Dynamically adjustable enterprise data security risk management and control system

Abstract

The invention discloses a dynamically adjustable enterprise data security risk management and control system, and belongs to the technical field of enterprise data security risk management and control. Comprising a data acquisition module, a risk assessment and weight adjustment module and a management and control measure adjustment module, the risk evaluation and weight adjustment module obtains the adjusted weight according to the risk value, the risk early warning value and the sub-weight matched with the sub-factor with the maximum change before and after the key change influence, and the management and control measure adjustment module executes the risk management and control of the sub-factor matched with the adjusted weight according to the adjusted weight. According to the enterprise data security risk management and control method, firstly, sub-weights matched with multiple sub-factors are comprehensively considered, then, the enterprise data security risk is comprehensively evaluated, secondly, a dynamic adjustment concept in the field of digital information transmission is introduced into an enterprise data security risk management and control system, and dynamic risk evaluation and weight adjustment are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise data security risk control, and particularly to a dynamically adjustable enterprise data security risk control system. Background Art

[0002] In today's digital age, the transmission of enterprise data information faces numerous security risks. These risk factors are intertwined and in a dynamic state of change, posing a huge challenge to the data security of enterprises.

[0003] Some existing data security risk control systems often adopt static configurations and thus cannot reflect the dynamic changes of enterprise data security risks in real time. During the process of data information transmission, key parameters will constantly change, and some existing systems lack effective monitoring and response mechanisms for these changes in key parameters. In addition, once the risk factor weights of existing systems are set, it is difficult to adjust them according to the actual risk situation, making it difficult for enterprises to adapt to complex and changeable production environments and data changes.

[0004] Therefore, it is of great practical significance to develop a dynamically adjustable enterprise data security risk control system. This system draws on relevant technologies and concepts in the field of digital information transmission and realizes all-round, real-time, and flexible control of enterprise data security risks through effective data collection, transmission, processing, and dynamic adjustment. Summary of the Invention

[0005] The technical problem to be solved by the present invention is that there are disadvantages in the prior art such as the lack of a dynamic evaluation mechanism, difficulty in adapting to data changes, and inflexible weight adjustment. For this reason, we propose a dynamically adjustable enterprise data security risk control system.

[0006] The technical solution mainly is: a dynamically adjustable enterprise data security risk control system, including a data collection module, a risk assessment and weight adjustment module, and a control measure adjustment module; The data collection module: obtains the risk factor information and key change information collected by each collection sub-module; The risk assessment and weight adjustment module: receives the risk factor information and the key change information transmitted by the data collection module; Obtains risk impact weight information according to the risk factor information; Obtains a basic risk value according to the risk factor information and the risk impact weight information; Obtains the risk value under the influence of key changes according to the basic risk value and the key change information; Extracts a risk warning value preset and stored in the risk assessment and weight adjustment module; Obtain the sub - weight in the risk impact weight information matched by the sub - factor with the largest change before and after according to the changes before and after of the sub - factors in the risk factor information. Obtain the adjusted weight according to the risk value under the influence of the key change, the risk warning value, and the sub - weight matched by the sub - factor with the largest change before and after. The control measure adjustment module: receives and executes the adjusted weight transmitted by the risk assessment and weight adjustment module. Execute the risk control of the sub - factor matched with it according to the adjusted weight.

[0007] Preferably, the acquisition sub - module includes a fault monitoring device, a network traffic monitoring device, a network performance monitoring tool, a network connection monitoring device, a system operation log, and the total factor acquisition amounts matched with the fault monitoring device, the network traffic monitoring device, the network performance monitoring tool, the network connection monitoring device, and the system operation log. The sub - factors of the risk factor information include the number of equipment failures, the number of abnormal traffic, the number of data transmission delays, the number of network interruptions, and the number of human errors. The fault monitoring device is used to obtain the number of equipment failures. The network traffic monitoring device is used to obtain the number of abnormal traffic. The network performance monitoring tool is used to obtain the number of data transmission delays. The network connection monitoring device is used to obtain the number of network interruptions. The system operation log is used to obtain the number of human errors.

[0008] Preferably, the risk impact weight information includes a first weight, a second weight, a third weight, a fourth weight, and a fifth weight. Multiply the number of equipment failures by the first weight to obtain the first risk that causes data loss, service interruption, and affects the normal storage and transmission of enterprise data. Multiply the number of abnormal traffic by the second weight to obtain the second risk of being attacked by the network, interfering with the normal data transmission of the enterprise, and even causing data leakage. Multiply the number of data transmission delays by the third weight to obtain the third risk that affects the real - time performance of the service, thereby causing untimely data processing and indicating potential problems in the network. Multiply the number of network interruptions by the fourth weight to obtain the fourth risk that makes enterprise data unable to be normally transmitted and shared, thereby seriously affecting business continuity. Multiply the number of human errors by the fifth weight to obtain the fifth risk of directly causing data loss and leakage due to human errors. Add the first risk, the second risk, the third risk, the fourth risk, and the fifth risk to obtain a comprehensive basic risk; Divide the comprehensive basic risk by the total factor collection quantity to obtain a basic risk value; Wherein, the sum of the first weight, the second weight, the third weight, the fourth weight, and the fifth weight is 1.

[0009] Preferably, the key change information includes a change amount before and after and a historical average change amount; According to the positive or negative value of the change amount before and after, the method for obtaining the risk value under the influence of the key change is as follows: When the change amount before and after is negative, directly obtain the risk value under the influence of the key change in the case of a negative value according to the basic risk value; When the change amount before and after is positive, obtain a relative change influence amount according to the change amount before and after and the historical average change amount; According to the basic risk value and the relative change influence amount, obtain the risk value under the influence of the key change in the case of a positive value.

[0010] Preferably, both the change amount before and after and the historical average change amount are divided into two key factors of device temperature and data transmission rate; When the key factor is the device temperature: The change amount before and after is the temperature change amount; The historical average change amount is the average temperature change amount; When the key factor is the data transmission rate: The change amount before and after is the transmission rate change amount; The historical average change amount is the average transmission rate change amount; Wherein, during the initial control, one of the key factors is arbitrarily selected from the device temperature and the data transmission rate through manual setting.

[0011] Preferably, the specific method for obtaining the sub - weight matched with the sub - factor with the largest change before and after based on the change before and after of the sub - factors in the risk factor information is as follows: Obtain the current and previous numbers of device failures, traffic anomaly times, data transmission delay times, network interruption times, and human error times from the risk assessment and weight adjustment module; Divide the current number of device failures by the previous number of device failures to obtain a first change ratio; Divide the current number of traffic anomalies by the previous number of traffic anomalies to obtain a second change ratio; Divide the current number of data transmission delays by the previous number of data transmission delays to obtain a third change ratio; Divide the current number of network interruptions by the previous number of network interruptions to obtain a fourth change ratio; Divide the current number of human errors by the previous number of human errors to obtain a fifth change ratio; Intelligently select the sub-weight with the largest change ratio from the first change ratio, the second change ratio, the third change ratio, the fourth change ratio, and the fifth change ratio.

[0012] Preferably, after the initial control, the key factors are intelligently selected according to the sub-weight with the largest change ratio, specifically as follows: If the largest change ratio is the first change ratio, then the key factor is intelligently selected as the device temperature; If the largest change ratio is the second change ratio, the third change ratio, and the fourth change ratio, then the key factor is intelligently selected as the data transmission rate.

[0013] Preferably, based on the risk value and the risk warning value under the influence of the key change, obtain a weight adjustment amount representing the deviation ratio of the current risk relative to the threshold, so as to more intuitively reflect the degree of risk exceeding and being lower than the threshold; Based on the sub-weight with the largest change ratio and the weight adjustment amount, obtain the adjusted weight.

[0014] The technical effects and advantages of the present invention: In the present invention, the system can collect the sub-factors and the front and back change amounts of the key factors measured in real time for each risk factor through the collection of the data collection module and the processing of the risk assessment and weight adjustment module, and combine the pre-set risk impact weight information and the historical average change amount to obtain the basic risk value and the risk value under the influence of the key change, which enables the system to reflect the dynamic change of the enterprise data security risk in real time and discover potential risks in time.

[0015] In addition, the system can automatically select the key change information according to the change of the key factor and affect the risk value under the influence of the key change in real time to adapt to the changes in the internal and external environment of the enterprise, so as to accurately evaluate the risk and improve the adaptability and flexibility of the system.

[0016] In the present invention, the process of obtaining the adjusted weight provides a flexible weight adjustment mechanism. Specifically, the system determines the sub-weight matching the sub-factor to be adjusted by comparing the front and back changes of the sub-factors, and adjusts the sub-weight with the largest change ratio according to the relationship between the risk value under the influence of the key change and the risk warning value, which enables the system to more accurately control the main risk factors, thereby improving the efficiency and effect of risk control. Brief Description of the Drawings

[0017] Figure 1 is the risk control flow chart of the enterprise data security risk control system of this enterprise; Figure 2 is the acquisition schematic diagram of the acquisition sub-module in the present invention. Detailed Description of the Preferred Embodiment

[0018] Now, the present invention will be further described in detail with reference to the accompanying drawings and preferred embodiments.

[0019] Refer to Figure 1 and Figure 2 As shown, the present invention provides a technical solution: a dynamically adjustable enterprise data security risk control system, including a data acquisition module, a risk assessment and weight adjustment module, and a control measure adjustment module; Data acquisition module: Obtain the risk factor information and key change information collected by each acquisition sub-module; The acquisition sub-module includes a fault monitoring device, a network traffic monitoring device, a network performance monitoring tool, a network connection monitoring device, a system operation log, and a total factor acquisition volume matching the fault monitoring device, the network traffic monitoring device, the network performance monitoring tool, the network connection monitoring device, and the system operation log; Risk assessment and weight adjustment module: Receive the risk factor information and key change information transmitted by the data acquisition module; According to the risk factor information, obtain the risk impact weight information; According to the risk factor information and the risk impact weight information, obtain the basic risk value; According to the basic risk value and the key change information, obtain the risk value under the influence of the key change; Extract the pre-set risk warning value stored in the risk assessment and weight adjustment module; According to the front-back change of the sub-factors in the risk factor information, obtain the sub-weight in the risk impact weight information matching the sub-factor with the largest front-back change; According to the risk value under the influence of the key change, the risk warning value, and the sub-weight matching the sub-factor with the largest front-back change, obtain the adjusted weight; Control measure adjustment module: Receive and execute the adjusted weight transmitted by the risk assessment and weight adjustment module; According to the adjusted weight, execute the risk control of the sub-factors matching it.

[0020] In this embodiment: First, for each acquisition sub-module, the number of device failures can be counted by the built-in fault monitoring device of the device, and this device will record the number of times of fault occurrence when the device fails; The number of abnormal traffic is counted by network traffic monitoring devices, which monitor network traffic in real time and record the number when abnormal fluctuations occur; The number of data transmission delays can be counted by network performance monitoring tools, which can monitor the data transmission delay in real time; The number of network interruptions is counted by network connection monitoring devices and recorded when the network connection is interrupted; The number of human errors can be recorded through the system operation log and counted when operators make misoperations.

[0021] Secondly, the risk assessment and weight adjustment module obtains the basic risk value by collecting comprehensive multi-factors through each acquisition sub-module, providing the initial risk situation for the system; Based on the basic risk value, the risk assessment is dynamically adjusted in combination with the key change information to obtain the risk value under the influence of key changes, enhancing the system's response ability to risk changes; The final adjustment and control are completed based on the sub-weights matched by the sub-factors with the largest changes before and after, enabling the system to accurately focus on the main risk factors; The obtained basic risk value, the risk value under the influence of key changes, and the risk warning value cooperate with each other. Through the data acquisition, analysis, decision-making, and control modules and related devices, a closed-loop management is formed, realizing the comprehensive, real-time, and accurate control of enterprise data security risks, and improving the adaptability and effectiveness of the system.

[0022] Refer to Figure 1 and Figure 2 As shown, in this implementation plan: the sub-factors of risk factor information include the number of equipment failures, the number of abnormal traffic, the number of data transmission delays, the number of network interruptions, and the number of human errors; The fault monitoring device is used to obtain the number of equipment failures; The network traffic monitoring device is used to obtain the number of abnormal traffic; The network performance monitoring tool is used to obtain the number of data transmission delays; The network connection monitoring device is used to obtain the number of network interruptions; The system operation log is used to obtain the number of human errors; The risk impact weight information includes the first weight, the second weight, the third weight, the fourth weight, and the fifth weight; Multiply the number of equipment failures by the first weight to obtain the first risk that causes data loss, business interruption, and affects the normal storage and transmission of enterprise data; Multiply the number of abnormal traffic by the second weight to obtain the second risk of being attacked by the network, interfering with the normal data transmission of the enterprise, and even causing data leakage; Multiply the number of data transmission delays by the third weight to obtain the real-time performance affecting the business, thereby causing untimely data processing and indicating the third risk of potential problems in the network; Multiply the number of network interruptions by the fourth weight to obtain the fourth risk that prevents the normal transmission and sharing of enterprise data, thereby seriously affecting business continuity; Multiply the number of human errors by the fifth weight to obtain the fifth risk of direct data loss and leakage due to human errors; Add the first risk, the second risk, the third risk, the fourth risk, and the fifth risk to obtain the comprehensive basic risk; Divide the comprehensive basic risk by the total factor collection volume to obtain the basic risk value; Among them, the sum of the first weight, the second weight, the third weight, the fourth weight, and the fifth weight is 1.

[0023] In this embodiment: The calculation formula for the basic risk value is as follows: ; Among them: F1 is the basic risk value reflecting the basic data security risk level of the enterprise in the current state; The larger the value of F1, the higher the risk; The smaller the value of F1, the lower the risk; N is the total factor collection volume, and N = 5; w i is any one of the first weight, the second weight, the third weight, the fourth weight, and the fifth weight in the risk impact weight information, the i-th weight; f i is any one of the equipment failure times, traffic anomaly times, data transmission delay times, network interruption times, and human error times in the risk factor information, the i-th real-time measurement value; The result reflects any one of the first risk, the second risk, the third risk, the fourth risk, and the fifth risk, the i-th risk; The result is the comprehensive basic risk; It should be noted that the setting of the i-th weight w i reflects the difference in the importance of different risk factors to enterprise data security. For factors that have a greater impact on data security, such as the number of network interruptions, a higher weight can be assigned, while for factors with relatively smaller impacts, such as some minor errors in the number of human errors, a lower weight can be assigned. This can more accurately reflect the contribution of each risk factor to the overall risk and make the evaluation result more targeted.

[0024] Refer to Figure 1 and Figure 2As shown in the figure, in this implementation: The key change information includes the amount of change before and after and the historical average change amount; According to the positive and negative values of the amount of change before and after, the acquisition of the risk value under the influence of key changes is as follows: When the amount of change before and after is negative, the risk value under the influence of key changes in the case of negative values is directly obtained according to the basic risk value; When the amount of change before and after is positive, the relative change influence amount is obtained according to the amount of change before and after and the historical average change amount; According to the basic risk value and the relative change influence amount, the risk value under the influence of key changes in the case of positive values is obtained.

[0025] In this embodiment: The calculation formula of the risk value under the influence of key changes is as follows: ; Wherein: F2 is the risk value under the influence of key changes; △B is the amount of change before and after; B avg is the historical average change amount; When △B ≤ 0, that is, when the amount of change before and after △B is negative and 0, F2 = F1; When △B > 0, that is, when the amount of change before and after △B is positive, .

[0026] Among them, it should be noted that it is divided into two cases of △B ≤ 0 and △B > 0 in order to avoid less than 0 is negative, and the phenomenon that F2 is less than 0 is negative. In actual situations, the risk assessment value generally will not be negative because the risk always exists, only the degree is different. The above operation can retain the risk maintenance of F2 = F1 when △B ≤ 0.

[0027] Referring to Figure 1 and Figure 2 As shown, in this implementation: The specific method for obtaining the sub-weight matching the sub-factor with the largest change before and after based on the change before and after of the sub-factor in the risk factor information is as follows: Obtain the current and previous number of equipment failures, number of flow anomalies, number of data transmission delays, number of network interruptions, and number of human errors from the risk assessment and weight adjustment module; Divide the current number of equipment failures by the previous number of equipment failures to obtain the first change ratio; Divide the current number of flow anomalies by the previous number of flow anomalies to obtain the second change ratio; Divide the current number of data transmission delays by the previous number of data transmission delays to obtain the third change ratio; Divide the current number of network interruptions by the previous number of network interruptions to obtain the fourth change ratio; Divide the current number of human errors by the previous number of human errors to obtain the fifth change ratio; Intelligently select the sub-weight with the largest change ratio from the first change ratio, the second change ratio, the third change ratio, the fourth change ratio, and the fifth change ratio; Based on the risk value and the risk warning value under the influence of key changes, obtain the weight adjustment amount representing the deviation ratio of the current risk relative to the threshold, which more intuitively reflects the degree to which the risk exceeds and is lower than the threshold; Based on the sub-weight with the largest change ratio and the weight adjustment amount, obtain the adjusted weight; In this embodiment: The calculation formula for the adjusted weight is as follows: ; Where: W i,new is the adjusted weight; F0 is the risk warning value; The result of is the weight adjustment amount; When F2 exceeds F0, the weight adjustment amount is greater than 1, which will cause the adjusted weight W i,new to increase; When F2 is lower than F0, the weight adjustment amount is less than 1, which will cause the adjusted weight W i,new to decrease; Among them, w i here refers to any i-th weight among the first weight, the second weight, the third weight, the fourth weight, and the fifth weight based on the largest change ratio.

[0028] By comparing the proportion changes of the first change ratio, the second change ratio, the third change ratio, the fourth change ratio, and the fifth change ratio, determine the sub-weight w i with the largest change ratio that needs to be adjusted, so as to use the calculation formula to highlight the main risk factors, enabling the enterprise to concentrate more resources and attention on key risks, improve the efficiency of risk control, and the adjusted weight W i,new is used for the next risk assessment and control, so that the risk control measures can more accurately target the main risk factors.

[0029] In addition, if the proportion change of the first change ratio is the largest, the system will increase the inspection frequency control of the equipment and perform equipment maintenance and maintenance in advance; For the case where the second change ratio changes greatly, the system will strengthen the control of network traffic monitoring to detect and prevent potential network attacks in a timely manner; If the proportion change of the third change ratio is the largest, the system will optimize the network configuration control to reduce data transmission delay; When the fourth change ratio changes the most, the system will increase the backup network line control to improve the reliability of the network; If the fifth change ratio has the largest change, the system will strengthen the control of employee training; It should be noted that, since the sum of the first weight, the second weight, the third weight, the fourth weight and the fifth weight is 1, when the adjusted weight W among the first weight, the second weight, the third weight, the fourth weight and the fifth weight is i,new After the adjustment is made, the other weights will also be averaged and reduced so that the sum of the first weight, the second weight, the third weight, the fourth weight and the fifth weight is always 1.

[0030] Reference Figure 1 As shown, in this implementation scheme: the before-after change amount and the historical average change amount are divided into two key factors of device temperature and data transmission rate; When the key factor is device temperature: The change before and after is the temperature change; The historical average change is the average change in temperature; When the key factor is data transfer rate: The change before and after is the change in transmission rate; The historical average change is the average change in transmission rate; Among them, during the initial control, one key factor is manually set from the device temperature and data transmission rate; After the initial control, key factors are intelligently selected based on the sub-weights of the maximum change ratio, as follows: If the maximum change ratio is the first change ratio, the key factor of the device temperature is intelligently selected; If the maximum change ratio is the second change ratio, the third change ratio, and the fourth change ratio, then intelligence is selected as a key factor for the data transmission rate.

[0031] In this embodiment, the enterprise data security risk is closely related to the equipment operation status and data transmission situation. Excessive equipment temperature will cause equipment failure, which in turn affects data security. Similarly, abnormal data transmission rate will indicate the risk of network attack or data leakage. The before-after change and the historical average change are divided into two key factors: equipment temperature and data transmission rate. This can more accurately capture the actual situation closely related to data security risks, making risk assessment more in line with the actual operation scenarios of the enterprise.

[0032] Manual setting of key factors is allowed during the initial control, which fully considers the personalized needs of the enterprise and the experience and judgment of managers. After the initial control, key factors are intelligently selected according to the sub-weights of the maximum change ratio, so that the system can automatically adjust the focus according to actual conditions, thereby enhancing the adaptability and flexibility of the system.

[0033] It should be noted that any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall also fall within the protection scope of the present invention.

Claims

1. A dynamically adjustable enterprise data security risk control system, characterized in that: It includes a data acquisition module, a risk assessment and weight adjustment module, and a control measure adjustment module; The data acquisition module: obtains the risk factor information and key change information collected by each acquisition sub-module; The risk assessment and weight adjustment module: receives the risk factor information and the key change information transmitted by the data acquisition module; Obtains risk impact weight information according to the risk factor information; Obtains a basic risk value according to the risk factor information and the risk impact weight information; Obtains the risk value under the influence of key changes according to the basic risk value and the key change information; Extracts the risk warning value preset and stored in the risk assessment and weight adjustment module; Obtains the sub-weight in the risk impact weight information matched by the sub-factor with the largest change before and after according to the change before and after of the sub-factor in the risk factor information; Obtains the adjusted weight according to the risk value under the influence of key changes, the risk warning value, and the sub-weight matched by the sub-factor with the largest change before and after; The control measure adjustment module: receives and executes the adjusted weight transmitted by the risk assessment and weight adjustment module; Executes the risk control of the sub-factor matched with it according to the adjusted weight.

2. The dynamically adjustable enterprise data security risk control system according to claim 1, wherein: The acquisition sub-module includes a fault monitoring device, a network traffic monitoring device, a network performance monitoring tool, a network connection monitoring device, a system operation log, and a total factor acquisition amount matched with the fault monitoring device, the network traffic monitoring device, the network performance monitoring tool, the network connection monitoring device, and the system operation log; The sub-factors of the risk factor information include the number of equipment failures, the number of abnormal traffic, the number of data transmission delays, the number of network interruptions, and the number of human errors; The fault monitoring device is used to obtain the number of equipment failures; The network traffic monitoring device is used to obtain the number of abnormal traffic; The network performance monitoring tool is used to obtain the number of data transmission delays; The network connection monitoring device is used to obtain the number of network interruptions; The system operation log is used to obtain the number of human errors.

3. The dynamically adjustable enterprise data security risk control system according to claim 2, characterized in that: The risk impact weight information includes a first weight, a second weight, a third weight, a fourth weight, and a fifth weight; Multiply the number of equipment failures by the first weight to obtain the first risk; Multiply the number of abnormal traffic by the second weight to obtain the second risk; Multiply the number of data transmission delays by the third weight to obtain the third risk; Multiply the number of network interruptions by the fourth weight to obtain the fourth risk; Multiply the number of human errors by the fifth weight to obtain the fifth risk; Add the first risk, the second risk, the third risk, the fourth risk, and the fifth risk to obtain the comprehensive basic risk; Divide the comprehensive basic risk by the total factor acquisition amount to obtain the basic risk value; Among them, the sum of the first weight, the second weight, the third weight, the fourth weight, and the fifth weight is 1.

4. The dynamically adjustable enterprise data security risk control system according to claim 3, characterized in that: The key change information includes the amount of change before and after and the historical average change amount; According to the positive or negative value of the before-and-after change amount, the risk value affected by the key change is obtained specifically as follows: When the before-and-after change amount is negative, the risk value affected by the key change in the negative case is directly obtained according to the basic risk value; When the before-and-after change amount is positive, the relative change influence amount is obtained according to the before-and-after change amount and the historical average change amount; According to the basic risk value and the relative change influence amount, the risk value affected by the key change in the positive case is obtained.

5. The dynamic adjustable enterprise data security risk control system according to claim 4, characterized in that: Both the before-and-after change amount and the historical average change amount are divided into two key factors: device temperature and data transmission rate; When the key factor is the device temperature: The before-and-after change amount is the temperature change amount; The historical average change amount is the average temperature change amount; When the key factor is the data transmission rate: The before-and-after change amount is the transmission rate change amount; The historical average change amount is the average transmission rate change amount; Among them, at the initial control, one of the key factors is manually selected from the device temperature and the data transmission rate.

6. The dynamically adjustable enterprise data security risk control system according to claim 5, characterized in that: The specific method for obtaining the sub-weight matching the sub-factor with the largest before-and-after change based on the before-and-after change of the sub-factor in the risk factor information is as follows: Obtain the current and previous numbers of device failures, traffic anomaly times, data transmission delay times, network interruption times, and human error times from the risk assessment and weight adjustment module; Divide the current number of device failures by the previous number of device failures to obtain the first change ratio; Divide the current number of traffic anomaly times by the previous number of traffic anomaly times to obtain the second change ratio; Divide the current number of data transmission delay times by the previous number of data transmission delay times to obtain the third change ratio; Divide the current number of network interruption times by the previous number of network interruption times to obtain the fourth change ratio; Divide the current number of human error times by the previous number of human error times to obtain the fifth change ratio; Intelligently select the sub-weight with the largest change ratio from the first change ratio, the second change ratio, the third change ratio, the fourth change ratio, and the fifth change ratio.

7. The dynamically adjustable enterprise data security risk control system according to claim 6, characterized in that: After the initial control, the key factor is intelligently selected according to the sub-weight with the largest change ratio, specifically as follows: If the largest change ratio is the first change ratio, the key factor selected is the device temperature; If the largest change ratio is the second change ratio, the third change ratio, and the fourth change ratio, the key factor selected is the data transmission rate.

8. The dynamically adjustable enterprise data security risk control system according to claim 6, characterized in that: Based on the risk value affected by the key change and the risk warning value, the weight adjustment amount is obtained; Based on the sub-weight with the largest change ratio and the weight adjustment amount, the adjusted weight is obtained.

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