Method, device and storage medium for determining risks of data security of internet of vehicles

Abstract

The application discloses a kind of vehicle networking data security risk determination method, device and storage medium.Therein, the method includes: identifying the access behavior of vehicle networking data platform, wherein, access behavior is used to indicate target access object target access operation of target data in vehicle networking data platform;Determine the first risk index of target access operation corresponding to access behavior, the second risk index corresponding to the information feature of access behavior, and the third risk index of target access object;The first risk index, the second risk index and the third risk index are weighted and processed, and the target risk index corresponding to access behavior is obtained;Based on target risk index, determine the risk level of access behavior.The application solves the technical problem that the accuracy of risk assessment of vehicle networking data security is low.

Description

Technical Field

[0001] This invention relates to the field of data security risk assessment technology, and more specifically, to a method, apparatus, and storage medium for determining the risks of vehicle network data security. Background Technology

[0002] Currently, vehicle-to-everything (V2X) data platforms face complex risk factors. Identifying risks associated with access to these platforms can provide a basis for policy formulation and decision-making, ensure the security of access controls, and maximize data security. After identifying the various risks faced by V2X data platforms, risk assessment is crucial. The assessment results will serve as the basis for risk policy formulation and risk monitoring; therefore, risk assessment for V2X data security is of paramount importance.

[0003] In related technologies, most risk assessment algorithms use multiplication or matrix methods to calculate risk values. The assessment methods are too simple and the assessment conclusions are relatively crude. Therefore, there is a technical problem of low accuracy in risk assessment of vehicle network data security.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method, apparatus, and storage medium for determining the risks of vehicle network data security, in order to at least solve the technical problem of low accuracy in risk assessment of vehicle network data security.

[0006] According to one aspect of the present invention, a method for determining the risk of vehicle-to-everything (V2X) data security is provided. The method includes: identifying access behavior of a V2X data platform, wherein the access behavior indicates a target access operation of a target access object on target data in the V2X data platform; determining a first risk indicator of the target access operation corresponding to the access behavior, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object, wherein the first risk indicator indicates the degree of impact of the target access operation on the data security of the V2X data platform, the information characteristics of the access behavior indicate the information characteristics of the target access object performing the access behavior and the information characteristics of the target data to be accessed by the access behavior, the second risk indicator indicates the degree of impact of the information characteristics of the access behavior on the data security of the V2X data platform, and the third risk indicator indicates the degree of impact of the target access object's historical access behavior on the data security of the V2X data platform; weighting the first risk indicator, the second risk indicator, and the third risk indicator to obtain a target risk indicator corresponding to the access behavior, wherein the target risk indicator indicates the degree of impact of the access behavior on the data security of the V2X data platform; and determining a risk level of the access behavior based on the target risk indicator, wherein the risk level indicates the degree of likelihood that the access behavior will pose a risk to the V2X data platform.

[0007] Optionally, determining a first risk indicator for the target access operation corresponding to the access behavior, a second risk indicator for the information characteristics of the access behavior, and a third risk indicator for the target access object includes: determining the first risk indicator based on the preset risk indicator corresponding to the target access operation and the probability of the target access operation occurring in historical access processes; determining the second risk indicator based on the first weight of the information characteristics of the target access object performing the access behavior and the risk index corresponding to the information characteristics of the target access object, and the second weight of the target data to be accessed by the access behavior and the risk index corresponding to the information characteristics of the target data; and determining the third risk indicator based on the historical number of times the target access object accesses the vehicle network data platform.

[0008] Optionally, the preset risk indicators include at least confidentiality indicators, integrity indicators, and availability indicators. Based on the preset risk indicators corresponding to the target access operation and the probability of occurrence of the target access operation in historical access processes, a first risk indicator is determined, including: determining the risk index of the confidentiality indicator, the risk index of the integrity indicator, and the risk index of the availability indicator corresponding to the target access operation based on a risk checklist, wherein the risk checklist includes the mapping relationship between various access behaviors and the risk indices of the risk indicators; determining the first product between the risk index of the confidentiality indicator and the probability of occurrence, the second product between the risk index of the integrity indicator and the probability of occurrence, and the third product between the risk index of the availability indicator and the probability of occurrence; and determining the sum of the first, second, and third products as the first risk indicator corresponding to the target access operation.

[0009] Optionally, the information characteristics of the target access object include at least: role characteristics, access level characteristics, historical violation characteristics, and risk quota indicators. The information characteristics of the target data accessed by the access behavior include at least: the sensitivity level characteristics and access level characteristics of the target data. Based on the first weight of the information characteristics of the target access object performing the access behavior and the risk index corresponding to the information characteristics of the target access object, and the second weight of the target data accessed by the access behavior and the risk index corresponding to the information characteristics of the target data, a second risk indicator is determined, including: based on the risk factor weight table, determining the first weight corresponding to the information characteristics of the target access object and the second weight corresponding to the information characteristics of the target data; determining the fourth product of the first weight and the risk index corresponding to the information characteristics of the target access object, and determining the fifth product of the second weight and the risk index corresponding to the information characteristics of the target data; and determining the sum of the fourth and fifth products as the second risk indicator.

[0010] Optionally, a third risk indicator is determined based on the historical number of times the target access object accesses the vehicle network data platform. This includes: determining the historical number of times the target access object accesses the vehicle network data platform based on the vehicle network database; and determining the third risk indicator corresponding to the historical access count based on an access count risk mapping table, wherein the access count risk mapping table includes various mapping relationships between access counts and risk indicators.

[0011] Optionally, the first risk indicator, the second risk indicator, and the third risk indicator are weighted to obtain the target risk indicator corresponding to the access behavior. This includes: determining the first influence weight of the target access operation on the data security of the vehicle network data platform based on the degree of impact of the target access operation on the data security of the vehicle network data platform; determining the second influence weight of the information characteristics of the access behavior on the data security of the vehicle network data platform based on the degree of impact of the information characteristics of the access behavior on the data security of the vehicle network data platform; and determining the third influence weight of the target access object on the data security of the vehicle network data platform based on the degree of impact of the target access object on the data security of the vehicle network data platform. The first risk indicator and the first influence weight, the second risk indicator and the second influence weight, and the third risk indicator and the third influence weight are weighted to obtain the target risk indicator corresponding to the access behavior.

[0012] Optionally, the risk level of the access behavior is determined based on the target risk indicator, including: determining the risk level of the access behavior as Level 1 in response to the target risk indicator being less than a first threshold; determining the risk level of the access behavior as Level 2 in response to the target risk indicator being greater than the first threshold but less than a second threshold; and determining the risk level of the access behavior as Level 3 in response to the target risk indicator being greater than the second threshold. The higher the risk level of the access behavior, the greater the likelihood that the access behavior will bring risks to the vehicle network data platform.

[0013] Optionally, the target access operation is at least one of the following behaviors: create, view, modify, delete, overwrite, leak, or copy.

[0014] According to another aspect of the present invention, a risk determination device for vehicle network data security is also provided. The device includes: an identification unit for identifying access behavior of a vehicle-to-everything (V2X) data platform, wherein the access behavior indicates a target access operation of a target access object on target data in the V2X data platform; a first determination unit for determining a first risk indicator of the target access operation corresponding to the access behavior, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object, wherein the first risk indicator indicates the degree of impact of the target access operation on the data security of the V2X data platform, the information characteristics of the access behavior indicate the information characteristics of the target access object performing the access behavior and the information characteristics of the target data to be accessed by the access behavior, the second risk indicator indicates the degree of impact of the information characteristics of the access behavior on the data security of the V2X data platform, and the third risk indicator indicates the degree of impact of the target access object's historical access behavior on the data security of the V2X data platform; a processing unit for weighting the first risk indicator, the second risk indicator, and the third risk indicator to obtain a target risk indicator corresponding to the access behavior, wherein the target risk indicator indicates the degree of impact of the access behavior on the data security of the V2X data platform; and a second determination unit for determining the risk level of the access behavior based on the target risk indicator, wherein the risk level indicates the degree of likelihood that the access behavior will bring risks to the V2X data platform.

[0015] According to another aspect of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the risk determination method for vehicle network data security in various embodiments of the present invention during runtime.

[0016] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to execute the risk determination method for vehicle network data security in various embodiments of the present invention.

[0017] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the method for determining the risk of vehicle network data security in various embodiments of the present invention.

[0018] According to another aspect of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the risk determination method for vehicle network data security in various embodiments of the present invention.

[0019] According to another aspect of the present invention, a computer program is also provided, which, when executed by a processor, implements the method for determining the risk of vehicle network data security in various embodiments of the present invention.

[0020] In this embodiment of the invention, access behavior of a vehicle-to-everything (V2X) data platform is identified. Access behavior indicates a target access operation by a target access object on target data within the V2X data platform. A first risk indicator corresponding to the target access operation, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object are determined. The first, second, and third risk indicators are weighted to obtain a target risk indicator corresponding to the access behavior. This target risk indicator indicates the degree of impact of the access behavior on the data security of the V2X data platform. Based on the target risk indicator, the risk level of the access behavior is determined. This risk level indicates the likelihood that the access behavior will pose a risk to the V2X data platform. In other words, this invention assesses the risk level of access behavior corresponding to the V2X data platform from multiple aspects. This ensures the accuracy of the determined risk level of the access behavior, thereby improving the accuracy of risk assessment for V2X data security. This solves the technical problem of low accuracy in risk assessment for V2X data security and achieves the goal of improving the accuracy of risk assessment for V2X data security. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0022] Figure 1 This is a flowchart of a method for determining the risk of vehicle network data security according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of a risk determination device for vehicle network data security according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to an embodiment of the present invention, a method for determining the risk of vehicle network data security is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] Figure 1 This is a flowchart of a method for determining the risk of vehicle network data security according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0028] Step S101: Identify access behavior to the vehicle network data platform.

[0029] In the technical solution provided by step S101 of the present invention, the access behavior is used to instruct the target access object to perform a target access operation on the target data in the vehicle network data platform.

[0030] In this embodiment, user behavior analysis technology can be used to identify access behavior on the vehicle-to-everything (V2X) data platform. For example, by analyzing the target user's behavior path, click behavior, and dwell time on the data platform, the target user's target access operation on the target data in the V2X data platform can be identified. The target access operation can be at least creation, viewing, deletion, or modification, but is not specifically limited here.

[0031] Step S102: Determine the first risk indicator of the target access operation corresponding to the access behavior, the second risk indicator corresponding to the information characteristics of the access behavior, and the third risk indicator of the target access object.

[0032] In the technical solution provided in step S102 of the present invention, the first risk indicator is used to indicate the degree of impact of the target access operation on the data security of the vehicle network data platform. The information characteristics of the access behavior are used to indicate the information characteristics of the target access object performing the access behavior, and the information characteristics of the target data to be accessed by the access behavior. The second risk indicator is used to indicate the degree of impact of the information characteristics of the access behavior on the data security of the vehicle network data platform. The third risk indicator is used to indicate the degree of impact of the target access object's historical access behavior on the data security of the vehicle network data platform. The information characteristics of the target access object performing the access behavior can be: role characteristics, access level characteristics, historical violation characteristics, and risk quota characteristics, etc.; the information characteristics of the target data to be accessed can be: sensitivity level characteristics, permitted access level characteristics, etc. These are merely illustrative examples and do not limit the specific content included in the information characteristics of the access behavior.

[0033] In this embodiment, after identifying the access behavior of the vehicle network data platform through step S101, a first risk indicator corresponding to the target access operation, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object are determined. The first risk indicator can be an information security risk indicator, denoted as Rcia; the second risk indicator can be called a context risk indicator, denoted as Rcon; and the third risk indicator can be called a past risk indicator of the visitor, denoted as Rhis.

[0034] Optionally, a first risk indicator is determined based on a preset risk indicator corresponding to the target access operation and the probability of the target access operation occurring in historical access processes. The preset risk indicators may include confidentiality (C) indicators, integrity (I) indicators, and availability (A) indicators; therefore, the preset risk indicators can also be referred to as CIA indicators.

[0035] For example, Table 1 is a risk checklist according to an embodiment of the present invention.

[0036] Table 1 Risk Verification Table

[0037]

[0038] As shown in Table 1, the risk checklist includes the mapping relationship between various access operations and risk indices of risk indicators. The risk index can be represented by the numbers 0 and 1. When the risk index is 0, it indicates that the risk attribute of the access operation is not considered, meaning that the access operation will not affect the current risk indicator. Conversely, when the risk index is 1, it indicates that the risk attribute of the access operation is considered, meaning that the access operation will affect the current risk indicator. Based on this, according to the risk checklist, the risk indices of the confidentiality indicator, integrity indicator, and availability indicator corresponding to the target access operation can be determined. Then, the first product between the risk index of the confidentiality indicator and the probability of occurrence of the access operation, the second product between the risk index of the integrity indicator and the probability of occurrence of the access operation, and the third product between the risk index of the availability indicator and the probability of occurrence of the access operation are determined. The sum of the first, second, and third products is then determined as the first risk indicator corresponding to the target access operation.

[0039] Alternatively, the first risk indicator can be determined using the following formula (1):

[0040] Rcia = C × P b +Ⅰ×P b +A×P b (1)

[0041]

[0042] Among them, P b N is used to represent the probability of an access action occurring. b N is used to represent the number of times a visit occurs. all This represents the total number of all access behaviors, with P representing the probability of each access behavior occurring. b This can be calculated using formula (2) based on historical statistics. Let's assume the probability P of a visitor modifying the data is... b If the value is 0.6, then its risk value Rcia = (0 × 0.6) + (1 × 0.6) + (1 × 0.6) = 1.2.

[0043] Optionally, a second risk indicator is determined based on a first weight of the information features of the target access object performing the access behavior and a risk index corresponding to the information features of the target access object, and a second weight of the target data to be accessed by the access behavior and a risk index corresponding to the information features of the target data.

[0044] For example, Table 2 is a risk factor weighting table provided according to an embodiment of the present invention.

[0045] Table 2 Risk Factor Weighting Table

[0046]

[0047] As shown in Table 2, the risk factor weight table includes the mapping relationship between each risk factor and its corresponding weight. Risk factors can include the information characteristics of the visitor and the information characteristics of the accessed information. Group 1 (visitor information characteristics) represents resource information associated with the requesting visitor. Group 2 (information characteristics of the accessed information) represents risks related to the resource itself. Table 2 lists a total of 6 risk factors in 2 groups and their corresponding weights. The total weight of each group is 0.5 (1 / 2), and the weight of each factor in each group is 0.5 / n, where n is the number of factors in the group.

[0048] Optionally, based on the risk factor weight table, the first weight corresponding to each information feature of the target access object and the second weight corresponding to each information feature of the accessed target data can be determined respectively. Then, the fourth product of the first weight and the risk index corresponding to the information feature of the target access object, and the fifth product of the second weight and the risk index corresponding to the information feature of the target data can be determined. The sum of the fourth and fifth products is then determined as the second risk indicator. For example, the second risk indicator can be determined by the following formula (3):

[0049] Rcon=∑f n ×r n (3)

[0050] Among them, f n r is used to represent the weight of risk factor n. n The risk value is used to represent the risk factor n, and the risk value of each risk factor is defined in advance. For example, the following formula (4) defines the risk value of the risk factor "role".

[0051]

[0052] Optionally, a third risk indicator can be determined based on the historical number of times the target access object accesses the vehicle network data platform.

[0053] For example, the historical number of visits by the target access object to the vehicle network data platform is determined based on the vehicle network database. Then, based on the access number risk mapping table, the third risk indicator corresponding to the historical access number is determined. The access number risk mapping table includes various mapping relationships between access numbers and risk indicators.

[0054] For another example, the third risk indicator can be determined by reading the risk values ​​from the database beforehand. If the visitor is making their first visit, then the visitor's third risk indicator Rhis is 0.

[0055] In this embodiment, a first risk indicator is determined based on a preset risk indicator corresponding to the target access operation and the probability of the target access operation occurring in historical access processes. A second risk indicator is determined based on a first weight of the information characteristics of the target access object performing the access behavior and the risk index corresponding to the information characteristics of the target access object, and a second weight of the target data to be accessed by the access behavior and the risk index corresponding to the information characteristics of the target data. A third risk indicator is determined based on the historical number of times the target access object accesses the vehicle network data platform. Step S103 is then executed based on the determined first, second, and third risk indicators.

[0056] Step S103: Weight the first risk indicator, the second risk indicator, and the third risk indicator to obtain the target risk indicator corresponding to the access behavior.

[0057] In the technical solution provided by step S103 of the present invention, the target risk index is used to indicate the degree of impact of access behavior on the data security of the vehicle network data platform.

[0058] In this embodiment, after determining the first risk indicator, the second risk indicator, and the third risk indicator through step S102, the first risk indicator, the second risk indicator, and the third risk indicator are weighted to obtain the target risk indicator corresponding to the access behavior.

[0059] Optionally, based on the degree of impact of the target access operation corresponding to the access behavior on the data security of the vehicle network data platform, a first impact weight of the target access operation on the data security of the vehicle network data platform is determined; based on the degree of impact of the information characteristics of the access behavior on the data security of the vehicle network data platform, a second impact weight of the information characteristics of the access behavior on the data security of the vehicle network data platform is determined; and based on the degree of impact of the target access object corresponding to the access behavior on the data security of the vehicle network data platform, a third impact weight of the target access object corresponding to the access behavior on the data security of the vehicle network data platform is determined.

[0060] Optionally, after determining the first influence weight, the second influence weight, and the third influence weight, the first risk indicator and the first influence weight, the second risk indicator and the second influence weight, and the third risk indicator and the third influence weight are weighted to obtain the target risk indicator corresponding to the access behavior.

[0061] For example, the target risk indicator can be calculated using the following formula (5):

[0062] Ra=(w1×Rcia)+(w2×Rcon)+(w3×Rhis) (5)

[0063] In this context, Rcia represents the first risk indicator (CIA risk), Rcon represents the second risk indicator (contextual risk), and Rhis represents the third risk indicator (the visitor's past risk value). w1 indicates the first influence weight, w2 indicates the second influence weight, and w3 indicates the third influence weight; that is, w1, w2, and w3 are the weights for each metric category.

[0064] Optionally, the influence weight of each metric category can also be obtained through expert experience. For example, the number of expert consultation rounds can be pre-set to Z; after each round of consultation, the questionnaire and the average β of the indicator evaluation for that round will be updated. i Evaluation data deviation δ j and indicator importance λ i The information is then fed back to the experts; after each expert learns about the evaluation opinions of other experts, they reflect on, revise, and improve their own evaluation opinions in the next round of evaluation; after the Nth round, which is the final round, the invention will receive the final opinions from multiple experts who have thought independently and revised and improved the information multiple times, resulting in a high degree of accuracy and rationality.

[0065] For example, if there are a total of m indicators, then the weight w of the i-th indicator is... i It can be obtained from formula (6).

[0066]

[0067] in, The importance of the indicator used to represent the Nth round, i.e., the last round, can be calculated using formula (7).

[0068]

[0069] Among them, ∝ i Used to represent the consistency of experts' evaluation opinions on indicator i, ∝ i ∈(0,1];d ji ε is used to represent the evaluation data of the j-th expert on the i-th indicator; j This represents the weight of the j-th expert. The higher the expert's reputation, the greater their weight. There are a total of n experts, ∝ i It can be calculated using formula (8).

[0070]

[0071] Among them, t ji Represents the normalized evaluation vector of the index (t) 1i ,t 2i,…t ni ), i∈1,m].

[0072] In this step, by weighting the determined first risk indicator, second risk indicator, and third risk indicator, the target risk indicator corresponding to the access behavior can be obtained. After obtaining the target risk indicator, the risk level of the access behavior can be determined through the following step S104.

[0073] Step S104: Determine the risk level of the access behavior based on the target risk indicators.

[0074] In the technical solution provided by step S104 of the present invention, the risk level is used to indicate the degree of possibility that the access behavior poses a risk to the vehicle network data platform.

[0075] In this embodiment, after obtaining the target risk index corresponding to the access behavior in step S103, the risk level of the access behavior is determined based on the target risk index.

[0076] Optionally, when the target risk indicator is less than the first threshold, the risk level of the access behavior is determined to be Level 1; when the target risk indicator is greater than the first threshold but less than the second threshold, the risk level of the access behavior is determined to be Level 2; when the target risk indicator is greater than the second threshold, the risk level of the access behavior is determined to be Level 3. The higher the risk level of the access behavior, the greater the likelihood that the access behavior will bring risks to the vehicle network data platform.

[0077] Through steps S101 to S104, access behavior of the vehicle-to-everything (V2X) data platform is identified. Access behavior indicates a target access operation by a target access object on target data within the V2X data platform. A first risk indicator corresponding to the target access operation, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator for the target access object are determined. The first, second, and third risk indicators are weighted to obtain a target risk indicator corresponding to the access behavior. This target risk indicator indicates the degree of impact of the access behavior on the data security of the V2X data platform. Based on the target risk indicator, the risk level of the access behavior is determined. The risk level indicates the likelihood of the access behavior posing a risk to the V2X data platform. In other words, this invention assesses the risk level of access behavior corresponding to the V2X data platform from multiple aspects. This ensures the accuracy of the determined risk level of the access behavior, thereby improving the accuracy of risk assessment for V2X data security. This solves the technical problem of low accuracy in risk assessment for V2X data security and achieves the goal of improving the accuracy of risk assessment for V2X data security.

[0078] The method described in this embodiment will be further described below.

[0079] As an optional implementation, determining a first risk indicator for the target access operation corresponding to the access behavior, a second risk indicator for the information characteristics of the access behavior, and a third risk indicator for the target access object includes: determining the first risk indicator based on a preset risk indicator corresponding to the target access operation and the probability of the target access operation occurring in historical access processes; determining the second risk indicator based on a first weight of the information characteristics of the target access object performing the access behavior and a risk index corresponding to the information characteristics of the target access object, and a second weight of the target data to be accessed by the access behavior and a risk index corresponding to the information characteristics of the target data; and determining the third risk indicator based on the historical number of times the target access object accesses the vehicle network data platform.

[0080] In this embodiment, a first risk indicator is determined based on a preset risk indicator corresponding to the target access operation and the probability of the target access operation occurring in historical access processes. The preset risk indicator may include C, I, and A indicators; therefore, the preset risk indicator may also be referred to as the CIA indicator.

[0081] Optionally, a second risk indicator is determined based on a first weight of the information features of the target access object performing the access behavior and a risk index corresponding to the information features of the target access object, and a second weight of the target data to be accessed by the access behavior and a risk index corresponding to the information features of the target data.

[0082] Optionally, a third risk indicator can be determined based on the historical number of times the target access object accesses the vehicle network data platform.

[0083] Optionally, this invention includes considering the access frequency of the target access object, which can more comprehensively assess the risk level of the target access object. By analyzing historical access counts, it is possible to better understand whether the access behavior of the target access object is regular and whether there is any abnormal access behavior. This allows for a more accurate assessment of the potential risks posed by the target access object, further improving security and the effectiveness of preventative measures.

[0084] As an optional implementation, the preset risk indicators include at least confidentiality indicators, integrity indicators, and availability indicators. Based on the preset risk indicators corresponding to the target access operation and the probability of occurrence of the target access operation in historical access processes, a first risk indicator is determined, including: determining the risk index of the confidentiality indicator, the risk index of the integrity indicator, and the risk index of the availability indicator corresponding to the target access operation based on a risk checklist, wherein the risk checklist includes the mapping relationship between various access behaviors and the risk indices of the risk indicators; determining the first product between the risk index of the confidentiality indicator and the probability of occurrence, the second product between the risk index of the integrity indicator and the probability of occurrence, and the third product between the risk index of the availability indicator and the probability of occurrence; and determining the sum of the first, second, and third products as the first risk indicator corresponding to the target access operation.

[0085] In this embodiment, based on the risk checklist, as shown in Table 1 above, the risk index of the confidentiality indicator, the risk index of the integrity indicator, and the risk index of the availability indicator corresponding to the target access operation are determined.

[0086] Optionally, a first product between the risk index and the probability of occurrence of the confidentiality indicator corresponding to the target access operation, a second product between the risk index and the probability of occurrence of the integrity indicator corresponding to the target access operation, and a third product between the risk index and the probability of occurrence of the availability indicator corresponding to the target access operation are determined; the sum of the first product, the second product, and the third product is determined as the first risk indicator corresponding to the target access operation.

[0087] For example, the first risk indicator can be determined using the aforementioned formula (1), where the first product can be C×P. b The second product can be I×P b The third product can be A×P b .

[0088] As an optional implementation, the information characteristics of the target access object include at least: role characteristics, access level characteristics, historical violation characteristics, and risk quota indicators. The information characteristics of the target data accessed by the access behavior include at least: the sensitivity level characteristics and the access level characteristics of the target data. Based on the first weight of the information characteristics of the target access object performing the access behavior and the risk index corresponding to the information characteristics of the target access object, and the second weight of the target data accessed by the access behavior and the risk index corresponding to the information characteristics of the target data, a second risk indicator is determined, including: based on the risk factor weight table, determining the first weight corresponding to the information characteristics of the target access object and the second weight corresponding to the information characteristics of the target data; determining the fourth product of the first weight and the risk index corresponding to the information characteristics of the target access object, and determining the fifth product of the second weight and the risk index corresponding to the information characteristics of the target data; and determining the sum of the fourth product and the fifth product as the second risk indicator.

[0089] In this embodiment, based on the risk factor weight table, the first weight corresponding to the information characteristics of the target access object and the second weight corresponding to the information characteristics of the target data are determined respectively; the fourth product of the first weight and the risk index corresponding to the information characteristics of the target access object is determined, and the fifth product of the second weight and the risk index corresponding to the information characteristics of the target data is determined; the sum of the fourth product and the fifth product is determined as the second risk index. The second risk index can be determined by the aforementioned formula (3), which will not be elaborated here.

[0090] Optionally, the present invention combines the fourth product of the first weight and the risk index corresponding to the information features of the target access object, and the fifth product of the second weight and the risk index corresponding to the information features of the target data to obtain the second risk index. By weighting the risk index with different information features, the risk of the target access object and the target data can be assessed more accurately and comprehensively.

[0091] As an optional implementation method, a third risk indicator is determined based on the historical number of times the target access object accesses the vehicle network data platform. This includes: determining the historical number of times the target access object accesses the vehicle network data platform based on the vehicle network database; and determining the third risk indicator corresponding to the historical access number based on an access number risk mapping table, wherein the access number risk mapping table includes various mapping relationships between access numbers and risk indicators.

[0092] In this embodiment, the historical number of times the target access object accesses the vehicle network data platform is determined based on the vehicle network database; a third risk indicator corresponding to the historical access number is determined based on the access number risk mapping table, wherein the access number risk mapping table includes various mapping relationships between access numbers and risk indicators.

[0093] For example, by reading the risk value from the database beforehand, if the visitor is making their first visit, then the visitor's Rhis is 0.

[0094] As an optional implementation, the first risk indicator, the second risk indicator, and the third risk indicator are weighted to obtain the target risk indicator corresponding to the access behavior. This includes: determining the first influence weight of the target access operation on the data security of the vehicle network data platform based on the degree of impact of the target access operation on the data security of the vehicle network data platform; determining the second influence weight of the information characteristics of the access behavior on the data security of the vehicle network data platform based on the degree of impact of the information characteristics of the access behavior on the data security of the vehicle network data platform; and determining the third influence weight of the target access object on the data security of the vehicle network data platform based on the degree of impact of the target access object on the data security of the vehicle network data platform based on the degree of impact of the target access object on the data security of the vehicle network data platform. The first risk indicator and the first influence weight, the second risk indicator and the second influence weight, and the third risk indicator and the third influence weight are weighted to obtain the target risk indicator corresponding to the access behavior.

[0095] In this embodiment, a first influence weight of the target access operation on the data security of the vehicle network data platform is determined based on the degree of influence of the target access operation corresponding to the access behavior on the data security of the vehicle network data platform. A second influence weight of the information characteristics of the access behavior on the data security of the vehicle network data platform is determined based on the degree of influence of the information characteristics of the access behavior on the data security of the vehicle network data platform. Finally, a third influence weight of the target access object corresponding to the access behavior on the data security of the vehicle network data platform is determined based on the degree of influence of the target access object corresponding to the access behavior on the data security of the vehicle network data platform.

[0096] Optionally, after determining the first influence weight, the second influence weight, and the third influence weight, the first risk indicator and the first influence weight, the second risk indicator and the second influence weight, and the third risk indicator and the third influence weight are weighted to obtain the target risk indicator corresponding to the access behavior.

[0097] Optionally, the influence weight of each metric category can also be obtained through expert experience. For example, the number of expert consultation rounds can be pre-set to Z; after each round of consultation, the questionnaire and the average β of the indicator evaluation for that round will be updated. i Evaluation data deviation δ j and indicator importance λ iThe information is then fed back to the experts; after each expert learns about the evaluation opinions of other experts, they reflect on, revise, and improve their own evaluation opinions in the next round of evaluation; after the Nth round, which is the final round, the invention will obtain the final opinions after multiple experts have thought independently and revised and improved them, which are highly accurate and reasonable. The influence weight of each measurement category is determined by relying on the expert experience, which can be obtained by the aforementioned formulas (6), (7), and (8), and will not be repeated here.

[0098] Optionally, the target risk indicator can be calculated using the aforementioned formula (5), which will not be elaborated here.

[0099] As an optional implementation method, the risk level of the access behavior is determined based on the target risk indicator, including: determining the risk level of the access behavior as level one when the target risk indicator is less than a first threshold; determining the risk level of the access behavior as level two when the target risk indicator is greater than the first threshold but less than a second threshold; and determining the risk level of the access behavior as level three when the target risk indicator is greater than the second threshold. The higher the risk level of the access behavior, the greater the likelihood that the access behavior will bring risks to the vehicle network data platform.

[0100] In this embodiment, when the target risk indicator is less than a first threshold, the risk level of the access behavior is determined to be level one; when the target risk indicator is greater than the first threshold but less than a second threshold, the risk level of the access behavior is determined to be level two; when the target risk indicator is greater than the second threshold, the risk level of the access behavior is determined to be level three. The higher the risk level of the access behavior, the greater the likelihood that the access behavior will bring risks to the vehicle network data platform.

[0101] Optionally, access behaviors can be categorized and assessed based on different risk indicators and thresholds to more accurately determine the degree of risk posed by these behaviors to the vehicle-to-everything (V2X) data platform. This categorization and assessment method helps to promptly identify potential risky behaviors and take corresponding measures for risk management and prevention, protecting the security and stability of the V2X data platform. Furthermore, by setting different risk levels, different handling measures can be taken for risky behaviors of different levels, improving the efficiency and targeting of risk management.

[0102] As an optional implementation, the target access operation is at least one of the following behaviors: creation operation, viewing operation, modification operation, deletion operation, overwrite operation, disclosure operation, and copy operation.

[0103] In this embodiment, the target access operation is at least one of the following behaviors: creation operation, viewing operation, modification operation, deletion operation, rewriting operation, disclosure operation, and copy operation.

[0104] Optionally, target access operations can help users achieve precise control over targets, ensuring that only authorized users can perform the corresponding operations, thus avoiding the risks of accidental operations and data leakage.

[0105] In the above steps, the access behavior of the vehicle-to-everything (V2X) data platform is identified, where the access behavior indicates the target access operation of the target access object on the target data in the V2X data platform; a first risk indicator corresponding to the target access operation, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object are determined; the first, second, and third risk indicators are weighted to obtain the target risk indicator corresponding to the access behavior, where the target risk indicator indicates the degree of impact of the access behavior on the data security of the V2X data platform; based on the target risk indicator, the risk level of the access behavior is determined, where the risk level indicates the degree of likelihood that the access behavior will bring risks to the V2X data platform. In other words, this invention assesses the risk level of the access behavior corresponding to the V2X data platform from multiple aspects, which ensures the accuracy of the determined risk level of the access behavior, thereby improving the accuracy of the risk assessment of V2X data security. This solves the technical problem of low accuracy in the risk assessment of V2X data security and achieves the goal of improving the accuracy of the risk assessment of V2X data security.

[0106] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0107] Currently, vehicle-to-everything (V2X) data platforms face complex risk factors. Identifying risks associated with access to these platforms can provide a basis for policy formulation and decision-making, ensure the security of access controls, and maximize data security. After identifying the various risks faced by V2X data platforms, risk assessment is crucial. The assessment results will serve as the basis for risk policy formulation and risk monitoring; therefore, risk assessment for V2X data security is of paramount importance.

[0108] In related technologies, most risk assessment algorithms use multiplication or matrix methods to calculate risk values. These methods are overly simplistic, resulting in relatively crude assessment conclusions. Consequently, there is a technical problem of low accuracy in risk assessment of vehicle network data security. Currently, no effective solution has been proposed to address this issue.

[0109] However, this invention provides a risk assessment method based on vehicle-to-everything (V2X) data security. By identifying access behaviors of V2X data platforms, it can determine the risk value of the visitor, the risk value of the target access operation, and the V2X data to be accessed based on the visitor performing the access behavior, the target access operation, and the V2X data to be accessed. This allows for a comprehensive consideration of multiple risk factors and risk values ​​to determine the degree of risk posed by the access behavior to V2X data security. In other words, this invention assesses the risk level of access behaviors to V2X data platforms from multiple perspectives, ensuring the accuracy of the determined risk level and solving the technical problem of low accuracy in prior art risk assessments of V2X data security. This achieves the technical effect of improving the accuracy of risk assessments for V2X data security.

[0110] In this embodiment, the present invention specifically includes two aspects: risk identification and risk quantification.

[0111] Optionally, risk identification involves identifying potential risks and existing risks that may be encountered during the access control process, identifying the characteristics of the risks, and classifying the risks to reduce uncertainty.

[0112] Optionally, the risk factors affecting the security of vehicle-to-everything (V2X) data are complex, and the main risks are as follows: First, V2X data includes sensitive information related to the vehicle itself, such as vehicle registration information, vehicle user information, and vehicle trajectory information, posing a risk of information leakage. Second, to improve the quality of data services, the positioning and application information of V2X must be tamper-proof, authentic, reliable, and trustworthy. Third, V2X data aggregates a large amount of sensitive information and has extremely high data value, making it an easy target for attacks.

[0113] Optionally, to meet the needs of identifying data security risks in the Internet of Vehicles (IoV), this invention will comprehensively use the following methods to compensate for the shortcomings of a single method: (1) Risk checklist method. Based on similar risk scenarios in the history of IoV, a risk identification checklist is drawn. By drawing on past experiences and lessons, the thinking of security administrators will become more active, and they can quickly associate potential risks through the checklist. (2) Brainstorming method. In group decision-making, the decisions of group members are easily subject to authority or the opinions of the majority, which greatly reduces the quality of the final decision. Introducing the brainstorming method in the process of identifying data security risks in IoV can ensure that the creative thinking of group decision-makers is fully utilized and improve the quality of decision-making. (3) Fault tree method. First, it is necessary to select an IoV fault state as the top event, which is the object and target to be analyzed. Then, the risk factors that cause the fault state of the top event are determined and the corresponding probabilities are calculated.

[0114] Optionally, of these three methods, the risk checklist method and brainstorming method are mainly for risk events that have not yet occurred, that is, predicting and identifying risks; while the fault tree method is mainly for risk events that have already occurred, that is, analyzing and handling risks. By using these three methods in combination, risks can be identified to the greatest extent and uncertainty can be reduced.

[0115] Optionally, risk quantification is performed based on 10 risk factors. This invention combines 3 CIA risk factors, 6 contextual risk factors, and H history records, for a total of 10 risk factors for risk quantification. The 3 CIA risk factors are the impact of confidentiality, integrity, and availability on data resource security; the 6 contextual risk factors are the impact of visitor characteristics and access information characteristics on data resource security; and the H history records represent the access history risks associated with the visitor.

[0116] Alternatively, the final risk can be calculated using the aforementioned formula (5), which will not be elaborated here.

[0117] Optionally, risk quantification is performed based on the three risk factors of CIA. According to the CIA risk value, Table 1 above lists the impact of different types of access behaviors on the confidentiality, integrity and availability of data in the Internet of Vehicles environment. The above formula (1) represents the risk quantification of access behaviors based on CIA. Where 1 indicates that the behavior considers risk attributes, and 0 indicates that the behavior attributes are not considered.

[0118] Optionally, the context risk value Rcon can be calculated using formula (3), which will not be elaborated here.

[0119] Optionally, the weighting of the measurement categories in this invention mainly relies on expert experience. The process is as follows: (1) Pre-set the number of expert consultation rounds as Z; (2) After each round of consultation, the questionnaire and the average value of the indicator evaluation β for this round will be updated. i Evaluation data deviation δ j and indicator importance λ i (3) After each expert learns about the evaluation opinions of other experts, they will think about, modify and improve their own evaluation opinions in the next round of evaluation; (4) After the Nth round, that is, the last round, the present invention will receive the final opinions of multiple experts who have thought independently and revised and improved the invention multiple times, which are highly accurate and reasonable.

[0120] In this embodiment, by identifying access behavior to the vehicle-to-everything (V2X) data platform, the risk values ​​of the visitor, the target access operation, and the V2X data to be accessed can be determined based on the visitor, the target access operation, and the V2X data. This allows for a comprehensive assessment of multiple risk factors and risk values ​​to determine the degree of risk posed by the access behavior to V2X data security. In other words, this invention evaluates the risk level of access behavior to the V2X data platform from multiple perspectives, ensuring the accuracy of the determined risk level and solving the technical problem of low accuracy in risk assessment of V2X data security in existing technologies. This achieves the technical effect of improving the accuracy of risk assessment for V2X data security.

[0121] According to an embodiment of the present invention, a risk determination device for vehicle network data security is also provided. It should be noted that this risk determination device for vehicle network data security can be used to execute the risk determination method for vehicle network data security in Embodiment 1.

[0122] Figure 2 This is a schematic diagram of a risk determination device for vehicle network data security according to an embodiment of the present invention. Figure 2 As shown, the vehicle network data security risk determination device 200 may include: an identification unit 201, a first determination unit 202, a processing unit 203, and a second determination unit 204.

[0123] The identification unit 201 is used to identify the access behavior of the vehicle network data platform, wherein the access behavior is used to indicate the target access object's target access operation on the target data in the vehicle network data platform.

[0124] The first determining unit 202 is used to determine a first risk indicator of the target access operation corresponding to the access behavior, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object. The first risk indicator is used to indicate the degree of impact of the target access operation on the data security of the vehicle network data platform. The information characteristics of the access behavior are used to indicate the information characteristics of the target access object performing the access behavior and the information characteristics of the target data to be accessed by the access behavior. The second risk indicator is used to indicate the degree of impact of the information characteristics of the access behavior on the data security of the vehicle network data platform. The third risk indicator is used to indicate the degree of impact of the historical access behavior of the target access object on the data security of the vehicle network data platform.

[0125] The processing unit 203 is used to perform weighted processing on the first risk indicator, the second risk indicator, and the third risk indicator to obtain the target risk indicator corresponding to the access behavior. The target risk indicator is used to indicate the degree of impact of the access behavior on the data security of the vehicle network data platform.

[0126] The second determining unit 204 is used to determine the risk level of the access behavior based on the target risk indicators, wherein the risk level is used to indicate the degree of possibility that the access behavior poses a risk to the vehicle network data platform.

[0127] Optionally, the first determining unit 202 may include: a first determining module, used to determine a first risk indicator based on a preset risk indicator corresponding to the target access operation and the probability of occurrence of the target access operation in historical access processes; a second determining module, used to determine a second risk indicator based on a first weight of the information features of the target access object performing the access behavior and a risk index corresponding to the information features of the target access object, and a second weight of the target data to be accessed by the access behavior and a risk index corresponding to the information features of the target data; and a third determining module, used to determine a third risk indicator based on the historical number of times the target access object accesses the vehicle network data platform.

[0128] Optionally, the first determining module may include: a first determining submodule, used to determine the risk index of the confidentiality indicator, the risk index of the integrity indicator, and the risk index of the availability indicator corresponding to the target access operation based on a risk checklist, wherein the risk checklist includes a mapping relationship between various access behaviors and the risk indices of the risk indicators; a second determining submodule, used to determine the first product between the risk index of the confidentiality indicator and the probability of occurrence, the second product between the risk index of the integrity indicator and the probability of occurrence, and the third product between the risk index of the availability indicator and the probability of occurrence; and a third determining submodule, used to determine the sum of the first product, the second product, and the third product as the first risk indicator corresponding to the target access operation.

[0129] Optionally, the second determining module may include: a fourth determining submodule, used to determine, based on the risk factor weight table, a first weight corresponding to the information characteristics of the target access object and a second weight corresponding to the information characteristics of the target data; a fifth determining submodule, used to determine the fourth product of the first weight and the risk index corresponding to the information characteristics of the target access object, and to determine the fifth product of the second weight and the risk index corresponding to the information characteristics of the target data; and a sixth determining submodule, used to determine the sum of the fourth and fifth products as the second risk indicator.

[0130] Optionally, the third determining module may include: a seventh determining submodule, used to determine the historical number of times the target access object accesses the vehicle network data platform based on the vehicle network database; and an eighth determining submodule, used to determine the third risk indicator corresponding to the historical access number based on the access number risk mapping table, wherein the access number risk mapping table includes various mapping relationships between access numbers and risk indicators.

[0131] Optionally, the processing unit 203 may include: a fourth determining module, used to determine a first influence weight of the target access operation on the data security of the vehicle network data platform based on the degree of influence of the target access operation corresponding to the access behavior on the data security of the vehicle network data platform; a second influence weight of the information characteristics of the access behavior on the data security of the vehicle network data platform based on the degree of influence of the information characteristics of the access behavior on the data security of the vehicle network data platform; and a third influence weight of the target access object corresponding to the access behavior on the data security of the vehicle network data platform based on the degree of influence of the target access object corresponding to the access behavior on the data security of the vehicle network data platform; and a weighting module, used to perform weighted processing on the first risk indicator and the first influence weight, the second risk indicator and the second influence weight, and the third risk indicator and the third influence weight to obtain the target risk indicator corresponding to the access behavior.

[0132] Optionally, the second determining unit 204 may include: a fifth determining module, used to determine the risk level of the access behavior as a first level in response to the target risk indicator being less than a first threshold; a sixth determining module, used to determine the risk level of the access behavior as a second level in response to the target risk indicator being greater than the first threshold and less than a second threshold; and a seventh determining module, used to determine the risk level of the access behavior as a third level in response to the target risk indicator being greater than the second threshold, wherein the higher the risk level of the access behavior, the greater the likelihood that the access behavior will bring risks to the vehicle network data platform.

[0133] In this embodiment, access behavior of the vehicle-to-everything (V2X) data platform is identified. Access behavior indicates a target access operation by a target access object on target data within the V2X data platform. A first risk indicator corresponding to the target access operation, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object are determined. The first, second, and third risk indicators are weighted to obtain a target risk indicator corresponding to the access behavior. This target risk indicator indicates the degree of impact of the access behavior on the data security of the V2X data platform. Based on the target risk indicator, the risk level of the access behavior is determined. This risk level indicates the likelihood that the access behavior will pose a risk to the V2X data platform. In other words, this invention assesses the risk level of access behavior corresponding to the V2X data platform from multiple aspects. This ensures the accuracy of the determined risk level of the access behavior, thereby improving the accuracy of risk assessment for V2X data security. This solves the technical problem of low accuracy in risk assessment for V2X data security and achieves the goal of improving the accuracy of risk assessment for V2X data security.

[0134] Embodiments of this application also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the risk determination method for vehicle network data security in various embodiments of the present invention during runtime.

[0135] Embodiments of this application also provide a computer-readable storage medium, which includes a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to execute the risk determination method for vehicle network data security in various embodiments of the present invention.

[0136] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the risk determination method for vehicle network data security in various embodiments of the present invention.

[0137] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program. When the computer program is executed by a processor, it implements the risk determination method for vehicle network data security in various embodiments of the present invention.

[0138] The embodiments of this application also provide a computer program that, when executed by a processor, implements the risk determination method for vehicle network data security in the various embodiments of the present invention described above.

[0139] Embodiments of this application also provide a vehicle for performing the vehicle-to-everything (V2X) data security risk determination method in various embodiments of the present invention.

[0140] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0141] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0143] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0144] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0145] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0146] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining the risks of vehicle network data security, characterized in that, The method comprises: identifying an access behavior of a vehicle Internet data platform, wherein the access behavior is used to indicate a target access operation of a target access object on target data in the vehicle Internet data platform; determining a first risk indicator of the target access operation corresponding to the access behavior, a second risk indicator of information features of the access behavior, and a third risk indicator of the target access object, wherein the first risk indicator is used to indicate an influence degree of the target access operation on data security of the vehicle Internet data platform, the information features of the access behavior are used to indicate information features of the target access object performing the access behavior and information features of the target data to be accessed by the access behavior, the second risk indicator is used to indicate an influence degree of the information features of the access behavior on data security of the vehicle Internet data platform, and the third risk indicator is used to indicate an influence degree of historical access behaviors of the target access object on data security of the vehicle Internet data platform; performing weighted processing on the first risk indicator, the second risk indicator, and the third risk indicator to obtain a target risk indicator corresponding to the access behavior, wherein the target risk indicator is used to indicate an influence degree of the access behavior on data security of the vehicle Internet data platform; based on the target risk indicator, determining a risk level of the access behavior, wherein the risk level is used to indicate a possibility degree of the access behavior bringing risks to the vehicle Internet data platform; wherein determining the first risk indicator of the target access operation corresponding to the access behavior, the second risk indicator of the information features of the access behavior, and the third risk indicator of the target access object comprises: determining the first risk indicator based on a preset risk indicator corresponding to the target access operation and an occurrence probability of the target access operation in a historical access process; determining the second risk indicator based on a first weight of the information features of the target access object performing the access behavior and a risk index corresponding to the information features of the target access object, and a second weight of the target data to be accessed by the access behavior and a risk index corresponding to the information features of the target data; and determining the third risk indicator based on a historical access frequency of the target access object on the vehicle Internet data platform.

2. The method of claim 1, wherein, The preset risk indicator at least includes a confidentiality indicator, an integrity indicator, and an availability indicator, and determining the first risk indicator based on the preset risk indicator corresponding to the target access operation and the occurrence probability of the target access operation in the historical access process comprises: determining a risk index of the confidentiality indicator corresponding to the target access operation, a risk index of the integrity indicator corresponding to the target access operation, and a risk index of the availability indicator corresponding to the target access operation based on a risk check table, wherein the risk check table includes a mapping relationship between a plurality of access behaviors and risk indexes of risk indicators. determining a first product between a risk index of the confidentiality index corresponding to the target access operation and the occurrence probability, a second product between a risk index of the integrity index corresponding to the target access operation and the occurrence probability, and a third product between a risk index of the availability index corresponding to the target access operation and the occurrence probability; determining a sum of the first product, the second product and the third product as the first risk index corresponding to the target access operation.

3. The method of claim 1, wherein, The information characteristics of the target access object at least include role characteristics, access level characteristics, historical violation characteristics and risk quota indicators, and the information characteristics of the target data accessed by the access behavior at least include sensitivity level characteristics of the target data and access level characteristics of the target data. The second risk index is determined based on a first weight of the information characteristics of the target access object performing the access behavior and a risk index corresponding to the information characteristics of the target access object, and a second weight of the information characteristics of the target data and a risk index corresponding to the information characteristics of the target data, comprising: determining the first weight corresponding to the information characteristics of the target access object and the second weight corresponding to the information characteristics of the target data based on a risk factor weight table; determining a fourth product of the first weight and a risk index corresponding to the information characteristics of the target access object, and a fifth product of the second weight and a risk index corresponding to the information characteristics of the target data; determining a sum of the fourth product and the fifth product as the second risk index.

4. The method of claim 1, wherein, The third risk index is determined based on a historical access frequency of the target access object to the vehicle Internet data platform, comprising: determining the historical access frequency of the target access object to the vehicle Internet data platform based on a vehicle Internet database; determining a third risk index corresponding to the historical access frequency based on an access frequency risk mapping table, wherein the access frequency risk mapping table includes a mapping relationship between a plurality of access frequencies and risk indicators.

5. The method of claim 1, wherein, The first risk index, the second risk index and the third risk index are weighted to obtain a target risk index corresponding to the access behavior, comprising: determining a first impact weight of the target access operation on the data security of the vehicle Internet data platform based on an impact degree of the target access operation corresponding to the access behavior on the data security of the vehicle Internet data platform, determining a second impact weight of the information characteristics of the access behavior on the data security of the vehicle Internet data platform based on an impact degree of the information characteristics of the access behavior, and determining a third impact weight of the target access object corresponding to the access behavior on the data security of the vehicle Internet data platform based on an impact degree of the target access object corresponding to the access behavior on the data security of the vehicle Internet data platform. The first risk indicator and the first influence weight, the second risk indicator and the second influence weight, and the third risk indicator and the third influence weight are weighted to obtain the target risk indicator corresponding to the access behavior.

6. The method of claim 1, wherein, Based on the target risk indicators, the risk level of the access behavior is determined, including: In response to the target risk indicator being less than a first threshold, the risk level of the access behavior is determined to be level one; In response to the target risk indicator being greater than the first threshold and less than the second threshold, the risk level of the access behavior is determined to be the second level; In response to the target risk indicator being greater than the second threshold, the risk level of the access behavior is determined to be level three, wherein the higher the risk level of the access behavior, the greater the likelihood that the access behavior will pose a risk to the vehicle network data platform.

7. The method of claim 1, wherein, The target access operation is at least one of the following behaviors: creation operation, viewing operation, modification operation, deletion operation, rewriting operation, disclosure operation, and copy operation. 8.A risk determination apparatus for data security of Internet of Vehicles, characterized in that, include: The identification unit is used to identify the access behavior of the vehicle network data platform, wherein the access behavior is used to indicate the target access object's target access operation on the target data in the vehicle network data platform; The first determining unit is configured to determine a first risk indicator of the target access operation corresponding to the access behavior, a second risk indicator corresponding to the information characteristics of the access behavior, and a third risk indicator of the target access object. The first risk indicator indicates the degree of impact of the target access operation on the data security of the vehicle-to-everything (V2X) data platform. The information characteristics of the access behavior indicate the information characteristics of the target access object executing the access behavior and the information characteristics of the target data to be accessed by the access behavior. The second risk indicator indicates the degree of impact of the information characteristics of the access behavior on the data security of the V2X data platform. The third risk indicator indicates the degree of impact of the historical access behavior of the target access object on the data security of the V2X data platform. The processing unit is used to perform weighted processing on the first risk indicator, the second risk indicator, and the third risk indicator to obtain the target risk indicator corresponding to the access behavior, wherein the target risk indicator is used to indicate the degree of impact of the access behavior on the data security of the vehicle network data platform. The second determining unit is used to determine the risk level of the access behavior based on the target risk indicator, wherein the risk level is used to indicate the degree of possibility that the access behavior poses a risk to the vehicle network data platform; The first determining unit is further configured to determine, through the following steps, a first risk indicator of the target access operation corresponding to the access behavior, a second risk indicator corresponding to the information features of the access behavior, and a third risk indicator of the target access object: determining the first risk indicator based on a preset risk indicator corresponding to the target access operation and the probability of occurrence of the target access operation in historical access processes; determining the second risk indicator based on a first weight of the information features of the target access object executing the access behavior and a risk index corresponding to the information features of the target access object, and a second weight of the target data to be accessed by the access behavior and a risk index corresponding to the information features of the target data; and determining the third risk indicator based on the historical number of accesses of the target access object to the vehicle network data platform.

9. An electronic device, comprising: include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 7.

11. A computer program product, characterised in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 7.

12. A vehicle characterized by comprising: The vehicle is used to perform the method according to any one of claims 1 to 7.

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