, and the problem of insufficient time consumption and accuracy caused by the reliance on expert experience of evaluation methods in the existing technology is solved. Improved the efficiency and accuracy of the evaluation.
Patent Information
- Application Number
- CN202410903684.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-08
- Publication Date
- 2024-12-20
AI Technical Summary
The existing automotive information security risk assessment methods rely on expert experience, take time and the evaluation results are affected by subjective factors, making it difficult to achieve fine-grained multi-dimensional risk impact ratings, resulting in insufficient evaluation accuracy.
The automatic evaluation process of risk impact level in the matrix form is adopted, combining functional characteristics, data flow chart element characteristics and information security attributes, and realize coupled analysis of risk impact level through matrix calculation and operation, including determining the functional impact type and building a weighted damage relationship matrix , perform matrix multiplication and fine-tuning based on automotive parts database to form the final risk impact rating evaluation.
It realizes fast, efficient, fine-grained, and multi-dimensional risk impact ratings, improves the accuracy of automotive information security risk assessment, reduces labor costs, and avoids inconsistency in evaluation standards.
Smart Images
Figure CN119168355A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of vehicle information security, and in particular relates to an automatic rating method and system for automobile information security risk impact. Background Art
[0002] The rapid development of technologies such as the Internet of Vehicles, artificial intelligence, and cloud computing has continuously improved the intelligence and networking of automobiles. The market size of intelligent networked vehicles has gradually expanded. Intelligent networked vehicles are equipped with many intelligent sensors, controllers, and other components that can communicate online to achieve the coordination of people, vehicles, roads, and clouds. However, the combination of the Internet of Vehicles and smart cars has brought new security risks to vehicle safety. Compared with traditional vehicle components, smart vehicle modules are more vulnerable to attacks at the information security level, such as information tampering, denial of service attacks, and privacy theft. Therefore, the assessment and protection of vehicle information security has become a crucial link in the life cycle of smart cars, and relevant regulations have also been increasingly improved. The R155 regulation issued by the United Nations World Forum for Harmonization of Vehicle Regulations (WP.29) requires automakers to obtain CSMS (Cybersecurity Management System) certification and review whether vehicle manufacturers have established cybersecurity management processes at all stages of the vehicle's complete life cycle. The ISO / SAE21434 standard provides a Threat Analysis and Risk Assessment (TARA) methodology, which has become an important basis for many automakers to implement vehicle cybersecurity management.
[0003] TARA analysis first needs to identify the safety assets to be evaluated. The common method is to use the functional data flow diagram as input and obtain the assets from the perspective of the data flow diagram elements; impact level assessment is an important part of TARA analysis, which is to estimate the severity of the impact of a certain damage scenario corresponding to the asset on the safety of the vehicle and users. In the current TARA analysis process, the impact level of the damage scenario is mainly evaluated by expert experience and database historical information. This method requires manual evaluation of risks one by one, which consumes a lot of time and cost, and the evaluation is highly affected by the subjective factors of experts, which may lead to the problem of insufficient accuracy of the rating results. Therefore, it is necessary to design an automated impact rating method and system to promote the unification of evaluation standards and improve the efficiency of impact rating. On the other hand, the current method considers relatively single factors, lacks a comprehensive analysis of the impact of multiple factors on risks, and it is difficult to achieve fine-grained impact rating. Therefore, it is necessary to design an impact rating method that considers comprehensive analysis of multiple factors to achieve more accurate evaluation and enhance the accuracy of subsequent automotive TARA analysis. Summary of the invention
[0004] In order to solve the problems in the prior art, the present invention provides an automatic rating method and system for automobile information security risk impacts. According to the risk level automatic evaluation process, the impact of various risk-related factors on the safety of the entire vehicle is comprehensively analyzed to achieve high-efficiency, fine-grained, and multi-dimensional risk impact rating, thereby improving the accuracy of automobile information security risk assessment.
[0005] In order to achieve the above object, on the one hand, the present invention provides an automatic rating method for automobile information security risk impact, the method comprising:
[0006] For the risk items to be evaluated, the risk impact level is expressed in matrix form according to the risk level automatic evaluation process. Through the calculation and operation of the matrix, the impact of various factors such as the functional characteristics corresponding to the risk, the characteristics of the data flow diagram elements and the information security attributes on the safety of the whole vehicle is coupled and analyzed to form the final risk impact level evaluation result. The risk level automatic evaluation process specifically includes:
[0007] Determine the impact type of the function. For each element to be evaluated in the function, select the corresponding damage relationship matrix according to the functional impact type;
[0008] Considering the impact of the importance of data flow graph elements on vehicle safety, the weighted damage relationship matrix at the element level is calculated according to the importance weight value of the element in the functional data flow graph;
[0009] Constructing the impact rating reference value into a matrix, and performing matrix multiplication-based impact rating adjustment with the weighted damage relationship matrix;
[0010] Based on the automobile parts database, the special properties of the element to be evaluated are queried, the impact rating of the element is fine-tuned, and the final impact rating score of each impact dimension of the element is obtained.
[0011] Furthermore, based on expert experience and relevant historical data of functions, the impact type of the function to be evaluated and the impact rating benchmark value are determined, where:
[0012] The function impact types include dangerous functions, protective functions, and full-impact functions. The dangerous functions are functions that may cause negative safety impacts if unexpectedly or improperly executed, but will not cause negative safety impacts if not executed; the protective functions are functions that are executed for the purpose of protecting the safety of the entire vehicle, but will not cause negative safety impacts if not executed; the full-impact functions are functions that may cause negative safety impacts except for correct execution.
[0013] Furthermore, for each element to be evaluated in the function, a corresponding damage relationship matrix is selected according to the function impact type, where:
[0014] The damage relationship matrix is an m×n matrix, where m is the number of impact rating dimensions, n is the number of information security attributes, and the matrix element a ij Indicates the correlation between the i-th impact rating dimension and the j-th information security attribute; the impact rating dimensions include security, property, operation, and privacy, and other dimensions are added according to actual security analysis requirements; the information security attributes include confidentiality, availability, integrity, authenticity, non-repudiation, and authority attributes, and other security attributes are added according to actual security analysis requirements; a ij ∈[0,1] represents the degree of impact that the damage to the j-th information security attribute will have on the i-th impact rating dimension;
[0015] For the kth element to be evaluated, construct the damage relationship matrix corresponding to the element according to the functional impact type and the element type. The element types include processes, data flows, data stores, and interacting entities.
[0016] Furthermore, the consideration of the impact of the importance of the data flow graph elements on the safety of the entire vehicle, for the elements to be evaluated, weighting the corresponding damage relationship matrix, specifically includes:
[0017] w k is the importance weight value of the kth element in the functional data flow graph, indicating the importance of the element for the correct and safe execution of the function, w k ∈[0,1], weight the damage relationship matrix and calculate the weighted damage relationship matrix of the kth element Right now
[0018] Furthermore, the impact rating calculation based on matrix multiplication calculates the impact rating matrix based on the weighted damage relationship matrix and the functional impact rating benchmark value, wherein:
[0019] The function impact rating benchmark value is constructed as a diagonal matrix B of size m×m, where m is the number of impact rating dimensions and its main diagonal element is the impact rating benchmark value of each dimension. The impact rating matrix of the kth element is calculated. And round the matrix elements.
[0020] Furthermore, based on the automobile parts database, the special properties of the element to be evaluated are queried to fine-tune the impact rating of the element, wherein:
[0021] For the kth element, query the vehicle asset database to determine its special properties, query the fine-tuning position ij and fine-tuning score b of the special properties on the rating matrix, and Fine-tune the element value of Get the final impact rating result matrix of the kth element
[0022] In another aspect, the present invention provides an automatic rating system for automobile information security risk impact, the system comprising:
[0023] Functional impact pre-determination module, used to obtain the functional data flow diagram drawn by experts and make a preliminary judgment on the functional impact, including the functional impact type, functional impact rating benchmark value and data flow diagram element importance weight value mark;
[0024] The damage relationship matrix automatic processing module is used to construct a damage relationship matrix for each element to be evaluated, and perform weighted calculation to obtain a weighted damage relationship matrix for each element;
[0025] The impact rating automatic evaluation module is used to construct and calculate the impact rating matrix for each element, and use the weighted damage relationship matrix and the impact rating benchmark value to perform the impact rating calculation based on matrix multiplication; based on the vehicle asset database, the impact rating matrix is fine-tuned according to the special attributes of the elements to obtain the final calculation result of the impact rating of each element.
[0026] Furthermore, in the function impact pre-determination module, based on expert experience and relevant function historical data, the function impact type is judged, including dangerous functions, protective functions and full-impact functions; and a reference value for the impact rating of the function level is given; a data flow diagram is drawn, and the importance of the elements to the safety of the entire vehicle is judged and a weight value is assigned; the function impact pre-determination information is used as input to the damage relationship matrix automatic processing module and the impact level automatic evaluation module, and also as input for subsequent threat analysis and risk assessment.
[0027] Furthermore, the damage relationship matrix automatic processing module selects the corresponding damage relationship matrix according to the functional impact type and the type of element to be evaluated, and performs weighted calculation on the damage relationship matrix according to the importance weight value of the element in the data flow diagram to obtain the weighted damage relationship matrix of the element as the input of the impact level automatic evaluation module.
[0028] Furthermore, the impact level automatic evaluation module constructs an impact rating benchmark value matrix based on the functional impact rating benchmark value, performs multiplication calculation with the weighted damage relationship matrix, and obtains an impact rating matrix; queries the vehicle asset database to obtain the special properties of the elements, fine-tunes the impact rating matrix, and outputs the final impact rating result as input for subsequent threat analysis and risk assessment.
[0029] Compared with the prior art, the present invention has the following beneficial effects:
[0030] For the automobile information security risks to be evaluated, the present invention takes into account the impact of multiple factors such as functional characteristics, security attribute characteristics, and functional data flow diagram element characteristics on the safety of the entire vehicle. Through the establishment, processing and calculation of the matrix, the impact level of the risk corresponding to the damage scenario is automatically evaluated, and a fast, efficient, fine-grained, and multi-dimensional impact level evaluation is achieved, which alleviates the problem that the traditional evaluation method relies too much on expert experience and considers a single factor, resulting in inaccurate evaluation results, and provides stronger support for subsequent risk analysis; an automatic impact rating system is designed to automatically generate risk impact rating results according to the automobile function input information, which solves the problems of high labor costs and inconsistent evaluation standards in traditional evaluation methods, avoids unnecessary duplication of labor, saves evaluation time, and improves the efficiency of automobile information security risk analysis. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 Schematic diagram of the automatic rating method for automobile information security risk impact in an embodiment of the present application.
[0032] Figure 2 This is a flowchart of automobile information security analysis in an embodiment of the present application.
[0033] Figure 3 Schematic diagram of the automatic rating system for automobile information security risk impact in an embodiment of the present application. DETAILED DESCRIPTION
[0034] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments.
[0035] Embodiment 1:
[0036] This embodiment provides an automatic rating method for automobile information security risk impact, the method is described in Figure 1 ,include:
[0037] For the risk items to be evaluated, the risk impact level is expressed in matrix form according to the risk level automatic evaluation process. Through the calculation and operation of the matrix, the impact of various factors such as the functional characteristics corresponding to the risk, the characteristics of the data flow diagram elements and the information security attributes on the safety of the whole vehicle is coupled and analyzed to form the final risk impact level evaluation result. The risk level automatic evaluation process specifically includes:
[0038] Combined consideration of the impact of functional characteristics and information security attributes on vehicle safety. For each element to be evaluated, select the corresponding damage relationship matrix according to the functional impact type.
[0039] Determine the impact type of the function. For each element to be evaluated in the function, select the corresponding damage relationship matrix according to the functional impact type;
[0040] Considering the impact of the importance of data flow graph elements on vehicle safety, the weighted damage relationship matrix at the element level is calculated according to the importance weight value of the element in the functional data flow graph;
[0041] Constructing the impact rating reference value into a matrix, and performing matrix multiplication-based impact rating adjustment with the weighted damage relationship matrix;
[0042] Based on the automobile parts database, the special properties of the element to be evaluated are queried, the impact rating of the element is fine-tuned, and the final impact rating score of each impact dimension of the element is obtained.
[0043] In this embodiment, the risk items to be evaluated are divided into security attribute levels of elements based on the asset identification results. For each element in a certain asset, an impact rating is performed on the damage scenario corresponding to each of its information security attributes, wherein the elements are elements in the data flow diagram, including processing procedures, data flows, interactive entities, and data storage, and the damage scenarios are some damage scenarios that may occur when the network security attributes of the asset are destroyed;
[0044] The automatic rating method for the impact of automotive information security risks assesses the impact of each damage scenario of the risk to be assessed. According to the ISO / SAE 21434 standard, the impact is mainly assessed in four dimensions, including security, finance, operation, and privacy. Secondly, other impact dimensions can be considered.
[0045] In this embodiment, the automobile information security analysis process is shown in Figure 2 , mainly describes the automatic rating method process of the automobile information security risk impact, specifically including:
[0046] S101, the expert inputs the information required for information security analysis at the function level. The method is implemented on the basis of risk-related input information, and the input information includes the function impact type and function level impact rating benchmark value determined by the expert, and the drawn function data flow diagram with weight mark; wherein the expert determines the function impact type to be evaluated and the impact rating benchmark value based on professional experience and relevant function historical data, and the function impact type specifically includes dangerous function, protective function, and full impact function:
[0047] The dangerous function refers to the function that will cause negative safety impact if it is not executed unexpectedly or improperly, and will not cause negative safety impact if it is not executed, such as the Bluetooth key unlocking function; the protective function refers to the function that is executed for the purpose of protecting the safety of the whole vehicle, and will not cause negative safety impact if it is not executed, such as the Bluetooth key locking function; the full-impact function refers to the function that may cause negative safety impact except for the correct execution, such as the gear management function;
[0048] The negative safety impact is a threat to the life and property safety of the vehicle or driver, and does not include a threat to functional operation.
[0049] S102, for a certain function of the vehicle, based on the input information of step S101, the system automatically performs asset identification and damage scene identification as input for impact level assessment;
[0050] The following is an example of a damage scenario: "The asset vehicle unlocking request is blocked or attacked by DDos, and the availability is damaged, causing the vehicle unlocking request function to fail or degrade, which has a significant impact on the use of the vehicle's functions."
[0051] S103, for each element to be evaluated in the function, select the corresponding damage relationship matrix according to the function impact type, where:
[0052] The damage relationship matrix is an m×n matrix, where m is the number of impact rating dimensions, n is the number of information security attributes, and the matrix element a ij Indicates the correlation between the i-th impact rating dimension and the j-th information security attribute; the impact rating dimensions include security, property, operation, and privacy, and other dimensions are added according to actual security analysis requirements; the information security attributes include confidentiality, availability, integrity, authenticity, non-repudiation, and authority attributes, and other security attributes are added according to actual security analysis requirements; a ij ∈[0,1] represents the degree of impact that the damage to the j-th information security attribute will have on the i-th impact rating dimension;
[0053] To facilitate understanding of the impairment relationship matrix in this embodiment, the impairment relationship matrix corresponding to the case of m=4 and n=6 is described by the following example:
[0054] An exemplary 4×6 damage relationship matrix of dangerous functions is shown in Table 1:
[0055] Table 1:
[0056] Confidentiality Availability Completeness Authenticity Non-repudiation Permission attributes Safety 0 0 0 1 0 1 finance 0 0 0 1 0 1 operate 0 1 0.6 0 0.6 1 privacy 1 0 0 0 0 0
[0057] The 4×6 damage relationship matrix of the protection function is shown in Table 2:
[0058] Table 2:
[0059] Confidentiality Availability Completeness Authenticity Non-repudiation Permission attributes Safety 0 1 1 0 0 1 finance 0 1 1 0 0 1 operate 0 1 0.6 0 0.6 1 privacy 1 0 0 0 0 0
[0060] The 4×6 damage relationship matrix of all impact functions is shown in Table 3:
[0061] Table 3:
[0062] Confidentiality Availability Completeness Authenticity Non-repudiation Permission attributes Safety 0 1 1 1 0 1 finance 0 1 1 1 0 1 operate 0 1 0.6 0 0.6 1 privacy 1 0 0 0 0 0
[0063] For the kth element in a certain asset to be evaluated, construct the damage relationship matrix corresponding to the element according to the functional impact type and the element type. The element types include processing, data flow, data storage and interactive entities. Each type of element faces threats with different security attributes. According to the STRIDE model, the corresponding relationship is shown in Table 4:
[0064] Table 4:
[0065] Element Type Compromised security attributes Process Confidentiality, availability, integrity, authenticity, non-repudiation, and authority attributes Data Flow Confidentiality, availability, integrity, authenticity Interactive Entities Authenticity and non-repudiation Data storage Confidentiality, availability, integrity
[0066] It is an m×l matrix. After selecting an m×n matrix according to the functional impact type, a submatrix is constructed according to the threats faced by each element in Table 4. The l-column matrix elements of the m×n matrix are selected to construct an m×l (l≤n) matrix.
[0067] S104, considering the impact of the importance of the data flow graph elements on the safety of the whole vehicle, for the elements to be evaluated, weighting the corresponding damage relationship matrix, specifically including:
[0068] w k is the importance weight value of the kth element in the functional data flow graph, indicating the importance of the element for the correct and safe execution of the function, w k ∈[0,1], weight the damage relationship matrix and calculate the weighted damage relationship matrix of the kth element Right now Correct and safe execution of the function means that the core part of the function can be executed normally and does not cause harm to the vehicle and personal safety. For example, in the Bluetooth key unlocking function, if the element is damaged and the vehicle cannot be unlocked, then its importance weight value is higher. If the element damage does not affect the unlocking of the vehicle, but only causes the unlocking sound reminder to fail after unlocking, then its importance weight value is lower.
[0069] S105, construct and calculate the impact rating matrix, based on the weighted damage relationship matrix calculated in step S104 The impact rating matrix is calculated based on the functional impact rating baseline value, where:
[0070] The function impact rating benchmark values evaluated by the experts in step S105 are constructed into a diagonal matrix B of size m×m, where m is the number of impact rating dimensions, and the values of the main diagonal elements are the impact rating benchmark values of each dimension, and the values of the non-main diagonal elements are 0. In this embodiment, the benchmark value b ii ∈{1,2,3,4}, according to the severity of the impact, take m=4 as an example, the impact rating benchmark values of the function in the four dimensions of security, property, operation, and privacy are 2, 2, 3, and 1 respectively, then the corresponding function impact rating benchmark value matrix is:
[0071]
[0072] Calculate the impact rating matrix for the kth element And the matrix The elements of are rounded up one by one, is an m×l matrix, and the matrix element c ij It indicates that when the security attribute j of the element to be evaluated is damaged, the rating value of dimension i is affected.
[0073] S106, fine-tune the impact rating matrix according to the impact of the special properties of the elements on the safety of the whole vehicle. For the kth element in a certain asset to be evaluated, query the vehicle asset database, determine the special properties of the element, query the fine-tuning position ij and fine-tuning score b of the special properties on the impact rating matrix, and adjust the impact rating matrix calculated in step S105. Fine-tune the element value of Get the final impact rating result matrix of the kth element in:
[0074] The vehicle asset database includes the asset attribute information of the currently evaluated vehicle model and the historical vehicle model. In this embodiment, the vehicle asset database is queried to obtain the attribute information of the element according to the element type and element name, and the matrix element subscript and fine-tuning score that need to be fine-tuned are queried according to the special property name;
[0075] In order to facilitate understanding of the fine-tuning of the impact rating in this embodiment, the special properties and fine-tuning rules of the process-type elements are explained through the following examples;
[0076] Exemplarily, the special properties of the process-type elements include: whether to store vehicle or user data, whether to communicate directly with the cloud platform, whether to communicate directly with the user's wireless device;
[0077] If the process to be evaluated stores vehicle or user data, the fine-tuning position i = getIndex("Privacy"), j = getIndex("Confidentiality") corresponds to a fine-tuning score b = 2;
[0078] If the process to be evaluated communicates directly with the cloud platform, the fine-tuning position i = getIndex ("property"), j = getIndex ("authenticity") corresponds to a fine-tuning score b = 3; the fine-tuning position i = getIndex ("privacy"), j = getIndex ("confidentiality") corresponds to a fine-tuning score b = 3;
[0079] If the process to be evaluated directly communicates with the user's wireless device, the fine-tuning position i = getIndex ("property"), j = getIndex ("authenticity") corresponds to a fine-tuning score b = 2; the fine-tuning position i = getIndex ("privacy"), j = getIndex ("confidentiality") corresponds to a fine-tuning score b = 2;
[0080] The getIndex is a function for obtaining the matrix index;
[0081] like is greater than the maximum impact rating, it is set to the maximum value. is less than the minimum impact rating, it is set to the minimum value.
[0082] S107, executing the remaining threat analysis and risk assessment process.
[0083] Embodiment 2:
[0084] This embodiment provides an automatic rating system for automobile information security risk impact, including:
[0085] Functional impact pre-determination module, used to obtain the functional data flow diagram drawn by experts and make a preliminary judgment on the functional impact, including the functional impact type, functional impact rating benchmark value and data flow diagram element importance weight value mark;
[0086] The damage relationship matrix automatic processing module is used to construct a damage relationship matrix for each element to be evaluated, and perform weighted calculation to obtain a weighted damage relationship matrix for each element;
[0087] The impact rating automatic evaluation module is used to construct and calculate the impact rating matrix for each element, and use the weighted damage relationship matrix and the impact rating benchmark value to perform the impact rating calculation based on matrix multiplication; based on the vehicle asset database, the impact rating matrix is fine-tuned according to the special attributes of the elements to obtain the final calculation result of the impact rating of each element.
[0088] In this embodiment, the system schematic diagram is shown in Figure 3 ,in:
[0089] In the function impact pre-determination module, experts judge the function impact type based on professional experience and relevant function historical data, including dangerous functions, protective functions and full-impact functions;
[0090] For the functions to be evaluated, experts give a benchmark value for the impact rating at the function level from the dimensions of security, property, operation, and privacy, or add other impact dimensions based on actual needs;
[0091] Draw a data flow diagram, determine the importance of elements to vehicle safety, and assign weight values;
[0092] The functional impact type, impact rating benchmark value, and data flow diagram with weight marking serve as inputs to the damage relationship matrix automatic processing module and the impact level automatic evaluation module, and also as inputs to subsequent threat analysis and risk assessment.
[0093] In the damage relationship matrix automatic processing module, for the data flow graph element to be evaluated, the corresponding damage relationship matrix is automatically selected from the predefined damage relationship matrix library according to the function impact type and the element type. The damage relationship matrix is an m×l matrix, where m is the number of dimensions affecting the rating, and l is the number of security attributes facing threats to the current element type;
[0094] According to the importance weight values of the elements in the data flow diagram, the damage relationship matrix is weighted and calculated, and the weighted result is rounded up to obtain the element-level weighted damage relationship matrix as the input of the impact level automatic evaluation module.
[0095] In the impact level automatic evaluation module, an m×m impact rating reference value matrix is constructed according to the functional impact rating reference value, and multiplied with the weighted damage relationship matrix calculated by the damage relationship matrix automatic processing module to obtain an m×l impact rating matrix;
[0096] According to the element type and element name, the vehicle asset database is queried to obtain the special attributes of the elements, and the impact rating fine-tuning position and fine-tuning value corresponding to the special attributes are queried, the impact rating matrix is fine-tuned, and the final impact rating result is output as the input for subsequent threat analysis and risk assessment.
Claims
1. An automatic rating method for automobile information security risk impact, characterized in that: For the risk items to be evaluated, the risk impact level is expressed in matrix form according to the risk level automatic evaluation process. Through the calculation and operation of the matrix, the impact of various factors such as the functional characteristics corresponding to the risk, the characteristics of the data flow diagram elements and the information security attributes on the safety of the whole vehicle is coupled and analyzed to form the final risk impact level evaluation result. The risk level automatic evaluation process specifically includes: Determine the impact type of the function. For each element to be evaluated in the function, select the corresponding damage relationship matrix according to the functional impact type; Considering the impact of the importance of data flow graph elements on vehicle safety, the weighted damage relationship matrix at the element level is calculated according to the importance weight value of the element in the functional data flow graph; Constructing the impact rating reference value into a matrix, and performing matrix multiplication-based impact rating adjustment with the weighted damage relationship matrix; Based on the automobile parts database, the special properties of the element to be evaluated are queried, the impact rating of the element is fine-tuned, and the final impact rating score of each impact dimension of the element is obtained.
2. The automatic rating method for automobile information security risk impact according to claim 1 is characterized in that: Determine the impact type of the function to be evaluated and the impact rating benchmark value based on expert experience and relevant historical data of the function, including: The function impact types include dangerous functions, protective functions, and full-impact functions. The dangerous functions are functions that may cause negative safety impacts if unexpectedly or improperly executed, but will not cause negative safety impacts if not executed; the protective functions are functions that are executed for the purpose of protecting the safety of the entire vehicle, but will not cause negative safety impacts if not executed; the full-impact functions are functions that may cause negative safety impacts except for correct execution.
3. The automatic rating method for automobile information security risk impact according to claim 1 is characterized in that: For each element to be evaluated in the function, the corresponding damage relationship matrix is selected according to the function impact type, where: The damage relationship matrix is an m×n matrix, where m is the number of impact rating dimensions, n is the number of information security attributes, and the matrix element a ij Indicates the correlation between the i-th impact rating dimension and the j-th information security attribute; the impact rating dimensions include security, property, operation, and privacy, and other dimensions are added according to actual security analysis requirements; the information security attributes include confidentiality, availability, integrity, authenticity, non-repudiation, and authority attributes, and other security attributes are added according to actual security analysis requirements; a ij ∈[0,1] represents the degree of impact that the damage to the j-th information security attribute will have on the i-th impact rating dimension; For the kth element in a certain asset to be evaluated, construct the damage relationship matrix corresponding to the element according to the functional impact type and the element type. The element types include processes, data flows, data stores, and interacting entities.
4. The automatic rating method for automobile information security risk impact according to claim 1 is characterized in that: The consideration of the impact of the importance of the data flow graph elements on the safety of the vehicle and weighting the corresponding damage relationship matrix of the elements to be evaluated specifically include: w k is the importance weight value of the kth element in the functional data flow graph, indicating the importance of the element for the correct and safe execution of the function, w k ∈[0,1], weight the damage relationship matrix and calculate the weighted damage relationship matrix of the kth element Right now 5. The automatic rating method for automobile information security risk impact according to claim 1 is characterized in that: The impact rating calculation based on matrix multiplication calculates the impact rating matrix based on the weighted damage relationship matrix and the functional impact rating benchmark value, wherein: The function impact rating benchmark value is constructed as a diagonal matrix B of size m×m, where m is the number of impact rating dimensions and its main diagonal element is the impact rating benchmark value of each dimension. The impact rating matrix of the kth element is calculated. And round the matrix elements.
6. The automatic rating method for automobile information security risk impact according to claim 1 is characterized in that: Based on the automobile parts database, the special properties of the element to be evaluated are queried to fine-tune the impact rating of the element, wherein: For the kth element, query the vehicle asset database to determine its special properties, query the fine-tuning position ij and fine-tuning score b of the special properties on the rating matrix, and Fine-tune the element value of Get the final impact rating result matrix of the kth element 7. An automatic rating system for automobile information security risk impact, characterized in that: The system comprises: Functional impact pre-determination module, used to obtain the functional data flow diagram drawn by experts and make a preliminary judgment on the functional impact, including the functional impact type, functional impact rating benchmark value and data flow diagram element importance weight value mark; The damage relationship matrix automatic processing module is used to construct a damage relationship matrix for each element to be evaluated, and perform weighted calculation to obtain a weighted damage relationship matrix for each element; The impact rating automatic evaluation module is used to construct and calculate the impact rating matrix for each element, and use the weighted damage relationship matrix and the impact rating benchmark value to perform the impact rating calculation based on matrix multiplication; based on the vehicle asset database, the impact rating matrix is fine-tuned according to the special attributes of the elements to obtain the final calculation result of the impact rating of each element.
8. The automatic rating system for automobile information security risk impact according to claim 7 is characterized in that: In the function impact pre-determination module, based on expert experience and relevant function historical data, the function impact type is determined, including dangerous functions, protective functions and full-impact functions; and the impact rating benchmark value of the function level is given; Draw a data flow diagram, determine the importance of elements to the safety of the entire vehicle, and assign weight values; the functional impact pre-determination information serves as the input of the damage relationship matrix automatic processing module and the impact level automatic evaluation module, and also as the input of subsequent threat analysis and risk assessment.
9. The automatic rating system for automobile information security risk impact according to claim 7, characterized in that: The damage relationship matrix automatic processing module selects the corresponding damage relationship matrix according to the functional impact type and the type of element to be evaluated, and performs weighted calculation on the damage relationship matrix according to the importance weight value of the element in the data flow diagram to obtain the weighted damage relationship matrix of the element as the input of the impact level automatic evaluation module.
10. The automatic rating system for automobile information security risk impact according to claim 7, characterized in that: The impact level automatic evaluation module constructs an impact rating reference value matrix according to the functional impact rating reference value, and performs multiplication calculation with the weighted damage relationship matrix to obtain an impact rating matrix; The vehicle asset database is queried to obtain the special properties of the elements, the impact rating matrix is fine-tuned, and the final impact rating result is output as the input for subsequent threat analysis and risk assessment.