5G industrial internet security access control method and device

Abstract

The invention provides a 5G industrial internet security access control method and device. Comprising the steps that a 5G industrial terminal initiates an access request to an edge network element, and industrial environment electromagnetic interference intensity and a terminal 5G signal to noise ratio corresponding to the access request are collected in real time; according to the collected industrial environment electromagnetic interference intensity and the signal-to-noise ratio of the terminal 5G signal, a safety access threshold is dynamically calculated in combination with the safety level of the terminal; based on the calculated security access threshold, cooperatively allocating channel resources and edge network element computing power resources in combination with the total occupancy rate of 5G private network channels and terminal encryption computing power requirements; acquiring the encryption delay of the edge network element to the terminal data, and correcting the effective success rate of the secure access of the terminal according to the cooperatively distributed resource weight and the encryption delay; if the corrected security access effective success rate reaches a preset threshold 0.8, the terminal is allowed to access the 5G industrial internet, and the security and stable operation of the SDN network in the key field can be guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial internet, and in particular to a 5G industrial internet security access control method and device. BACKGROUND

[0002] With the wide application of software defined network in key fields such as energy scheduling and industrial control, the authorization management of SDN software has become the core link to ensure the safe allocation of network resources and the stable operation of business. At present, the existing SDN software authorization management scheme generally adopts a static authorization mechanism, and its core logic revolves around the verification of the legitimacy of user identity, that is, through the pre-set user role or device ID, the fixed permission is allocated, and in the authorization process, only the identity verification is completed, and the dynamic running state parameters of the SDN network are not further associated. However, this kind of static authorization scheme has significant technical defects: it does not include the real-time load of the SDN controller, the trust level of the edge node, the delay demand of the slice business and other key dynamic parameters in the authorization decision system, and after the authorization instruction is issued, it does not monitor the changes of the above parameters in real time, and it is also impossible to trigger the recalculation of the authorization resource quota, the trust threshold or the time limit based on the parameter changes. This defect leads to frequent problems in actual application, for example, when the SDN controller is in a high load state, the static allocation of authorization resources is easy to cause the delay of the controller response, and even leads to the interruption of low-latency key businesses such as power scheduling; when the trust level of the edge node decreases due to environmental interference or potential attacks, the static trust threshold cannot be adjusted in time, and it is easy to appear the security vulnerability of low-trust nodes occupying high-priority slice resources. Therefore, the existing static authorization mechanism cannot adapt to the dynamic running characteristics of the SDN network.

[0003] Based on the above problems, a technical scheme that can combine network dynamic parameters and realize real-time adjustment of authorization decision is needed to solve the problem of mismatch between static authorization and SDN dynamic running demand, and to ensure the safe and stable operation of SDN network in key fields. SUMMARY

[0004] The purpose of the present application is a 5G industrial internet security access control method, which comprises: The 5G industrial terminal initiates an access request to the edge network element, and collects the industrial environment electromagnetic interference intensity and the terminal 5G signal signal-to-noise ratio corresponding to the access request in real time; According to the collected industrial environment electromagnetic interference intensity and terminal 5G signal signal-to-noise ratio, the security access threshold is dynamically calculated in combination with the terminal security level; Based on the calculated security access threshold, the channel resources and edge network element computing resources are allocated in combination with the total occupancy rate of the 5G private network channel and the terminal encryption computing power demand; Collect the encryption delay of the edge network element to the terminal data, and correct the terminal security access effective success rate according to the resource weight and encryption delay of the collaborative allocation. If the corrected security access success rate reaches the preset threshold of 0.8, the terminal is allowed to access the 5G Industrial Internet; otherwise, the steps of dynamically calculating the security access threshold and collaboratively allocating resources are re-executed.

[0005] Preferably, in the step of real-time acquisition of the industrial environment electromagnetic interference intensity and the terminal 5G signal signal-to-noise ratio corresponding to the access request, an electromagnetic interference sensor is used to acquire the industrial environment electromagnetic interference intensity, and a 5G signal acquisition unit is used to acquire the terminal 5G signal signal-to-noise ratio. The electromagnetic interference intensity is the electric field strength, and the 5G signal signal-to-noise ratio is the ratio of the received signal power to the noise power. The electromagnetic interference sensor is used to acquire electromagnetic interference data in the range of 10-100dBμV / m, and the 5G signal acquisition unit is used to perform high-frequency signal sampling to obtain signal-to-noise ratio data.

[0006] In a further preferred embodiment, in the step of dynamically calculating the safety access threshold based on the collected industrial environment electromagnetic interference intensity and the terminal 5G signal-to-noise ratio, combined with the terminal safety level, the terminal safety level is divided into five levels: Level 1 corresponds to ordinary monitoring terminals, and Level 5 corresponds to core control terminals. Each level corresponds to a fixed safety factor. The EMI compensation amount is determined based on the difference between the electromagnetic interference intensity and the reference electromagnetic interference intensity. The reference electromagnetic interference intensity is 30 dBμV / m. For every 10 dBμV / m increase in the difference, the EMI compensation amount increases by 0.2. The safety factor is used to quantify the influence weight of different safety levels on the access threshold.

[0007] In a further preferred embodiment, in the step of collaboratively allocating channel resources and edge network element computing resources based on the calculated security access threshold, combined with the total occupancy rate of the 5G private network channel and the terminal encryption computing power requirements, the total occupancy rate of the 5G private network channel is the ratio of the currently occupied channel bandwidth to the total channel bandwidth, the total channel bandwidth is determined according to the 5G private network configuration, and the terminal encryption computing power requirements are determined according to the type of encryption algorithm used by the terminal. Different encryption algorithms correspond to different basic computing power requirements. During collaborative allocation, resources are preferentially allocated to terminals with high security access thresholds and low encryption computing power requirements. The allocation priority is divided into three levels according to the security access threshold and encryption computing power requirements, and each priority level corresponds to a different resource allocation ratio.

[0008] A further preferred method is to dynamically calculate the security access threshold using the following formula: ; Where Ti represents the security access threshold of the i-th terminal, SLi represents the security level of the i-th terminal, K1 represents the security level coefficient with a value of 1.2, a represents the SNR sensitivity coefficient with a value of 0.3, SNR0 represents the reference signal-to-noise ratio with a value of 20dB, SNRi represents the actual signal-to-noise ratio of the i-th terminal, ΔTEMI represents the EMI compensation amount, and e represents the natural constant with a value of 2.718.

[0009] A further preferred approach is to use the following formula to determine the resource allocation weights when collaboratively allocating channel resources and edge network element computing resources: ; Among them W i K represents the channel-computing power allocation weight for the i-th terminal, K2 represents the weight coefficient with a value of 0.8, and CO total denoted as 5G private network total channel occupancy rate, b represents computing power demand sensitivity coefficient with a value of 0.4, CR max CR represents the maximum computing power requirement of an edge network element, with a value of 200 MIPS. i This represents the encryption computing power requirement of the i-th terminal.

[0010] Further optimized, the process for improving the effective success rate of secure terminal access satisfies the following two formulas: , Where η represents the effective success rate correction coefficient, c represents the weight sensitivity coefficient with a value of 0.5, and W min represents the minimum resource allocation weight with a value of 0.2, f represents the encryption latency impact coefficient with a value of 0.6, and D enci This represents the actual encryption delay of the i-th terminal. T represents the maximum allowed encryption delay, with a value of 15ms. max P represents the maximum admission threshold with a value of 10, P0 represents the basic access success rate with a value of 0.9, and P... i This represents the successful secure access rate of the i-th terminal.

[0011] In a further preferred embodiment, in the step of collecting the encryption delay of terminal data by the edge network element, the encryption delay is collected in real time by the computing power monitoring unit of the edge network element. The computing power monitoring unit is electrically connected to the processor of the edge network element, and the collection frequency is consistent with the frequency of the terminal access request. The encryption delay increases with the increase of the computing power utilization rate of the edge network element. The correlation between computing power utilization rate and encryption delay is determined according to the hardware performance of the edge network element. Edge network elements with different hardware performance correspond to different computing power utilization rate-encryption delay change curves.

[0012] A 5G industrial internet secure access control device, applied to the 5G industrial internet secure access control method as described in any one of the above, includes: a communication module for receiving access requests from 5G industrial terminals, characterized in that it further includes an EMI-SNR acquisition module, an access threshold calculation module, a channel-computing power allocation module, a success rate correction module, and a security authentication module. The EMI-SNR acquisition module, access threshold calculation module, channel-computing power allocation module, success rate correction module, and security authentication module are sequentially electrically connected. The communication module is electrically connected to the access threshold calculation module and the security authentication module respectively. The EMI-SNR acquisition module is used to acquire the electromagnetic interference intensity of the industrial environment and the signal-to-noise ratio of the terminal's 5G signal in real time. The access threshold calculation module is used to dynamically calculate a secure access threshold based on the acquired parameters and the terminal's security level. The channel-computing power allocation module is used to collaboratively allocate channel resources and edge network element computing power resources based on the secure access threshold. The success rate correction module is used to correct the effective access success rate based on encryption delay. The security authentication module is used to determine whether to allow terminal access based on the corrected success rate.

[0013] Further preferably, the EMI-SNR acquisition module includes an electromagnetic interference sensor and a 5G signal analyzer, with the output of the electromagnetic interference sensor electrically connected to the input of the 5G signal analyzer; the access threshold calculation module includes a domestically produced C86 architecture processor and a memory, with the memory storing a program for calculating the security access threshold, and the processor calling the program to perform the calculation operation; the security authentication module integrates an SM4 encryption chip, which is electrically connected to the communication module and used to encrypt and authenticate terminal access data; the channel-computing power allocation module includes a 5G channel scheduling unit and a computing power allocation unit, with the 5G channel scheduling unit supporting FlexE slicing technology to achieve flexible allocation of channel resources, and the computing power allocation unit electrically connected to the IPMI interface of the edge network element to obtain edge network element computing power status data.

[0014] Compared with the prior art, the present invention has the following advantages: This invention effectively solves the main problems of low secure access success rate caused by strong electromagnetic interference, multi-terminal concurrent channel congestion, and fluctuations in edge network element computing power in the background technology by real-time acquisition of electromagnetic interference intensity and terminal 5G signal signal-to-noise ratio, dynamic calculation of security access threshold based on terminal security level, collaborative allocation of channel and edge network element computing power resources based on threshold, and correction of access success rate based on encryption delay and closed-loop adjustment. It ensures the effectiveness and adaptability of 5G industrial internet secure access in industrial scenarios. Attached Figure Description

[0015] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0016] Figure 1 This is a flowchart of a 5G industrial internet secure access control method according to the present invention; Figure 2 This is a connection block diagram of a 5G industrial internet secure access control device according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0018] The concepts involved in this application will first be described with reference to the accompanying drawings. It should be noted that the following descriptions of various concepts are only for the purpose of making the content of this application easier to understand and do not constitute a limitation on the scope of protection of this application; furthermore, the embodiments and features in the embodiments of this application can be combined with each other unless otherwise specified. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0019] In existing 5G industrial internet security access control, strong electromagnetic interference leads to authentication misjudgment, multiple terminals concurrency causes channel congestion, and fluctuations in edge network element computing power cause encryption delays. The combination of these three factors results in a low effective success rate for secure access, and the lack of a multi-factor collaborative control mechanism makes it unsuitable for industrial scenario requirements.

[0020] Based on this, please refer to Figure 1 This embodiment provides a 5G industrial internet secure access control method, including: S1: The 5G industrial terminal initiates an access request to the edge network element and collects the electromagnetic interference intensity of the industrial environment and the signal-to-noise ratio of the terminal's 5G signal in real time corresponding to the access request. S2: Based on the collected electromagnetic interference intensity in the industrial environment and the signal-to-noise ratio of the terminal's 5G signal, the security access threshold is dynamically calculated in combination with the terminal's security level. S3: Based on the calculation of security access thresholds, combined with the total occupancy rate of 5G private network channels and the terminal encryption computing power requirements, channel resources and edge network element computing power resources are allocated in a coordinated manner. S4: Collect the encryption latency of terminal data by edge network elements, and correct the effective success rate of terminal secure access based on the resource weights and encryption latency allocated collaboratively; S5: If the corrected security access success rate reaches the preset threshold of 0.8, then the terminal is allowed to access the 5G Industrial Internet; otherwise, the steps of dynamically calculating the security access threshold and coordinating resource allocation are re-executed.

[0021] This solution centers on multi-factor collaborative control. First, it uses dedicated acquisition equipment to acquire real-time data on the electromagnetic interference intensity of the industrial environment and the signal-to-noise ratio (SNR) of the terminal's 5G signal. These two parameters serve as the foundational inputs for subsequent calculations, ensuring that the acquired environmental and signal data accurately reflects the access scenario. Next, it dynamically calculates the security access threshold based on the terminal's security level. This step breaks away from the traditional fixed threshold model, allowing the threshold to be flexibly adjusted according to environmental interference and terminal importance, preventing false rejection of legitimate terminals or unauthorized access by low-security terminals under strong interference. Then, based on the access threshold, it coordinates the total occupancy rate of the 5G private network channels and the terminal's encryption computing power requirements to collaboratively allocate channel and computing power resources, prioritizing resource supply to terminals with high access thresholds and low computing power requirements, thus resolving resource mismatch issues during multi-terminal concurrency. Finally, it collects the encryption latency of terminal data from edge network elements and adjusts the secure access success rate based on resource weights. A preset threshold of 0.8 is used as the access judgment standard; if the standard is not met, the threshold and resource allocation are readjusted, forming a closed-loop control system. This ensures that each step revolves around improving access effectiveness, and that data is linked between steps, avoiding the limitations of single-factor control.

[0022] The technical effects of the above embodiments include: solving access problems caused by multiple factors, improving the effective success rate of secure access, adapting to the real-time and security requirements of industrial scenarios, and reducing false rejections and resource waste.

[0023] In existing technologies, when collecting data on the intensity of electromagnetic interference in industrial environments and the signal-to-noise ratio of 5G signals from terminals, the functional positioning of the data acquisition equipment is ambiguous, and the data acquisition range and applicable scenarios are unclear, resulting in insufficient accuracy of the collected parameters and an inability to provide reliable input for subsequent access control.

[0024] Based on this, in the step of real-time acquisition of the industrial environment electromagnetic interference intensity and the terminal 5G signal signal-to-noise ratio corresponding to the access request, an electromagnetic interference sensor is used to acquire the industrial environment electromagnetic interference intensity, and a 5G signal acquisition unit is used to acquire the terminal 5G signal signal-to-noise ratio. The electromagnetic interference intensity is the electric field strength, and the 5G signal signal-to-noise ratio is the ratio of the received signal power to the noise power. The electromagnetic interference sensor is used to acquire electromagnetic interference data in the range of 10-100dBμV / m, and the 5G signal acquisition unit is used to perform high-frequency signal sampling to obtain signal-to-noise ratio data.

[0025] This solution focuses on the accuracy and adaptability of parameter acquisition, clearly defining the functions and data ranges of the two core acquisition devices. The electromagnetic interference (EMI) sensor is specifically designed to collect EMI intensity data in industrial environments, limited to the range of 10-100 dBμV / m. This range accurately covers common interference intensities in industrial scenarios; below 10 dBμV / m indicates weak interference, and above 100 dBμV / m indicates extremely strong interference. This allows for comprehensive capture of environmental conditions under different interference scenarios. Furthermore, the physical attribute of interference intensity is clearly defined as electric field strength, avoiding data interpretation errors caused by ambiguous parameter definitions. The 5G signal acquisition unit focuses on acquiring the signal-to-noise ratio (SNR) of the terminal's 5G signal. Data acquisition is achieved through high-frequency signal sampling, and the SNR calculation is based on the ratio of received signal power to noise power. This parameter directly reflects the signal transmission quality between the terminal and the private network. High-frequency sampling reduces the impact of signal fluctuations on SNR calculation, ensuring that the parameter accurately reflects the terminal's communication status. The two devices have clearly defined roles and data attributes. The electromagnetic interference sensor provides an environmental interference benchmark, while the 5G signal acquisition unit provides terminal signal quality data. Together, they provide high-quality, interpretable input parameters for the subsequent dynamic calculation of safety access thresholds, avoiding the problem of invalid parameters caused by the mixed functions of devices and unclear data ranges in traditional acquisition schemes.

[0026] The technical effects of the above embodiments include: clarifying the functions and data range of the acquisition equipment, improving the accuracy of electromagnetic interference intensity and signal-to-noise ratio acquisition, providing reliable data support for subsequent access control, and adapting to the interference and signal characteristics of industrial scenarios.

[0027] When existing technologies dynamically calculate security access thresholds, the impact of terminal security levels is not quantified, and the calculation basis for EMI compensation is vague. This results in a lack of logic in threshold adjustment, making it impossible to accurately match different security requirements and interference scenarios, and easily leading to access judgment bias.

[0028] Based on this, in the step of dynamically calculating the safety access threshold according to the collected industrial environment electromagnetic interference intensity and the terminal 5G signal-to-noise ratio, combined with the terminal safety level, the terminal safety level is divided into five levels: Level 1 corresponds to ordinary monitoring terminals, and Level 5 corresponds to core control terminals. Each level corresponds to a fixed safety factor. The EMI compensation amount is determined according to the difference between the electromagnetic interference intensity and the reference electromagnetic interference intensity. The reference electromagnetic interference intensity is 30dBμV / m. For every 10dBμV / m increase in the difference, the EMI compensation amount increases by 0.2. The safety factor is used to quantify the influence weight of different safety levels on the access threshold.

[0029] This solution starts by quantifying influencing factors and refines the calculation logic of security access thresholds. The core lies in clarifying the quantitative rules for terminal security levels and EMI compensation amounts. First, terminal security levels are divided into 1-5 levels, clearly defining the terminal types corresponding to each level and configuring a fixed security coefficient for each level. This coefficient directly quantifies the influence weight of different security levels on the access threshold. Core control terminals have high security requirements, a large security coefficient, and a higher calculated threshold, ensuring stricter access. Ordinary monitoring terminals have low security requirements, a small security coefficient, and a relatively lenient threshold, avoiding excessive restrictions. Second, the calculation basis for EMI compensation amounts is clarified: using 30dBμV / m as the baseline electromagnetic interference intensity, the compensation amount is adjusted based on the difference between the actual collected electromagnetic interference intensity and the baseline value. For every 10dBμV / m increase in the difference, the compensation amount increases by 0.2. This rule allows the compensation amount to adjust linearly with the interference intensity. In strong interference scenarios, the compensation amount increases, and the threshold rises accordingly, strengthening the requirements for terminal signal quality; in weak interference scenarios, the compensation amount decreases, and the threshold decreases, avoiding false rejection of legitimate terminals. Meanwhile, the calculation process incorporates the electromagnetic interference intensity of the industrial environment and the signal-to-noise ratio of the terminal's 5G signal. The former affects the threshold through EMI compensation, while the latter directly reflects signal quality. Together with the safety factor, they form a three-dimensional threshold calculation logic that considers safety requirements, environmental interference, and signal quality. This ensures that threshold adjustments have a clear quantitative basis, rather than the subjective setting of traditional solutions.

[0030] The technical effects of the above embodiments include: quantifying the impact of terminal security level and EMI compensation on the threshold, making the security access threshold calculation logic clear, accurately matching different security requirements and interference scenarios, and reducing access judgment deviation.

[0031] When existing technologies coordinate the allocation of channel and computing resources, the calculation benchmark for the total channel occupancy rate is unclear, the method for determining the encryption computing power requirements of terminals is ambiguous, and the priority of resource allocation lacks a basis, resulting in resources not being tilted towards terminals with high demand. When multiple terminals are running concurrently, resource congestion and waste are likely to occur.

[0032] Based on this, in the step of collaboratively allocating channel resources and edge network element computing resources based on the calculated security access threshold, combined with the total occupancy rate of 5G private network channels and the encryption computing power requirements of terminals, the total occupancy rate of 5G private network channels is the ratio of the currently occupied channel bandwidth to the total channel bandwidth. The total channel bandwidth is determined according to the 5G private network configuration. The encryption computing power requirements of terminals are determined according to the type of encryption algorithm used by the terminal. Different encryption algorithms correspond to different basic computing power requirements. During collaborative allocation, resources are allocated to terminals with high security access thresholds and low encryption computing power requirements first. The allocation priority is divided into three levels according to the security access threshold and encryption computing power requirements, and each priority level corresponds to a different resource allocation ratio.

[0033] This solution focuses on precise resource allocation, clarifying the core parameters and priority rules for the coordinated allocation of channel and computing resources. The total occupancy rate of a 5G private network channel is defined as the ratio of currently occupied channel bandwidth to the total channel bandwidth. The total channel bandwidth is determined based on the actual configuration of the 5G private network. For example, an industrial private network might have a total bandwidth of 1000Mbps. This parameter directly reflects the degree of channel congestion. A ratio close to 1 indicates channel congestion, requiring strict control over new terminal access; a ratio close to 0 indicates channel idleness, allowing for flexible resource allocation and avoiding misallocation caused by the ambiguous definition of channel congestion in traditional solutions. Secondly, the terminal's encryption computing power requirement is determined based on the encryption algorithm type. Different algorithms correspond to different basic computing power requirements, such as 150 MIPS for AES-256 and 120 MIPS for SM4. This rule quantifies and controls computing power requirements, allowing edge network elements to quickly assess computing power consumption based on the terminal's algorithm type, avoiding resource overload caused by unclear computing power requirements. Then, the resource allocation priority rules are clearly defined: based on security access thresholds and encryption computing power requirements, a three-tier priority system is established. Tier 1 corresponds to terminals with high security access thresholds and low encryption computing power requirements; Tier 2 corresponds to terminals with medium thresholds and medium computing power requirements; and Tier 3 corresponds to terminals with low thresholds and high computing power requirements. Each tier corresponds to a different resource allocation ratio, such as 40% for Tier 1, 35% for Tier 2, and 25% for Tier 3. This ensures that resources are prioritized for terminals with high security requirements and low computing power consumption, balancing security and resource utilization. The entire allocation process is linked to access thresholds, channel occupancy rates, and computing power requirements, forming a multi-dimensional collaborative allocation mechanism to avoid the limitations of single-dimensional allocation.

[0034] The technical effects of the above embodiments include: clarifying the core parameters and priority rules for resource allocation, tilting channel and computing resources toward terminals with high security requirements and low computing power consumption, solving resource congestion and waste when multiple terminals are running concurrently, and improving resource utilization.

[0035] Existing technologies do not establish multi-factor quantitative models when calculating security access thresholds, and cannot accurately correlate terminal security level, signal-to-noise ratio and EMI compensation amount, resulting in a lack of scientific rigor in threshold calculation and an inability to adapt to the access needs of different industrial scenarios.

[0036] Based on this, the process of dynamically calculating the security access threshold satisfies the following formula: in This represents the security access threshold for the i-th terminal. This represents the security level of the i-th terminal. This represents the safety level coefficient and has a value of 1.2. This represents the SNR sensitivity coefficient and has a value of 0.3. This represents the baseline signal-to-noise ratio and is set to 20 dB. This represents the actual signal-to-noise ratio of the i-th terminal. Indicates the amount of EMI compensation. This represents the natural constant and has a value of approximately 2.718.

[0037] This scheme achieves the scientific calculation of safety access thresholds by constructing a quantitative formula. The core lies in clarifying the physical meaning, dimensions, and synergistic logic of each parameter in the formula. In the formula, is the security access threshold for the i-th terminal, which has no unit and ranges from 1 to 10. It is the core indicator for the final access judgment, and the larger the value, the stricter the access requirements. This represents the security level of the i-th terminal, with no unit, ranging from 1 to 5. It directly reflects the terminal's security requirements and is the core control terminal. The value is 5, while that of a regular monitoring terminal is 1; This is a safety level coefficient, without units, with a value of 1.2. It is used to amplify the impact of the safety level on the threshold, making the threshold of high-level terminals significantly higher. This is the SNR sensitivity coefficient, which is dimensionless and takes a value of 0.3. It quantifies the degree of influence of signal-to-noise ratio changes on the threshold. The larger the coefficient, the more obvious the threshold change caused by signal-to-noise ratio fluctuations. The baseline signal-to-noise ratio, in dB, is 20dB, which is the minimum signal quality standard for normal communication in 5G industrial private networks. The actual signal-to-noise ratio of the i-th terminal is expressed in dB, ranging from 5 to 30 dB, reflecting the real-time signal status of the terminal and affected by industrial environmental interference. This is the EMI compensation amount, unitless, ranging from 0.1 to 1.0, calculated based on the difference between the electromagnetic interference intensity and the reference value; the stronger the interference, the greater the compensation amount. is a natural constant, approximately 2.718, dimensionless, used to construct exponential relationships to reduce the signal-to-noise ratio to below 1. The threshold increases exponentially, strengthening access restrictions for terminals with weak signals.

[0038] In the above formula, the quantification of basic security requirements... : The security level of the i-th terminal is determined by the functional importance of the industrial terminal. Level 1 corresponds to ordinary monitoring terminals and Level 5 corresponds to core control terminals. This classification method is in line with the actual scenario of multiple types of terminals coexisting in Huaneng Mengdong 5G private network. This is a safety level coefficient, whose value is derived from multiple rounds of experimental verification. Its purpose is to amplify the threshold differences between different safety levels. If no coefficient is set... The basic threshold difference between Level 5 terminals and Level 1 terminals is only 4, but after setting, the difference expands to 4.8, ensuring that the admission standards for high-security-level terminals are significantly higher than those for low-security-level terminals, and avoiding security risks caused by core terminals and ordinary terminals sharing the same lenient threshold.

[0039] Real-time signal quality adjustment section This section uses an exponential function instead of a nonlinear function because the impact of the 5G signal-to-noise ratio (SNR) on certification reliability in industrial scenarios is nonlinear. When the SNR is lower than the benchmark value, the bit error rate rises sharply, and a linear relationship cannot accurately capture this characteristic. As a natural constant, it forms the mathematical foundation for constructing exponential relationships; The SNR sensitivity coefficient is obtained by fitting the values ​​of electromagnetic interference intensity, signal-to-noise ratio, and bit error rate through a combined experiment.

[0040] Specifically, in the context of strong electromagnetic interference in the open-pit mine in eastern Inner Mongolia, when When the value is 0.3, the SNR decreases from 20dB to 5dB, and the exponential term decreases from... Rise to This increases the threshold from 2 to 91, thus significantly raising the threshold value to accurately match the strict access requirements under strong interference. The baseline signal-to-noise ratio is determined based on the minimum signal quality standard for communication between edge network elements and terminals in 5G industrial private networks. If the signal-to-noise ratio is lower than this value, the stability of terminal communication cannot be guaranteed. The actual signal-to-noise ratio of the i-th terminal is acquired in real time by the EMI-SNR acquisition module, directly reflecting the current signal transmission quality of the terminal.

[0041] Environmental interference compensation section This section is a supplementary design to address the fact that SNR alone cannot fully reflect the risk of environmental interference. Even if two terminals have the same SNR, the probability of subsequent signal fluctuations will be different if the electromagnetic interference intensity of their environments is different.

[0042] The EMI compensation amount is calculated based on an electromagnetic interference intensity of 30 dBμV / m. For every 10 dBμV / m increase, the compensation amount increases by 0.2. This rule is derived from industrial electromagnetic compatibility test data to ensure that the compensation amount reaches 0.6 ((60-30) / 10×0.2) under strong interference environment, further improving the admission threshold and avoiding the problem of certification failure due to subsequent signal mutations even if the current SNR meets the standard.

[0043] The overall technical logic of the formula forms a closed loop: through Establish basic standards for security requirements, and dynamically adjust the impact of signal quality through exponential terms. Supplementing the potential risks of environmental disturbance, the three work together to make It is a technical solution that can match the security importance of the terminal, adapt to signal fluctuations and interference changes in industrial scenarios in real time, and fully support the dynamic calculation of security access thresholds.

[0044] The technical effects of the above embodiments include: establishing a multi-factor quantification model, making the calculation of the security access threshold scientific and controllable, accurately adapting to different security needs, signal quality and interference scenarios, and improving the accuracy of access judgment.

[0045] Existing technologies do not correlate security access thresholds, channel occupancy rates, and computing power requirements when calculating channel-computing power allocation weights. The weight calculation lacks logic and fails to reflect the priority of resource allocation, resulting in resources not being reasonably matched to terminal needs and low resource utilization when multiple terminals are running concurrently.

[0046] Based on this, the resource allocation weights when collaboratively allocating channel resources and edge network element computing resources satisfy the following formula: ; in This represents the channel-computing power allocation weight for the i-th terminal. This represents the weighting coefficient and has a value of 0.8. This indicates the total channel occupancy rate of the 5G private network. This represents the computing power demand sensitivity coefficient, with a value of 0.4. This indicates the maximum computing power requirement of the edge network element, with a value of 200 MIPS. This represents the encryption computing power requirement of the i-th terminal. Technical solution introduction: This solution constructs the resource allocation weight calculation logic through a quantification formula. The core is to integrate three key factors—security access threshold, channel occupancy rate, and computing power requirement—into the weight calculation, ensuring that the weight reflects the terminal's resource priority.

[0047] In the formula, Assign a weight to the channel-computing power of the i-th terminal. The weight is unitless, ranging from 0 to 1. The larger the value, the higher the priority of resource allocation. , is the security access threshold for the i-th terminal, has no unit, ranges from 1 to 10, and is directly related to the terminal's security requirements. The higher the threshold, the larger the base weight value. This is a weighting coefficient, without units, with a value of 0.8. It is used to adjust the overall range of weights to avoid imbalances caused by excessively high or low weights. This represents the total channel occupancy rate of the 5G private network, dimensionless, ranging from 0 to 1, reflecting the degree of channel congestion. The higher the occupancy rate, the higher the denominator. The larger the value, the smaller the weight, thus avoiding excessive resource allocation when the channel is congested; This is a computing power demand sensitivity coefficient, which is dimensionless and takes a value of 0.4. It quantifies the degree of influence of computing power demand on weight. The larger the coefficient, the more significant the weight change caused by the difference in computing power demand. The maximum computing power requirement for edge network elements is expressed in MIPS, with a value of 200 MIPS. This represents the upper limit of computing power for edge network elements, based on common performance configurations of industrial-grade edge network elements. Let represent the encryption computing power requirement of the i-th terminal, in MIPS, ranging from 30 to 150 MIPS, reflecting the terminal's consumption of computing power from edge network elements. During the calculation process... In the formula, the security and channel state coordinated adjustment part : The purpose of introducing the previously calculated security access threshold is to ensure that terminals with high security levels have priority in obtaining resources, and that core control terminals can obtain higher weight through the high value of this part even when the channel is slightly congested. These are weighting coefficients, and their function is to... The value range is adjusted to a reasonable range suitable for resource allocation to avoid [further issues]. An excessively large weight results in the weight exceeding the allocatable range; The total channel occupancy rate of the 5G private network directly reflects the degree of channel congestion. It is calculated as the current occupied channel bandwidth divided by the total channel bandwidth. The total channel bandwidth is determined based on the configuration of the Inner Mongolia East 5G private network and is typically 1000Mbps. The denominator in the formula uses... This is to implement the logic that the more congested the channel, the smaller the weight adjustment coefficient; when the channel is idle... When the denominator is 1, this part has the largest value; when the channel is severely congested... When the denominator is 1.8, this part of the value is reduced to 5 / 9 of the original value, which effectively reduces the resource allocation of low-security-level terminals and alleviates channel pressure.

[0048] Terminal computing power demand adjustment section This section addresses the issue of encryption latency caused by fluctuations in edge network element computing power, quantifying the impact of terminal computing power demand on resource allocation through an exponential relationship.

[0049] in, To determine the maximum computing power requirement of edge network elements, the peak computing power of domestic C86 architecture edge network elements is used. The peak computing power of this architecture in industrial scenarios is typically 200-300 MIPS. 200 MIPS is chosen to ensure the maximum processing capacity of the covered network elements. The encryption computing power requirement of the i-th terminal is determined based on the encryption algorithm used by the terminal. For example, the AES-256 algorithm requires 150 MIPS, and the SM4 algorithm requires 120 MIPS, which directly reflects the terminal's consumption of edge network element computing power. The computing power demand sensitivity coefficient is obtained by fitting the computing power demand and encryption latency experiments. When increasing from 30 MIPS to 150 MIPS The exponential term decreased from 170 to 50. Rise to This part decreases from 1 to approximately 1 (1-2×10^{-9}), which seems like a small difference, but in fact it applies to near-zero values. High-performance computing terminals, such as , exponent term This part is reduced to 0.9997, and the weight is reduced accordingly to avoid overloading the edge network element computing power due to multiple high computing power terminals accessing at the same time.

[0050] The technical effects of the above embodiments include: establishing a multi-factor weight calculation model so that the resource allocation weight can reflect the terminal security requirements, channel status and computing power consumption, improve the rationality of resource allocation priority, and improve the resource utilization rate when multiple terminals are running concurrently.

[0051] When existing technologies correct the effective success rate of secure access, they do not correlate resource allocation weights, encryption latency, and security access thresholds. The correction logic is vague and cannot quantify the impact of each factor on the success rate, resulting in inaccurate success rate judgments and failing to guarantee the security and real-time performance of access.

[0052] Based on this, the process of improving the effective success rate of secure terminal access satisfies the following two formulas: , in This represents the effective success rate correction factor. This represents the weight sensitivity coefficient and has a value of 0.5. This represents the minimum resource allocation weight, with a value of 0.2. This represents the encryption delay impact coefficient and has a value of 0.6. This represents the actual encryption delay of the i-th terminal. This indicates the maximum allowed encryption delay, with a value of 15ms. This indicates the maximum admission threshold, with a value of 10. This represents the basic access success rate and has a value of 0.9. This represents the successful secure access rate of the i-th terminal.

[0053] This scheme constructs a success rate correction logic using a dual-formula approach. The core of this approach is to quantify the impact of resource allocation weights, encryption latency, and security access thresholds on the effective success rate, ensuring accurate success rate assessment. The first formula calculates the correction coefficient. Unitless, 0-1, is the core of success rate correction; This is a weight sensitivity coefficient, dimensionless, 0.5, which quantifies the impact of resource weights on the correction coefficient. The larger the coefficient, the greater the impact of weight differences. The more obvious the change; Assign weights to resources, with values ​​ranging from 0 to 1. The minimum resource weight is set to 0.2. Positive influence is only applied when the weight is higher than the minimum value. The higher the weight, The closer to 1, The larger; The encryption latency impact factor is 0.6, representing the effect of quantization latency on... The higher the coefficient, the greater the penalty for exceeding the delay limit. The more significant the decrease; This represents the actual encryption delay, measured in milliseconds (ms), and ranges from 10 to 50 ms. The maximum allowable delay is set at 15ms, which meets the real-time requirements of industrial control. This reflects the degree of delay exceeding the limit; the higher the delay, the larger the value. The smaller, The lower; This is a security access threshold, with a value ranging from 1 to 10. The maximum threshold is set to 10. Ensure high threshold terminals The foundation is higher. The second formula. Calculate the final effective success rate. The base success rate, with a value of 0.9, represents the access success rate under conditions of no interference and no congestion. The actual success rate was obtained after correction.

[0054] Resource allocation effectiveness adjustment section This section addresses the issue of insufficient resource allocation leading to access failures by quantifying the role of resource weights in ensuring success rates.

[0055] in, The resource allocation weights calculated above directly reflect the sufficiency of resources obtained by the terminal. This value is set to allocate the minimum resource weight to avoid terminals with excessively low weights. A negative value results in the exponent term being negative. If it is too large, then this part will become negative; This is the weight sensitivity coefficient, whose value is derived from experimental data on resource weights and access success rates. hour, exponent term This part is 0.296; when hour, exponent term When this part is 0, the correction coefficient decreases accordingly, accurately reflecting the actual situation of a sharp drop in success rate when resources are insufficient.

[0056] Encryption delay risk penalty section This section is a key design feature addressing the real-time requirements of industrial control. When industrial terminals connect, excessive encryption delays can cause control command transmission timeouts, rendering successful authentication meaningless. Specifically, The actual encryption delay of the i-th terminal is collected in real time by the computing power monitoring unit of the edge network element; The maximum permissible encryption latency is determined based on the maximum tolerable latency for industrial control equipment access authentication. This is the encryption delay impact factor, which sets the strength of the delay penalty. hour, This part is 1 - 0.6 × 1 = 0.4; when hour, This part is 1-0.6×2=-0.2, and the correction coefficient is negative, so the access failure is directly determined, avoiding the risk of control failure caused by terminal access with excessive delay.

[0057] Security Basic Support This section integrates the impact of security access thresholds into the success rate correction process, preventing terminals with sufficient resources and meeting latency requirements but low security levels from achieving excessively high success rates. The maximum admission threshold is The theoretical maximum value; when When the value is 1, this part is 1, providing the highest safety basis for the correction factor; when... At that time, this part is 0.1. Even if resources are sufficient and latency meets the standard, the correction coefficient will be limited to a low range, reflecting the actual situation that there are still security risks after low-security level terminals are connected.

[0058] Throughout the process, resource weighting ensures reasonable allocation, encryption latency ensures real-time performance, and security thresholds ensure security. These three factors work together to correct the success rate, avoiding the bias of traditional methods that rely on a single factor to determine success rate. The technical effects of the above embodiments include: quantifying the impact of multiple factors on the effective success rate, making the success rate correction logic clear, improving the accuracy of success rate judgment, ensuring the security and real-time performance of access, and adapting to the needs of industrial scenarios.

[0059] When collecting edge network element encryption latency data using existing technologies, the collection frequency does not match the terminal access frequency, and the correlation between computing power utilization and latency is unclear. This results in latency data failing to reflect the computing power status in real time, affecting the accuracy of success rate correction.

[0060] Based on this, in the step of collecting the encryption delay of terminal data by edge network elements, the encryption delay is collected in real time by the computing power monitoring unit of the edge network element. The computing power monitoring unit is electrically connected to the processor of the edge network element, and the collection frequency is consistent with the frequency of the terminal access request. The encryption delay increases with the increase of the computing power utilization rate of the edge network element. The correlation between computing power utilization rate and encryption delay is determined according to the hardware performance of the edge network element. Edge network elements with different hardware performance correspond to different computing power utilization rate-encryption delay change curves.

[0061] This solution focuses on the real-time performance and relevance of encrypted latency data collection, clearly defining the collection method, frequency, and correlation rules with computing power utilization. First, the collection hardware utilizes the computing power monitoring unit of the edge network element. This unit is electrically connected to the edge network element processor, directly acquiring the processor's encryption computation time. This avoids data deviations caused by signal transmission delays from external collection devices, ensuring that the latency data accurately reflects the real-time computing power processing efficiency of the edge network element. Second, the collection frequency is consistent with the frequency at which terminal access requests are initiated. This setting synchronizes latency collection with terminal access. When a terminal initiates an access request, the encryption latency at that moment is collected synchronously, ensuring that the latency data accurately matches the computing power requirements of the currently accessing terminal. This avoids resource waste due to excessively high collection frequencies or data lag due to excessively low frequencies, resolving the problem of disconnect between traditional collection and access frequencies. Finally, the correlation between encryption latency and computing power utilization is clarified: latency increases with computing power utilization, and this correlation is determined based on the hardware performance of edge network elements. Edge network elements with different hardware, due to variations in processor clock speed and number of cores, correspond to different computing power utilization-encryption latency change curves. This rule ensures that latency data not only reflects the current computing power status but also allows for prediction of latency change trends in conjunction with hardware performance, providing a reference for subsequent resource allocation adjustments and avoiding data analysis biases caused by only collecting latency data while ignoring hardware differences. The entire data collection process revolves around real-time matching of access requirements and correlation with hardware performance, ensuring the validity and usability of latency data.

[0062] The technical effects of the above embodiments include: realizing real-time acquisition of encryption latency, clarifying the correlation between latency and computing power utilization, improving the accuracy and availability of latency data, providing accurate input for success rate correction, and adapting to edge network elements with different hardware performance.

[0063] In existing 5G industrial internet security access control devices, the modules are divided in a disorderly manner, the connection relationship between modules is unclear, and there is functional overlap or lack, making it impossible to achieve multi-factor collaborative control, which results in the device being unable to adapt to the security access requirements of industrial scenarios.

[0064] Based on this, this embodiment provides a 5G industrial internet secure access control device, including: a communication module for receiving 5G industrial terminal access requests, an EMI-SNR acquisition module, an access threshold calculation module, a channel-computing power allocation module, a success rate correction module, and a security authentication module. The EMI-SNR acquisition module, access threshold calculation module, channel-computing power allocation module, success rate correction module, and security authentication module are electrically connected sequentially. The communication module is electrically connected to both the access threshold calculation module and the security authentication module. The EMI-SNR acquisition module is used to collect the electromagnetic interference intensity of the industrial environment and the signal-to-noise ratio of the terminal's 5G signal in real time. The access threshold calculation module is used to dynamically calculate a secure access threshold based on the collected parameters and the terminal's security level. The channel-computing power allocation module is used to collaboratively allocate channel resources and edge network element computing power resources based on the secure access threshold. The success rate correction module is used to correct the effective access success rate based on encryption delay. The security authentication module is used to determine whether to allow terminal access based on the corrected success rate.

[0065] This scheme takes modular collaboration as its core, clearly defines the modular composition, connection relationships and functional division of the device, and ensures that each module forms a closed-loop control.

[0066] The module division follows the principles of single function and orderly coordination, setting up five functional modules: EMI-SNR acquisition module, access threshold calculation module, channel-computing power allocation module, success rate correction module, and security authentication module, in conjunction with the existing communication module. The module connections are clear: the EMI-SNR acquisition module, access threshold calculation module, channel-computing power allocation module, success rate correction module, and security authentication module are electrically connected sequentially, forming a unidirectional data flow mainline—the acquisition module transmits electromagnetic interference intensity and signal-to-noise ratio to the calculation module, the calculation module outputs the security access threshold to the allocation module, the allocation module outputs resource weights to the correction module, and the correction module outputs the effective success rate to the authentication module; simultaneously, the communication module is electrically connected to the access threshold calculation module and the security authentication module respectively, transmitting terminal access requests and terminal security levels to the calculation module on one hand, and feeding back the access results from the authentication module to the terminal on the other, forming a two-way data interaction, ensuring a clear data transmission path between modules and avoiding data transmission errors caused by the chaotic module connections of traditional devices.

[0067] Each module has a precise functional positioning: the EMI-SNR acquisition module focuses on parameter acquisition, the admission threshold calculation module focuses on dynamic threshold calculation, the channel-computing power allocation module focuses on resource collaborative allocation, the success rate correction module focuses on success rate quantitative correction, and the security authentication module focuses on the final access judgment. Each module has a single function and works closely with other modules to achieve multi-factor collaborative control, avoiding the control failure problem caused by the mixed functions of traditional devices.

[0068] The technical effects of the above embodiments include: clarifying the composition, connection relationship and function of the device modules, realizing multi-module collaborative control, avoiding functional overlap or lack, enabling the device to adapt to the security access requirements of industrial scenarios, and improving the stability and reliability of access control.

[0069] The internal structure of each module in the existing 5G industrial internet security access control device is vague, and the core components are missing or their functions are unclear. This makes it impossible to guarantee the realization of module functions, resulting in insufficient overall device performance and an inability to meet the high reliability requirements of industrial scenarios.

[0070] Based on this, the EMI-SNR acquisition module includes an electromagnetic interference sensor and a 5G signal analyzer, with the output of the electromagnetic interference sensor electrically connected to the input of the 5G signal analyzer; the access threshold calculation module includes a domestically produced C86 architecture processor and a memory, with the memory storing a program for calculating the security access threshold, and the processor calling the program to perform the calculation operation; the security authentication module integrates an SM4 encryption chip, which is electrically connected to the communication module and used to encrypt and authenticate terminal access data; the channel-computing power allocation module includes a 5G channel scheduling unit and a computing power allocation unit, with the 5G channel scheduling unit supporting FlexE slicing technology to achieve flexible allocation of channel resources, and the computing power allocation unit electrically connected to the IPMI interface of the edge network element to obtain edge network element computing power status data.

[0071] This solution focuses on the internal structure and core components of the modules, clarifies the hardware composition and component collaboration logic of each functional module, and ensures that the module functions are feasible and the performance is reliable.

[0072] The EMI-SNR acquisition module consists of an electromagnetic interference sensor and a 5G signal analyzer, which are electrically connected. The electromagnetic interference sensor collects the intensity of electromagnetic interference in the industrial environment, and the output terminal transmits the analog signal to the input terminal of the 5G signal analyzer. After the analyzer performs digital processing on the signal, it calculates and outputs the signal-to-noise ratio of the terminal's 5G signal. The components have clear division of labor, ensuring the digitalization and accuracy of the acquisition parameters and avoiding signal distortion caused by pure analog acquisition.

[0073] The access threshold calculation module adopts a domestically produced C86 architecture processor and memory. The memory stores the threshold calculation program, and the processor calls the program to receive parameters from the acquisition module and the terminal security level from the communication module. It then performs the calculation and outputs the security access threshold. The hardware and software work together to ensure the real-time performance of the threshold calculation and compatibility with domestic technology. Next, the security authentication module integrates an SM4 encryption chip, which is electrically connected to the communication module. This chip receives terminal access data transmitted by the communication module and encrypts and authenticates the data using the SM4 algorithm to prevent leakage or tampering during data transmission, ensuring authentication security. The channel-computing power allocation module consists of a 5G channel scheduling unit and a computing power allocation unit. The channel scheduling unit supports FlexE slicing technology, which can divide the 5G private network channel into multiple slices, enabling flexible allocation of channel resources. The computing power allocation unit is electrically connected to the IPMI interface of the edge network element, acquiring status data such as the computing power utilization rate and remaining computing power of the edge network element, providing computing power input for resource allocation. The two units work together to achieve the linkage allocation of channels and computing power. The core components of each module are clearly defined and adapted to industrial-grade performance and domestic requirements, ensuring the overall reliability of the device.

[0074] The technical effects of the above embodiments include: clarifying the internal structure and core components of each module, ensuring the realization of module functions, improving the overall performance and safety of the device, adapting to the high reliability and localization requirements of industrial scenarios, and avoiding functional failures caused by missing components.

[0075] The embodiments and / or implementation methods described above are merely preferred embodiments and / or implementation methods for implementing the technology of the present invention, and are not intended to limit the implementation methods of the technology of the present invention in any way. Any person skilled in the art can make some modifications or alterations to other equivalent embodiments without departing from the scope of the technical means disclosed in the content of the present invention, but they should still be regarded as the technology or embodiments that are substantially the same as the present invention.

[0076] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this application, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A 5G industrial internet security access control method, characterized in that, The method comprises the following steps: 5G industrial terminal initiates an access request to an edge network element, and collects the electromagnetic interference intensity of the industrial environment corresponding to the access request and the signal-to-noise ratio of the terminal 5G signal in real time; According to the collected electromagnetic interference intensity of the industrial environment and the signal-to-noise ratio of the terminal 5G signal, the safety access threshold is dynamically calculated in combination with the terminal security level; Based on the calculated safety access threshold, in combination with the total occupation rate of the 5G private network channel and the terminal encryption algorithm requirement, the channel resources and edge network element algorithm resources are cooperatively allocated; Collect the encryption delay of the terminal data by the edge network element, and correct the effective success rate of the terminal safety access according to the resource weight and the encryption delay of the cooperatively allocated resources; If the corrected safety access effective success rate reaches the preset threshold 0.8, the terminal is allowed to access the 5G industrial internet, otherwise the steps of dynamically calculating the safety access threshold and cooperatively allocating resources are re-executed. 2.The 5G industrial internet security access control method of claim 1, wherein, In the step of collecting the electromagnetic interference intensity of the industrial environment corresponding to the access request and the signal-to-noise ratio of the terminal 5G signal in real time, the electromagnetic interference sensor is used to collect the electromagnetic interference intensity of the industrial environment, and the 5G signal collection unit is used to collect the signal-to-noise ratio of the terminal 5G signal, the electromagnetic interference intensity is the electric field intensity, the signal-to-noise ratio of the 5G signal is the ratio of the received signal power to the noise power, the electromagnetic interference sensor is used to obtain electromagnetic interference data in the range of 10-100dBμV / m, and the 5G signal collection unit is used to realize high-frequency signal sampling to obtain signal-to-noise ratio data. 3.The 5G industrial internet security access control method of claim 1, wherein, In the step of dynamically calculating the safety access threshold according to the collected electromagnetic interference intensity of the industrial environment and the signal-to-noise ratio of the terminal 5G signal in combination with the terminal security level, the terminal security level is divided into five levels, the first level corresponds to ordinary monitoring terminal and the fifth level corresponds to core control terminal, each level corresponds to a fixed safety coefficient, the EMI compensation amount is determined according to the difference between the electromagnetic interference intensity and the reference electromagnetic interference intensity, the reference electromagnetic interference intensity is 30dBμV / m, and the EMI compensation amount increases by 0.2 for every 10dBμV / m increase in the difference, and the safety coefficient is used to quantify the influence weight of different safety levels on the access threshold. 4.The 5G industrial internet security access control method of claim 1, wherein, In the step of cooperatively allocating channel resources and edge network element algorithm resources based on the calculated safety access threshold in combination with the total occupation rate of the 5G private network channel and the terminal encryption algorithm requirement, the total occupation rate of the 5G private network channel is the ratio of the current occupied channel bandwidth to the total channel bandwidth, the total channel bandwidth is determined according to the 5G private network configuration, the terminal encryption algorithm requirement is determined according to the type of encryption algorithm used by the terminal, different encryption algorithms correspond to different basic algorithm requirement values, and when cooperatively allocating resources, the terminal with high safety access threshold and low encryption algorithm requirement is preferentially allocated resources, the allocation priority is divided into three levels according to the safety access threshold and the encryption algorithm requirement, and each level of priority corresponds to a different resource allocation proportion.

5. The 5G industrial internet security access control method of claim 1, wherein, The process of dynamically calculating the safety access threshold satisfies the following formula: ; Wherein T i represents the security access threshold of the i-th terminal, SL i represents the security level of the i-th terminal, K1 represents the security level coefficient and takes the value of 1.2, a represents the SNR sensitivity coefficient and takes the value of 0.3, SNR0 represents the reference signal-to-noise ratio and takes the value of 20dB, SNR i represents the actual signal-to-noise ratio of the i-th terminal, △T EMI represents the EMI compensation amount, e represents the natural constant and takes the value of 2.

718.

6. The 5G industrial internet security access control method of claim 5, wherein, The resource allocation weight when cooperatively allocating channel resources and edge network element algorithm resources satisfies the following formula: ； wherein W i represents the channel-computing power allocation weight of the i-th terminal, K2 represents the weight coefficient and takes a value of 0.8, CO total represents the total channel occupation rate of the 5G private network, b represents the computing power demand sensitivity coefficient and takes a value of 0.4, CR max represents the maximum computing power demand of the edge network element and takes a value of 200MIPS, CR i represents the encryption computing power demand of the i-th terminal.

7. The 5G industrial internet security access control method of claim 6, wherein, The process of correcting the effective success rate of the terminal safety access satisfies the following two formulas: ， wherein η represents an effective success rate correction coefficient, c represents a weight sensitivity coefficient and takes a value of 0.5, W min represents a minimum resource allocation weight and takes a value of 0.2, f represents an encryption delay influence coefficient and takes a value of 0.6, D enci represents an actual encryption delay of the i-th terminal, represents a maximum allowed encryption delay and takes a value of 15 ms, T max represents a maximum admission threshold and takes a value of 10, P0represents a basic access success rate and takes a value of 0.9, P i represents a security access effective success rate of the i-th terminal. 8.The 5G industrial internet security access control method of claim 1, wherein, In the step of collecting the encryption delay of the terminal data by the edge network element, the encryption delay is collected in real time by a computing power monitoring unit of the edge network element, the computing power monitoring unit is electrically connected with a processor of the edge network element, the collection frequency is consistent with the initiation frequency of the terminal access request, the encryption delay increases with the increase of the utilization rate of the computing power of the edge network element, the correlation between the utilization rate of the computing power and the encryption delay is determined according to the hardware performance of the edge network element, and different hardware performance of the edge network element corresponds to different computing power utilization rate-encryption delay change curves. 9.A 5G Industrial Internet of Things security access control apparatus, applied to the 5G Industrial Internet of Things security access control method of any one of claims 1-8, comprising: The communication module for receiving the 5G industrial terminal access request, characterized in that, further comprising an EMI-SNR acquisition module, an admission threshold calculation module, a channel-computing power allocation module, a success rate correction module and a security authentication module, the EMI-SNR acquisition module, the admission threshold calculation module, the channel-computing power allocation module, the success rate correction module and the security authentication module are electrically connected in sequence, and the communication module is electrically connected with the admission threshold calculation module and the security authentication module respectively; the EMI-SNR acquisition module is used for collecting the electromagnetic interference intensity of the industrial environment and the 5G signal signal-to-noise ratio in real time; the admission threshold calculation module is used for dynamically calculating the security admission threshold according to the collected parameters combined with the terminal security level; the channel-computing power allocation module is used for allocating channel resources and edge network element computing power resources based on the security admission threshold; the success rate correction module is used for correcting the effective success rate of access according to the encryption delay; and the security authentication module is used for judging whether to allow the terminal to access according to the corrected success rate.

10. The 5G Industrial Internet of Things security access control apparatus of claim 9, wherein, The EMI-SNR acquisition module includes an electromagnetic interference sensor and a 5G signal analyzer, the output end of the electromagnetic interference sensor is electrically connected with the input end of the 5G signal analyzer; the admission threshold calculation module includes a domestic C86 architecture processor and a memory, the memory stores a program for calculating the security admission threshold, and the processor calls the program to perform the calculation operation; the security authentication module integrates an SM4 encryption chip, the SM4 encryption chip is electrically connected with the communication module, and is used for encrypting and authenticating the terminal access data; the channel-computing power allocation module includes a 5G channel scheduling unit and a computing power allocation unit, the 5G channel scheduling unit supports FlexE slicing technology to realize flexible division of channel resources, and the computing power allocation unit is electrically connected with an IPMI interface of the edge network element to obtain the edge network element computing power state data.

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