Device security analysis method, device, computer device and storage medium

Abstract

The present application relates to a device safety analysis method, apparatus, computer equipment, storage medium and computer program product. The method includes: constructing a corresponding simulation model based on the physical structure of the target device; obtaining a simulation type, and determining a matching simulation tool and simulation method based on the simulation type; determining the abnormal value range corresponding to the abnormal event, inputting at least one boundary value in the abnormal value range into the simulation model for simulation, and obtaining a boundary simulation result; testing the model validity of the simulation model, the data validity of the simulation data and the operation validity of the simulation result; if the validity test passes, sampling the abnormal value range multiple times to obtain multiple target abnormal parameters; inputting the multiple target abnormal parameters into the simulation model for simulation, obtaining the sampled simulation results, and determining the safety analysis result of the target device based on the sampled simulation results. The use of this method can improve the accuracy of equipment safety prediction.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a device security analysis method, apparatus, computer equipment, storage medium and computer program product. Background Art

[0002] With the development of science and technology, various equipments have higher and higher requirements for safety. Safety refers to the state that there is no possibility of casualties, occupational diseases, equipment damage, property loss or environmental damage. Safety is a discipline that studies how to identify, reduce and control dangers to keep them within an acceptable range. In order to fully identify and control dangers, the safety major has developed a variety of safety analysis tools such as preliminary hazard analysis, system hazard analysis, fault tree analysis, failure mode and effect analysis, etc., which well support the system safety design work.

[0003] In traditional technologies, various safety analysis tools generally identify hazards through logical deduction and induction, and measure the consequences and probability of occurrence of hazards. Such methods rely on the correctness of the logical analysis process. For systems that lack historical design data or have complex architectures, the results are often quite different from the actual operation of the system, resulting in inaccurate safety analysis. Summary of the invention

[0004] Based on this, it is necessary to provide a device safety analysis method, apparatus, computer equipment, computer-readable storage medium and computer program product that can improve the accuracy of device safety analysis in response to the above technical problems.

[0005] In a first aspect, the present application provides a device security analysis method. The method comprises:

[0006] Build a corresponding simulation model based on the physical structure of the target device;

[0007] Acquire a simulation type, and determine a matching simulation tool and simulation method based on the simulation type;

[0008] Determine an abnormal value range corresponding to an abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation using the simulation tool and simulation method to obtain a boundary simulation result;

[0009] Verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the operation validity based on the boundary simulation results;

[0010] If the model validity test, data validity test and operation validity test are all passed, multiple sampling is performed on the abnormal value range to obtain multiple target abnormal parameters;

[0011] The plurality of target abnormal parameters are respectively input into the simulation model for simulation to obtain sampling simulation results, and the safety analysis results of the target device are determined based on the sampling simulation results.

[0012] In one embodiment, the checking of the model validity of the simulation model, the checking of the data validity of the simulation data used in the simulation process, and the checking of the operation validity based on the boundary simulation result include:

[0013] Performing validity testing of the simulation model based on the difference between the actual physical model of the target device and the simulation model;

[0014] According to the authenticity of the simulation data, performing validity check on the simulation data;

[0015] The effectiveness of the simulation operation process is checked based on the error between the simulation result and the actual result.

[0016] In one embodiment, if the model validity check, the data validity check and the operation validity check are all passed, the abnormal value range is sampled multiple times to obtain multiple abnormal parameters, including:

[0017] If the model validity check, the data validity check and the operation validity check are all passed, then determine the first distribution function corresponding to the abnormal event and the second distribution function corresponding to the boundary value in the abnormal value range;

[0018] In combination with the first distribution function and the second distribution function, the values ​​in the abnormal value range are sampled multiple times to obtain multiple target abnormal parameters.

[0019] In one embodiment, the determining of the first distribution function corresponding to the abnormal event and the second distribution function corresponding to the boundary value in the abnormal value range includes:

[0020] Estimating the failure rate of the abnormal event to determine a first distribution function corresponding to the abnormal event;

[0021] Based on uniform distribution or normal distribution, a second distribution function corresponding to the boundary value in the abnormal value range is determined.

[0022] In one embodiment, determining the security analysis result of the target device based on the sampling simulation result includes:

[0023] According to the sampling simulation results corresponding to different target abnormal parameters, determine whether the corresponding target abnormal parameters have an impact on the security of the target device, and count the number of target abnormal parameters that have an impact on the security of the target device;

[0024] According to the number of target abnormal parameters that affect the safety of the target device, estimate the probability of abnormal accidents occurring within the abnormal value range;

[0025] A security analysis result of the target device is determined based on the probability.

[0026] In one embodiment, the estimating the probability of an abnormal accident occurring within the abnormal value range according to the number of target abnormal parameters that affect the safety of the target device includes:

[0027] The number of target abnormal parameters that affect the safety of the target device is used as a numerator, and the total number of the target abnormal parameters is used as a denominator, and the probability of an abnormal accident occurring within the abnormal value range is calculated.

[0028] In a second aspect, the present application also provides a device for analyzing equipment security. The device comprises:

[0029] A construction module, used to construct a corresponding simulation model based on the physical structure of the target device;

[0030] A determination module, used to obtain a simulation type, and determine a matching simulation tool and simulation method based on the simulation type;

[0031] A simulation module, used to determine the abnormal value range corresponding to the abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation through the simulation tool and simulation method to obtain a boundary simulation result;

[0032] A verification module, used to verify the model validity of the simulation model, verify the data validity of the simulation data used in the simulation process, and verify the operation validity based on the boundary simulation result;

[0033] A sampling module is used to perform multiple sampling on the abnormal value range to obtain multiple target abnormal parameters if the model validity test, the data validity test and the operation validity test are all passed;

[0034] The simulation module is also used to input the multiple target abnormal parameters into the simulation model for simulation, obtain sampling simulation results, and determine the security analysis results of the target device based on the sampling simulation results.

[0035] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0036] Build a corresponding simulation model based on the physical structure of the target device;

[0037] Acquire a simulation type, and determine a matching simulation tool and simulation method based on the simulation type;

[0038] Determine an abnormal value range corresponding to an abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation using the simulation tool and simulation method to obtain a boundary simulation result;

[0039] Verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the operation validity based on the boundary simulation results;

[0040] If the model validity test, data validity test and operation validity test are all passed, multiple sampling is performed on the abnormal value range to obtain multiple target abnormal parameters;

[0041] The plurality of target abnormal parameters are respectively input into the simulation model for simulation to obtain sampling simulation results, and the safety analysis results of the target device are determined based on the sampling simulation results.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0043] Build a corresponding simulation model based on the physical structure of the target device;

[0044] Acquire a simulation type, and determine a matching simulation tool and simulation method based on the simulation type;

[0045] Determine an abnormal value range corresponding to an abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation using the simulation tool and simulation method to obtain a boundary simulation result;

[0046] Verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the operation validity based on the boundary simulation results;

[0047] If the model validity test, data validity test and operation validity test are all passed, multiple sampling is performed on the abnormal value range to obtain multiple target abnormal parameters;

[0048] The plurality of target abnormal parameters are respectively input into the simulation model for simulation to obtain sampling simulation results, and the safety analysis results of the target device are determined based on the sampling simulation results.

[0049] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0050] Build a corresponding simulation model based on the physical structure of the target device;

[0051] Acquire a simulation type, and determine a matching simulation tool and simulation method based on the simulation type;

[0052] Determine an abnormal value range corresponding to an abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation using the simulation tool and simulation method to obtain a boundary simulation result;

[0053] Verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the operation validity based on the boundary simulation results;

[0054] If the model validity test, data validity test and operation validity test are all passed, multiple sampling is performed on the abnormal value range to obtain multiple target abnormal parameters;

[0055] The plurality of target abnormal parameters are respectively input into the simulation model for simulation to obtain sampling simulation results, and the safety analysis results of the target device are determined based on the sampling simulation results.

[0056] The above-mentioned equipment safety analysis method, device, computer equipment, storage medium and computer program product, by constructing a simulation model of the physical structure of the target equipment, and determining the corresponding simulation tool and simulation method according to the simulation category of the target equipment, at least one boundary value in the abnormal value range is input into the simulation model according to the abnormal value range corresponding to the abnormal event, and the model is simulated by the simulation tool and simulation method to obtain the boundary simulation result. Then, the model validity of the simulation model, the data validity of the simulation data used in the simulation process, and the operation validity of the boundary simulation result are tested. If the model validity test, the data validity test and the operation validity test are all passed, then the abnormal value range is sampled multiple times to obtain multiple target abnormal parameters, and the multiple target abnormal parameters are respectively input into the simulation model for simulation to obtain the sampling simulation results corresponding to each target abnormal parameter, and the safety analysis results of the target equipment are determined based on these sampling simulation results. In this way, the equipment safety problems that may be caused by abnormal events are simulated by the modeling and simulation method, so as to predict the degree of influence of abnormal events on equipment safety, and the accuracy of equipment safety prediction is improved compared with traditional safety analysis methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 An application environment diagram of a device security analysis method in an embodiment;

[0058] Figure 2 A schematic diagram of a process flow of a device safety analysis method in one embodiment;

[0059] Figure 3 It is a flowchart of a device safety analysis method in a specific embodiment;

[0060] Figure 4 A schematic diagram of a process of performing a security impact probability analysis on a target device in a specific embodiment;

[0061] Figure 5 is a structural block diagram of a device safety analysis apparatus in one embodiment;

[0062] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0064] The device security analysis method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The device security analysis method mentioned in each embodiment of the present application can be implemented by the terminal and the server separately, or it can be implemented by the terminal and the server working together. Taking the device security analysis method in the present application implemented by the terminal and the server working together as an example, the user can use the terminal to build a simulation model corresponding to the physical structure of the target device, and determine the matching simulation tool and simulation method based on the simulation type, and then determine the abnormal value range corresponding to the abnormal event, and input at least one boundary value in the abnormal value range into the simulation model through the terminal. The server simulates the simulation model in combination with the simulation tool and simulation method to obtain a boundary simulation result. The user verifies the model validity of the simulation model through the terminal, verifies the data validity of the simulation data used in the simulation process, and verifies the operation validity based on the boundary simulation results. If the model validity test, data validity test and operation validity test are all passed, the server samples the abnormal value range multiple times to obtain multiple target abnormal parameters. The user inputs the multiple target abnormal parameters into the simulation model through the terminal for simulation, obtains the sampling simulation results, and determines the security analysis results of the target device based on the sampling simulation results. Among them, the terminal 102 can be but is not limited to various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented as an independent server or a server cluster composed of multiple servers.

[0065] In one embodiment, Figure 2 As shown, a device security analysis method is provided, and the method is applied to a computer device (the computer device can be specifically Figure 1 The terminal or server in the example is used to illustrate, including the following steps:

[0066] Step S202: construct a corresponding simulation model based on the physical structure of the target device.

[0067] Among them, the simulation model is constructed based on the physical structure, material parameters and working environment of the target equipment.

[0068] Specifically, engineers will design a physical structure model of the target device according to the functions and working scenarios of the target device, and the computer equipment will build a corresponding simulation model based on the physical structure of the target device.

[0069] Step S204, obtaining the simulation type, and determining a matching simulation tool and simulation method based on the simulation type.

[0070] The simulation type is determined according to the safety category, such as electromagnetic simulation, thermal simulation, rigid body dynamics simulation, impact mechanics simulation or fluid mechanics simulation.

[0071] Specifically, according to the simulation type to which the security belongs, the computer device determines the simulation tools and simulation methods required for this simulation.

[0072] In one embodiment, if the safety issue that needs to be simulated is the problem of which part of the car the fuel leak will flow to, then the computer device can determine that the simulation type is fluid mechanics simulation, and the simulation tool can be a fluid mechanics simulation tool, which can be implemented using commercial software or through self-written programs, such as ANSYS Fluent (fluid simulation tool), and the simulation method can be an algorithm in fluid mechanics.

[0073] Step S206, determining the abnormal value range corresponding to the abnormal event, inputting at least one boundary value in the abnormal value range into the simulation model, and performing simulation through simulation tools and simulation methods to obtain boundary simulation results.

[0074] Among them, the abnormal event can be a change in the device input parameters or environmental parameters that affect the normal function of the target device. The abnormal value range corresponding to the abnormal event can be determined based on the maximum abnormal value range of the abnormal event given by the engineers of the target device during the design phase. The abnormal value range is the maximum value range in which the abnormal event can still enable the target device to continue to operate. Similarly, the abnormal value range corresponding to the abnormal event can also be offset or set to zero, which is not limited here.

[0075] Specifically, the computer device inputs at least one boundary value in the abnormal value range into the simulation model according to the abnormal value range corresponding to the abnormal event of the target device, simulates the simulation model through the determined simulation tool and simulation method, and obtains the boundary simulation result corresponding to the boundary value.

[0076] For example, if the rated working voltage of a device is 28V, and the device is marked that the working voltage of the device can fluctuate between 25V and 32V, then the abnormal event of the target device is voltage abnormality, and 25V and 32V can be the boundary values ​​of the abnormal value range corresponding to the abnormal event of the target device. The computer device inputs 25V or 32V as a boundary value into the simulation model, and uses the corresponding simulation tools and simulation methods to simulate and obtain the boundary simulation results of the target device corresponding to the 25V or 32V voltage.

[0077] Step S208, checking the model validity of the simulation model, checking the data validity of the simulation data used in the simulation process, and checking the operation validity based on the boundary simulation result.

[0078] Among them, the verification of model validity, data validity and operation validity is to ensure that the accuracy of the simulation model, simulation data and simulation results used in the simulation are valid.

[0079] Specifically, the computer device verifies the model validity of the simulation model, verifies the data validity of the simulation data used in the simulation process, and verifies the operation validity based on the boundary simulation result.

[0080] In one embodiment, the model validity of the simulation model is checked, the data validity of the simulation data used in the simulation process is checked, and the operation validity is checked based on the boundary simulation results, including: checking the validity of the simulation model based on the difference between the actual physical model of the target device and the simulation model; checking the validity of the simulation data based on the authenticity of the simulation data; and checking the validity of the simulation operation process based on the error between the simulation results and the actual results.

[0081] Specifically, for the difference between the actual physical model of the target device and the simulation model, the computer device can ensure the validity of the simulation model by comparing the actual physical model of the target device with the key structure of the simulation model. For the validity of the simulation data, the computer device can determine it by verifying the authenticity of the simulation data. For the validity of the operation, the computer device can ensure the validity of the simulation operation according to the error between the boundary simulation result and the actual result by comparing the boundary simulation result with the result of the actual test.

[0082] In one of the embodiments, the validity of the simulation data can be determined by determining whether the simulation data used is the data collected by the target device during actual application. For example, whether the material parameters used by the target device are the material parameters that the material should correspond to. For example, when simulating a dielectric material, it is necessary to input the corresponding dielectric constant and magnetic permeability.

[0083] In the above embodiment, by verifying the model validity of the simulation model, the data validity of the simulation data, and the operational validity of the boundary simulation results, the validity of the entire simulation process is ensured, thereby improving the accuracy of the target device security analysis results.

[0084] Step S210: If the model validity check, data validity check and operation validity check are all passed, the abnormal value range is sampled multiple times to obtain multiple target abnormal parameters.

[0085] Among them, sampling is used to extract multiple target abnormal parameters to eliminate the randomness of the simulation results of individual or specific target abnormal parameters.

[0086] Specifically, if the model validity check, data validity check and operation validity check are all passed, the computer device samples the abnormal value range multiple times to obtain multiple target abnormal parameters.

[0087] In one embodiment, the sampling method may be a Monte Carlo sampling method. In other embodiments, random sampling, stratified sampling or overall sampling may also be used, which is not limited in the present embodiment.

[0088] Step S212, inputting a plurality of target abnormal parameters into the simulation model for simulation respectively, obtaining sampling simulation results, and determining the security analysis results of the target device based on the sampling simulation results.

[0089] The safety analysis results include whether unexpected safety issues will occur and the probability of the unexpected safety issues occurring.

[0090] Specifically, the computer device inputs the multiple target abnormal parameters obtained by sampling into the simulation model for simulation, obtains the sampling simulation results corresponding to each sampling value, and determines the security analysis results of the target device based on the sampling simulation results corresponding to each sampling value.

[0091] In one embodiment, as shown in Table 1, if the target device is an aircraft, the computer device determines the safety analysis result of the target device based on the sampling simulation result corresponding to each sampling value of the abnormal parameter. For example, the severity level of the accident corresponding to the probability of occurrence of the safety problem can be no impact, slight impact, mild impact, severe impact and catastrophic impact. The definitions and probability requirements of different severity levels refer to Table 1.

[0092] Table 1 Safety requirements for civil aircraft

[0093]

[0094] In the above-mentioned device safety analysis method, by constructing a simulation model of the physical structure of the target device, and determining the corresponding simulation tool and simulation method according to the simulation category of the target device, at least one boundary value in the abnormal value range is input into the simulation model according to the abnormal value range corresponding to the abnormal event, and the model is simulated by the simulation tool and simulation method to obtain the boundary simulation result. Then, the model validity of the simulation model, the data validity of the simulation data used in the simulation process, and the operation validity of the boundary simulation result are tested. If the model validity test, the data validity test and the operation validity test are all passed, then the abnormal value range is sampled multiple times to obtain multiple target abnormal parameters, and the multiple target abnormal parameters are respectively input into the simulation model for simulation to obtain the sampling simulation results corresponding to each target abnormal parameter, and the safety analysis results of the target device are determined based on these sampling simulation results. In this way, the equipment safety problems that may be caused by abnormal events are simulated by the modeling and simulation method, so as to predict the degree of influence of abnormal events on equipment safety, and the probability of equipment safety prediction is improved compared with the traditional safety analysis method.

[0095] In one embodiment, if the model validity check, the data validity check and the operation validity check are all passed, the abnormal value range is sampled multiple times to obtain multiple abnormal parameters, including: if the model validity check, the data validity check and the operation validity check are all passed, then determine the first distribution function corresponding to the abnormal event and the second distribution function corresponding to the boundary value in the abnormal value range; combine the first distribution function and the second distribution function to sample the values ​​in the abnormal value range multiple times to obtain multiple target abnormal parameters.

[0096] Among them, the distribution function is the most important probability characteristic of a random variable, which is used to completely describe the statistical laws of the random variable and determine all other probability characteristics of the random variable.

[0097] Specifically, if the model validity check, data validity check and operation validity check are all passed, the computer device determines the first distribution function corresponding to the abnormal event, and the second distribution function corresponding to the boundary value in the abnormal value range. Combining the first distribution function and the second distribution function, the computer device samples the values ​​in the abnormal value range multiple times to obtain multiple target abnormal parameters.

[0098] In one embodiment, a computer device determines a first distribution function corresponding to an abnormal event and a second distribution function corresponding to a boundary value in an abnormal value range, distributes the values ​​in the abnormal value range according to the first distribution function and the second distribution function, and then samples the values ​​in the abnormal value range using a corresponding sampling method, thereby obtaining multiple target abnormal parameters.

[0099] In the above embodiment, the computer device samples the values ​​in the abnormal value range by determining the corresponding first distribution function and the second distribution function, so as to comprehensively consider the impact of abnormal events on the security of the target device and eliminate the randomness of the security impact of a single value of the abnormal parameter on the target device.

[0100] In one embodiment, a first distribution function corresponding to an abnormal event and a second distribution function corresponding to a boundary value in an abnormal value range are determined, including: estimating the failure rate of the abnormal event to determine the first distribution function corresponding to the abnormal event; and determining the second distribution function corresponding to the boundary value in the abnormal value range based on a uniform distribution or a normal distribution.

[0101] Among them, the failure rate indicates the frequency of equipment failure within a unit event. Uniform distribution is a symmetrical probability distribution, and the distribution probability in the same length interval is equally likely. Normal distribution is also called Gaussian distribution. The normal curve is bell-shaped, low at both ends, high in the middle, and symmetrical on both sides.

[0102] Specifically, the computer device estimates the failure rate of the abnormal event and determines the first distribution function corresponding to the abnormal event. The computer device determines the second distribution function corresponding to the boundary value in the abnormal value range based on uniform distribution or normal distribution.

[0103] In one embodiment, the first distribution function can be estimated by using the failure rate of the fault mode, and the failure rate can be queried through data standard manuals such as GJB299 and NPRD, or can be determined based on the experience of engineers. The second distribution function can be determined in combination with the usage scenario, and can generally be determined by using uniform distribution or normal distribution on the abnormal value range.

[0104] In the above embodiment, by using different methods to determine the required first distribution function and second distribution function in different application scenarios, the probability of security prediction of the target device can be improved in a more targeted manner.

[0105] In one embodiment, a safety analysis result of a target device is determined based on a sampling simulation result, including: determining whether the corresponding target abnormal parameters have an impact on the safety of the target device according to the sampling simulation results corresponding to different target abnormal parameters, and counting the number of target abnormal parameters that have an impact on the safety of the target device; estimating the probability of an abnormal accident occurring within an abnormal value range according to the number of target abnormal parameters that have an impact on the safety of the target device; and determining the safety analysis result of the target device based on the probability.

[0106] Specifically, the computer device compares the sampled simulation results corresponding to different target abnormal parameters obtained by simulation with corresponding standards, such as national standards, industry standards, or standards that can be determined intuitively, to determine whether the sampled simulation results corresponding to different target abnormal parameters exceed the corresponding standard provisions. If exceeded, the target abnormal parameters corresponding to the sampled simulation results will affect the safety of the target device. The computer device counts the number of target abnormal parameters that affect the safety of the target device, estimates the probability of abnormal accidents within the abnormal value range based on the number of target abnormal parameters that affect the safety of the target device, and determines the safety analysis results of the target device based on the probability.

[0107] In one of the embodiments, it is necessary to determine whether an object on a target device falling from an area on structure A will hit structure B of the target device. A computer device simulates abnormal parameters of the target position obtained by sampling the area to obtain a trajectory of the object falling from different target positions. Based on the trajectory, the computer device can intuitively determine whether the object will hit structure B after falling from different target positions. The computer device counts the number of abnormal parameters of the target position corresponding to the structure B that will be hit by the trajectory, estimates the probability of a collision within the abnormal value range, and determines the safety analysis result of the target device based on the probability.

[0108] In the above embodiment, by judging the simulation results, it is determined whether the simulation results corresponding to different sampling values ​​will cause safety impact on the target device, and the number of sampling values ​​that will cause safety impact is counted, so as to estimate the probability of abnormal accidents within the abnormal value range, and analyze the safety of the target device based on the probability. In this way, the safety analysis results obtained are more accurate and more referenceable.

[0109] In one embodiment, based on the number of target abnormal parameters that affect the safety of the target device, the probability of an abnormal accident occurring within the abnormal value range is estimated, including: taking the number of target abnormal parameters that affect the safety of the target device as the numerator and the total number of target abnormal parameters as the denominator, and calculating the probability of an abnormal accident occurring within the abnormal value range.

[0110] Specifically, the computer device uses the number of target abnormal parameters that affect the safety of the target device as the numerator and the total number of target abnormal parameters as the denominator, and calculates the probability of an abnormal accident occurring within the abnormal value range in a ratio or percentage format.

[0111] For example, the number of target abnormal parameters that affect the safety of the target device is a, and the total number of target abnormal parameters is b. Then, the probability of an abnormal accident occurring within the abnormal value range is a / b.

[0112] In the above embodiment, the probability of an abnormal accident occurring within the abnormal value range is calculated by means of a ratio, so that the possibility of an abnormal accident occurring due to abnormal parameters can be obtained more intuitively.

[0113] In a specific embodiment, Figure 3 As shown, the security analysis work for the target device is divided into two parts: design work and security work. Specifically, the computer device completes the corresponding design scheme and design model according to the functional requirements and application scenarios of the target device. According to the design model of the target device, the corresponding simulation model of the target device can be obtained, and the boundary of the obtained simulation model of the target device is expanded, including determining abnormal events and determining the abnormal value range corresponding to the abnormal events, inputting at least one boundary value of the abnormal value range as an input parameter into the simulation model for simulation, and verifying the validity of the simulation model after the simulation, the validity of the simulation data, and the operational validity of the simulation results. If the validity of the simulation model, the validity of the simulation data, and the operational validity of the simulation results fail to pass the verification, the simulation model of the target device is obtained again; if the validity of the simulation model, the validity of the simulation data, and the operational validity of the simulation results pass the verification, then based on the simulation results obtained by the simulation, the impact of the boundary value of the abnormal event on the security of the target device is determined to determine whether the boundary value will affect the security of the target device. If there will be no security impact, the simulation is terminated. If there will be a security impact, the probability that the abnormal event will affect the security of the target device is analyzed. The analysis method is as follows: Figure 4 As shown, first determine the first distribution function corresponding to the abnormal event and the second distribution function corresponding to the boundary value in the abnormal value range, combine the first distribution function and the second distribution function, perform Monte Carlo sampling on the abnormal value range, input the different sampling values ​​obtained by sampling into the simulation model for simulation, and judge the impact of the simulation results corresponding to different sampling values ​​on the security of the target device, count the number of sampling values ​​that have security impact, until the simulation of all sampling values ​​is completed, and determine the probability that the abnormal event will affect the security of the target device according to the ratio of the number of sampling values ​​that have security impact to the total number of sampling values. Finally, judge whether the security probability is acceptable. If not, readjust the design plan and design model of the target device. If acceptable, end the simulation.

[0114] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0115] Based on the same inventive concept, the embodiment of the present application also provides a device security analysis device for implementing the device security analysis method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more device security analysis device embodiments provided below can refer to the limitations of the device security analysis method above, and will not be repeated here.

[0116] In one embodiment, Figure 5 As shown, a device security analysis apparatus is provided, comprising: a construction module 501, a determination module 502, a simulation module 503, a verification module 504 and a sampling module 505, wherein:

[0117] The construction module 501 is used to construct a corresponding simulation model based on the physical structure of the target device.

[0118] The determination module 502 is used to obtain the simulation type and determine the matching simulation tool and simulation method based on the simulation type.

[0119] The simulation module 503 is used to determine the abnormal value range corresponding to the abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation through simulation tools and simulation methods to obtain boundary simulation results.

[0120] The verification module 504 is used to verify the model validity of the simulation model, verify the data validity of the simulation data used in the simulation process, and verify the operation validity based on the boundary simulation results.

[0121] The sampling module 505 is used to perform multiple sampling on the abnormal value range to obtain multiple target abnormal parameters if the model validity check, data validity check and operation validity check are all passed.

[0122] The simulation module 503 is also used to input multiple target abnormal parameters into the simulation model for simulation, obtain sampling simulation results, and determine the security analysis results of the target device based on the sampling simulation results.

[0123] In one embodiment, the verification module 504 is also used to verify the validity of the simulation model based on the difference between the actual physical model of the target device and the simulation model; to verify the validity of the simulation data based on the authenticity of the simulation data; and to verify the validity of the simulation operation process based on the error size between the simulation result and the actual result.

[0124] In one embodiment, the sampling module 505 is also used to determine the first distribution function corresponding to the abnormal event and the second distribution function corresponding to the boundary value in the abnormal value range if the model validity check, the data validity check and the operation validity check are all passed; in combination with the first distribution function and the second distribution function, the values ​​in the abnormal value range are sampled multiple times to obtain multiple target abnormal parameters.

[0125] In one embodiment, the sampling module 505 is further used to estimate the failure rate of the abnormal event to determine the first distribution function corresponding to the abnormal event; based on the uniform distribution or the normal distribution, determine the second distribution function corresponding to the boundary value in the abnormal value range.

[0126] In one embodiment, the simulation module 503 is also used to determine whether the corresponding target abnormal parameters have an impact on the safety of the target device based on the sampling simulation results corresponding to different target abnormal parameters, and to count the number of target abnormal parameters that have an impact on the safety of the target device; based on the number of target abnormal parameters that have an impact on the safety of the target device, estimate the probability of an abnormal accident occurring within the abnormal value range; and determine the safety analysis result of the target device based on the probability.

[0127] In one embodiment, the simulation module 503 is further used to calculate the probability of an abnormal accident occurring within the abnormal value range by taking the number of target abnormal parameters that affect the safety of the target device as the numerator and the total number of target abnormal parameters as the denominator.

[0128] The above-mentioned device safety analysis device constructs a simulation model of the physical structure of the target device, determines the corresponding simulation tool and simulation method according to the simulation category of the target device, inputs at least one boundary value in the abnormal value range into the simulation model according to the abnormal value range corresponding to the abnormal event, simulates the model through the simulation tool and simulation method, and obtains the boundary simulation result. Then, the model validity of the simulation model, the data validity of the simulation data used in the simulation process, and the operation validity of the boundary simulation result are tested. If the model validity test, the data validity test and the operation validity test are all passed, then the abnormal value range is sampled multiple times to obtain multiple target abnormal parameters, and the multiple target abnormal parameters are respectively input into the simulation model for simulation to obtain the sampling simulation results corresponding to each target abnormal parameter, and the safety analysis results of the target device are determined based on these sampling simulation results. In this way, the equipment safety problems that may be caused by abnormal events are simulated by the modeling and simulation method, so as to predict the degree of influence of abnormal events on equipment safety, and the probability of equipment safety prediction is improved compared with the traditional safety analysis method.

[0129] Each module in the above-mentioned device security analysis device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0130] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store sampled simulation result data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a device security analysis method is implemented.

[0131] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0132] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: constructing a corresponding simulation model based on the physical structure of the target device; obtaining a simulation type, and determining a matching simulation tool and simulation method based on the simulation type; determining an abnormal value range corresponding to an abnormal event, inputting at least one boundary value in the abnormal value range into the simulation model, and simulating through the simulation tool and the simulation method to obtain a boundary simulation result; verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the operation validity based on the boundary simulation result; if the model validity check, the data validity check, and the operation validity check are all passed, sampling the abnormal value range multiple times to obtain multiple target abnormal parameters; inputting the multiple target abnormal parameters into the simulation model for simulation respectively to obtain the sampled simulation results, and determining the security analysis result of the target device based on the sampled simulation results.

[0133] In one embodiment, when the processor executes the computer program, the following steps are also implemented: based on the difference between the actual physical model of the target device and the simulation model, the validity of the simulation model is checked; based on the authenticity of the simulation data, the validity of the simulation data is checked; based on the error size between the simulation result and the actual result, the validity of the simulation operation process is checked.

[0134] In one embodiment, when the processor executes the computer program, the following steps are also implemented: if the model validity check, the data validity check and the operation validity check are all passed, then a first distribution function corresponding to the abnormal event and a second distribution function corresponding to the boundary value in the abnormal value range are determined; in combination with the first distribution function and the second distribution function, multiple samplings are performed on the values ​​in the abnormal value range to obtain multiple target abnormal parameters.

[0135] In one embodiment, when the processor executes the computer program, the following steps are also implemented: estimating the failure rate of the abnormal event to determine the first distribution function corresponding to the abnormal event; and determining the second distribution function corresponding to the boundary value in the abnormal value range based on the uniform distribution or the normal distribution.

[0136] In one embodiment, when the processor executes the computer program, the following steps are also implemented: according to the sampling simulation results corresponding to different target abnormal parameters, determine whether the corresponding target abnormal parameters affect the safety of the target device, and count the number of target abnormal parameters that affect the safety of the target device; according to the number of target abnormal parameters that affect the safety of the target device, estimate the probability of abnormal accidents within the abnormal value range; determine the safety analysis results of the target device based on the probability.

[0137] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the number of target abnormal parameters that affect the safety of the target device is used as the numerator, the total number of target abnormal parameters is used as the denominator, and the probability of an abnormal accident occurring within the abnormal value range is calculated.

[0138] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program implements the following steps when executed by a processor: constructing a corresponding simulation model based on the physical structure of the target device; obtaining a simulation type, and determining a matching simulation tool and simulation method based on the simulation type; determining an abnormal value range corresponding to an abnormal event, inputting at least one boundary value in the abnormal value range into the simulation model, and simulating through the simulation tool and simulation method to obtain a boundary simulation result; verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the operation validity based on the boundary simulation result; if the model validity check, the data validity check, and the operation validity check are all passed, sampling the abnormal value range multiple times to obtain multiple target abnormal parameters; inputting the multiple target abnormal parameters into the simulation model for simulation respectively to obtain the sampled simulation results, and determining the security analysis result of the target device based on the sampled simulation results.

[0139] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the difference between the actual physical model of the target device and the simulation model, the validity of the simulation model is checked; based on the authenticity of the simulation data, the validity of the simulation data is checked; based on the error between the simulation result and the actual result, the validity of the simulation operation process is checked.

[0140] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the model validity check, the data validity check and the operation validity check are all passed, then a first distribution function corresponding to the abnormal event and a second distribution function corresponding to the boundary value in the abnormal value range are determined; combining the first distribution function and the second distribution function, multiple samplings are performed on the values ​​in the abnormal value range to obtain multiple target abnormal parameters.

[0141] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: estimating the failure rate of the abnormal event to determine the first distribution function corresponding to the abnormal event; and determining the second distribution function corresponding to the boundary value in the abnormal value range based on a uniform distribution or a normal distribution.

[0142] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the sampling simulation results corresponding to different target abnormal parameters, determine whether the corresponding target abnormal parameters have an impact on the safety of the target device, and count the number of target abnormal parameters that have an impact on the safety of the target device; based on the number of target abnormal parameters that have an impact on the safety of the target device, estimate the probability of an abnormal accident occurring within the abnormal value range; and determine the safety analysis result of the target device based on the probability.

[0143] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the number of target abnormal parameters that affect the safety of the target device is used as the numerator, the total number of target abnormal parameters is used as the denominator, and the probability of an abnormal accident occurring within the abnormal value range is calculated.

[0144] In one embodiment, a computer program product is provided, including a computer program, which implements the following steps when executed by a processor: constructing a corresponding simulation model based on the physical structure of a target device; obtaining a simulation type, and determining a matching simulation tool and simulation method based on the simulation type; determining an abnormal value range corresponding to an abnormal event, inputting at least one boundary value in the abnormal value range into the simulation model, and simulating through the simulation tool and simulation method to obtain a boundary simulation result; verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the operation validity based on the boundary simulation result; if the model validity check, the data validity check, and the operation validity check are all passed, sampling the abnormal value range multiple times to obtain multiple target abnormal parameters; inputting the multiple target abnormal parameters into the simulation model for simulation respectively to obtain sampled simulation results, and determining the security analysis result of the target device based on the sampled simulation results.

[0145] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the difference between the actual physical model of the target device and the simulation model, the validity of the simulation model is checked; based on the authenticity of the simulation data, the validity of the simulation data is checked; based on the error size between the simulation result and the actual result, the validity of the simulation operation process is checked.

[0146] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the model validity check, the data validity check and the operation validity check are all passed, then a first distribution function corresponding to the abnormal event and a second distribution function corresponding to the boundary value in the abnormal value range are determined; combining the first distribution function and the second distribution function, multiple samplings are performed on the values ​​in the abnormal value range to obtain multiple target abnormal parameters.

[0147] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: estimating the failure rate of the abnormal event to determine the first distribution function corresponding to the abnormal event; and determining the second distribution function corresponding to the boundary value in the abnormal value range based on a uniform distribution or a normal distribution.

[0148] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the sampling simulation results corresponding to different target abnormal parameters, determine whether the corresponding target abnormal parameters have an impact on the safety of the target device, and count the number of target abnormal parameters that have an impact on the safety of the target device; based on the number of target abnormal parameters that have an impact on the safety of the target device, estimate the probability of an abnormal accident occurring within the abnormal value range; and determine the safety analysis result of the target device based on the probability.

[0149] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the number of target abnormal parameters that affect the safety of the target device is used as the numerator, the total number of target abnormal parameters is used as the denominator, and the probability of an abnormal accident occurring within the abnormal value range is calculated.

[0150] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0151] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0152] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0153] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A device safety analysis method, characterized in that: The method comprises: Build a corresponding simulation model based on the physical structure of the target device; Acquire a simulation type, and determine a matching simulation tool and simulation method based on the simulation type; Determine an abnormal value range corresponding to an abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation using the simulation tool and simulation method to obtain a boundary simulation result; Verifying the model validity of the simulation model, verifying the data validity of the simulation data used in the simulation process, and verifying the validity of the simulation operation process based on the boundary simulation results; If the model validity test, data validity test and operation validity test are all passed, multiple sampling is performed on the abnormal value range to obtain multiple target abnormal parameters; Inputting a plurality of target abnormal parameters into the simulation model for simulation respectively to obtain sampling simulation results, and determining the safety analysis results of the target device based on the sampling simulation results; The checking of the operation validity based on the boundary simulation result includes: checking the validity of the simulation operation process according to the error between the boundary simulation result and the actual result.

2. The method according to claim 1, characterized in that The checking of the model validity of the simulation model and the checking of the data validity of the simulation data used in the simulation process include: Performing validity testing of the simulation model based on the difference between the actual physical model of the target device and the simulation model; According to the authenticity of the simulation data, the validity of the simulation data is checked.

3. The method according to claim 1, characterized in that If the model validity test, data validity test and operation validity test are all passed, the abnormal value range is sampled multiple times to obtain multiple abnormal parameters, including: If the model validity check, the data validity check and the operation validity check are all passed, then determine the first distribution function corresponding to the abnormal event and the second distribution function corresponding to the boundary value in the abnormal value range; In combination with the first distribution function and the second distribution function, the values ​​in the abnormal value range are sampled multiple times to obtain multiple target abnormal parameters.

4. The method according to claim 3, characterized in that The determining of the first distribution function corresponding to the abnormal event and the second distribution function corresponding to the boundary value in the abnormal value range includes: Estimating the failure rate of the abnormal event to determine a first distribution function corresponding to the abnormal event; Based on uniform distribution or normal distribution, a second distribution function corresponding to the boundary value in the abnormal value range is determined.

5. The method according to any one of claims 1 to 4, characterized in that The determining the security analysis result of the target device based on the sampling simulation result includes: According to the sampling simulation results corresponding to different target abnormal parameters, determine whether the corresponding target abnormal parameters have an impact on the security of the target device, and count the number of target abnormal parameters that have an impact on the security of the target device; According to the number of target abnormal parameters that affect the safety of the target device, estimate the probability of abnormal accidents occurring within the abnormal value range; A security analysis result of the target device is determined based on the probability.

6. The method according to claim 5, characterized in that The estimating the probability of abnormal accidents occurring within the abnormal value range according to the number of target abnormal parameters that affect the safety of the target device includes: The number of target abnormal parameters that affect the safety of the target device is used as a numerator, and the total number of the target abnormal parameters is used as a denominator, and the probability of an abnormal accident occurring within the abnormal value range is calculated.

7. A device for analyzing equipment safety, characterized in that: The device comprises: A construction module, used to construct a corresponding simulation model based on the physical structure of the target device; A determination module, used to obtain a simulation type, and determine a matching simulation tool and simulation method based on the simulation type; A simulation module, used to determine the abnormal value range corresponding to the abnormal event, input at least one boundary value in the abnormal value range into the simulation model, and perform simulation through the simulation tool and simulation method to obtain a boundary simulation result; A verification module, used to verify the model validity of the simulation model, verify the data validity of the simulation data used in the simulation process, and verify the validity of the simulation operation process based on the boundary simulation result; A sampling module is used to perform multiple sampling on the abnormal value range to obtain multiple target abnormal parameters if the model validity test, the data validity test and the operation validity test are all passed; The simulation module is further used to input the plurality of target abnormal parameters into the simulation model for simulation, obtain sampling simulation results, and determine the safety analysis results of the target device based on the sampling simulation results; Among them, the verification module is used to verify the effectiveness of the operation based on the boundary simulation results, and is used to verify the effectiveness of the simulation operation process according to the error size between the simulation results and the actual results.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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