Network data security protection method and system

Abstract

The invention provides a network data security protection method and system, and belongs to the technical field of data security, and the method specifically comprises the steps: obtaining historical monitoring data of different target monitoring devices in different time periods, and carrying out the recognition of a target feature in the historical monitoring data in different time periods according to the recognition result of the target feature in the historical monitoring data in different time periods; the method comprises the steps of determining data leakage risk dates of different target monitoring devices in different time periods, determining matching conditions of the target monitoring devices belonging to the data leakage risk dates in different time periods in different data leakage risk dates, and determining the data leakage risk of the video monitoring system when determining that the data leakage risk of the video monitoring system meets requirements based on the matching conditions. The data security protection strategy of the video monitoring system in different time periods is determined on the basis of the distribution data of the data leakage risk dates of different target monitoring devices in different time periods, so that the security of network data is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data security, and in particular relates to a network data security protection method and system. Background Art

[0002] The monitoring data of the video surveillance device involves personal privacy data, which makes it extremely important to ensure the security of the monitoring data. Specifically, in the invention patent application CN202010231458.3 "A video surveillance system based on cloud services", the image information obtained by the image capture module is recognized and analyzed by the recognition module, and the image information is similarly recognized with the recorded image information stored in the database, and the security of the text data is determined, thereby ensuring the security of the video information transmission process and increasing the security of the viewers. However, the above technical solutions all have the following technical problems:

[0003] When performing security protection processing on network data, the existing technical solutions have neglected to determine differentiated data security protection strategies based on the analysis results of video surveillance data. In different time periods, there are differences in the flow of people in the video surveillance data, which leads to a certain degree of difference in the risk of data leakage in different time periods. Therefore, if differentiated security protection strategies cannot be determined based on the data leakage risks in different time periods, it is impossible to improve data security while reducing the difficulty of data encryption processing.

[0004] In response to the above technical problems, the present application specifically provides a network data security protection method and system. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present application provides a network data security protection method, which specifically includes:

[0007] S1: obtaining a target monitoring device of a video monitoring system, and when it is determined that the video monitoring system needs to generate a differentiated data security protection strategy based on the distribution data of the target monitoring device and the data volume of different target monitoring devices, proceeding to the next step;

[0008] S2 obtains historical monitoring data of different target monitoring devices in different time periods, and determines data leakage risk dates of different target monitoring devices in different time periods based on the recognition results of target features in the historical monitoring data in different time periods;

[0009] S3 determines the matching status of target monitoring devices belonging to data leakage risk dates in different time periods among different data leakage risk dates. When it is determined based on the matching status that the data leakage risk of the video monitoring system meets the requirements, the data security protection strategy of the video monitoring system in different time periods is determined based on the distribution data of the data leakage risk dates of different target monitoring devices in different time periods.

[0010] The beneficial effects of the present invention are:

[0011] Based on the distribution data of target monitoring devices and the data volume of different target monitoring devices, it is determined whether the video monitoring system needs to generate differentiated data security protection strategies, thereby realizing the evaluation of the difficulty of encryption processing based on the number and amount of data that need to be encrypted, ensuring that video monitoring systems with lower encryption processing difficulty can adopt more stringent encryption processing measures, while also realizing the determination of differentiated encryption processing measures for adaptive monitoring systems with higher encryption processing difficulty, reducing the difficulty of encryption processing.

[0012] Based on the distribution data of data leakage risk dates of different target monitoring devices in different time periods, the data security protection strategies of the video surveillance system in different time periods are determined. The differences in the degree of matching with the data leakage risk dates of the target monitoring devices in different time periods lead to the differences in the data leakage risks of the video surveillance system in different time periods. This realizes the differentiated determination of data security protection strategies for different time periods based on the differences in data leakage risks. On the basis of ensuring data security, the difficulty of data encryption processing is reduced.

[0013] A further technical solution is that the target monitoring device is a monitoring device in the video monitoring system.

[0014] A further technical solution is that the data volume of the target monitoring device is determined based on an average value of the data volume of historical monitoring data of the target monitoring device on different dates.

[0015] A further technical solution is to determine that the video surveillance system needs to generate differentiated data security protection strategies, specifically including:

[0016] Determining the number of the target monitoring devices based on the distribution data of the target monitoring devices;

[0017] Determining the total amount of data of the target monitoring devices based on the number of the target monitoring devices and the amount of data of different target monitoring devices;

[0018] Determine whether the video surveillance system needs to generate differentiated data security protection strategies based on the total amount of data.

[0019] A further technical solution is that, when the total amount of data is less than a preset data amount threshold, it is determined that the video surveillance system does not need to generate a differentiated data security protection strategy.

[0020] A further technical solution is that, when the video surveillance system does not need to generate differentiated data security protection strategies, preset encryption measures are used to perform data security protection processing for the video surveillance system.

[0021] A further technical solution is that the method for determining the data security protection strategy of the video surveillance system in different time periods is:

[0022] Determine the quantity proportion of the data leakage risk dates of different target monitoring devices in the period based on the distribution data of the data leakage risk dates of different target monitoring devices in the period;

[0023] Determining matching risk coefficients of different target monitoring devices in the time period based on the proportion of the number of data leakage risk dates of different target monitoring devices in the time period;

[0024] Matching risk monitoring devices in the time period are performed by matching risk coefficients of different target monitoring devices in the time period, and the data security protection strategy in the time period is determined by using the number of matching risk monitoring devices.

[0025] A further technical solution is to determine the data security protection strategy in the time period by using the number of matching risk monitoring devices, specifically including:

[0026] When the number of the matching risk monitoring devices is greater than a preset risk device number threshold, a preset encryption measure is used to perform data security protection processing on the video monitoring system.

[0027] When the number of the matching risk monitoring devices is not greater than a preset risk device number threshold, a second preset encryption measure is used to perform data security protection processing on the video monitoring system.

[0028] A further technical solution is that the preset encryption measure is to use the CryptoJS library to perform data encryption processing, and the second preset encryption measure is to use Base64 encoding to perform data encryption processing.

[0029] In a second aspect, the present invention provides a computer system comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned network data security protection method when running the computer program.

[0030] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0031] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0033] Figure 1 It is a flow chart of a network data security protection method;

[0034] Figure 2 It is a flowchart to determine the differentiated data security protection strategies that need to be generated by the video surveillance system;

[0035] Figure 3 is a flow chart of a method for determining a data breach risk date in a time period;

[0036] Figure 4 It is a flow chart of a method for determining data security protection strategies of a video surveillance system in different time periods;

[0037] Figure 5 It is a framework diagram of a computer system. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0039] In this application, differentiated data security protection strategies are generated based on the data leakage risks of the video surveillance system in different time periods, which not only reduces the difficulty of encryption processing but also ensures the security of network data.

[0040] The total amount of data is determined by the amount of data from different target monitoring devices. When the total amount of data is greater than a preset data amount threshold, it is determined that the video monitoring system does not need to generate differentiated data security protection strategies.

[0041] Target features include pedestrians, vehicles, and debris accumulation.

[0042] When the number of moments of monitoring images with target features in the time period of the target monitoring device on the date accounts for more than 0.6, it is determined that the date is a data leakage risk date for the target monitoring device in the time period.

[0043] The number of target monitoring devices belonging to data leakage risk dates in different time periods is determined based on the matching of target monitoring devices belonging to data leakage risk dates in different time periods, and the time period in which the number of target monitoring devices belonging to data leakage risk dates is greater than the preset number of devices is taken as the risk period. When the proportion of the number of risk periods is greater than 0.3 and the proportion of the number of data leakage risk dates is greater than 0.5, it is determined that the data leakage risk of the video surveillance system does not meet the requirements.

[0044] The risk monitoring device is determined based on the proportion of the number of data leakage risk dates of different target monitoring devices in the time period. When the proportion of the number of risk monitoring devices is greater than 0.2, the video monitoring system adopts preset encryption measures to perform data security protection processing of the video monitoring system in the time period.

[0045] Example 1

[0046] like Figure 1 As shown, the present application provides a first aspect, the present application provides a first aspect, the present application provides a network data security protection method, specifically including:

[0047] S1: obtaining a target monitoring device of a video monitoring system, and when it is determined that the video monitoring system needs to generate a differentiated data security protection strategy based on the distribution data of the target monitoring device and the data volume of different target monitoring devices, proceeding to the next step;

[0048] Furthermore, the target monitoring device is a monitoring device in the video monitoring system.

[0049] Specifically, the data volume of the target monitoring device is determined according to an average value of the data volume of the historical monitoring data of the target monitoring device on different dates.

[0050] It should be noted that if Figure 2 As shown, it is determined that the video surveillance system needs to generate a differentiated data security protection strategy, specifically including:

[0051] Determining the number of the target monitoring devices based on the distribution data of the target monitoring devices;

[0052] Determining the total amount of data of the target monitoring devices based on the number of the target monitoring devices and the amount of data of different target monitoring devices;

[0053] Determine whether the video surveillance system needs to generate differentiated data security protection strategies based on the total amount of data.

[0054] Furthermore, when the total amount of data is less than a preset data amount threshold, it is determined that the video surveillance system does not need to generate a differentiated data security protection strategy.

[0055] It is understandable that when the video surveillance system does not need to generate differentiated data security protection strategies, the preset encryption measures are used to perform data security protection processing of the video surveillance system.

[0056] Optionally, determining that the video surveillance system needs to generate a differentiated data security protection strategy specifically includes:

[0057] Based on the distribution data of the target monitoring devices, the number of the target monitoring devices is determined, and when the number of the target monitoring devices is greater than the preset number of devices, it is determined that the video monitoring system needs to generate a differentiated data security protection strategy;

[0058] When the number of target monitoring devices is not greater than the preset number of devices:

[0059] When the number of the target monitoring devices is not within the preset device number range:

[0060] It is determined that the video surveillance system does not need to generate differentiated data security protection strategies;

[0061] When the number of the target monitoring devices is within the preset device number range:

[0062] Based on the number of the target monitoring devices and the data volumes of different target monitoring devices, determining the total amount of data of the target monitoring devices, and when the total amount of data of the target monitoring devices does not meet the requirements, determining that the video monitoring system needs to generate differentiated data security protection strategies;

[0063] When the total amount of data of the video surveillance system meets the requirements:

[0064] Based on the monitoring targets of different target monitoring devices, the target monitoring devices are divided into a plurality of monitoring device groups, and when the number of the monitoring device groups is greater than the preset number of groups, it is determined that the video monitoring system does not need to generate differentiated data security protection strategies;

[0065] When the number of monitoring device groups is not greater than the preset number of groups:

[0066] The difficulty of encryption processing is determined by the total amount of data of the target monitoring device, the leakage risk coefficient is determined according to the number of the monitoring device groups, and the encryption requirement coefficient of the video surveillance system is determined by the ratio of the leakage risk coefficient to the encryption processing difficulty. The encryption requirement coefficient is used to determine whether the video surveillance system needs to generate differentiated data security protection strategies.

[0067] Furthermore, when the encryption requirement coefficient is greater than a preset coefficient threshold, it is determined that the video surveillance system needs to generate a differentiated data security protection strategy.

[0068] S2 obtains historical monitoring data of different target monitoring devices in different time periods, and determines data leakage risk dates of different target monitoring devices in different time periods based on the recognition results of target features in the historical monitoring data in different time periods;

[0069] Specifically, the target characteristics are determined according to the monitoring target of the target monitoring device, and specifically according to the preset target characteristics corresponding to the monitoring target, wherein when the monitoring target is a residential area, the target characteristics include pedestrians and vehicles; when the monitoring target is a safe passage, the target characteristics include passage debris; when the monitoring target is a fire monitoring area, the monitoring target includes flammable points and accumulation of debris.

[0070] Specifically, Figure 3 As shown, the method for determining the data leakage risk date in the period is:

[0071] Based on the recognition result of the target feature in the historical monitoring data in the time period, determine the time when the time period in different dates includes the target feature, and use it as the feature matching time;

[0072] Determine the data leakage risk coefficient of the time period according to the proportion of the number of feature matching moments in the time period on the date;

[0073] It is determined based on the data leakage risk coefficient whether the date is a data leakage risk date in the time period.

[0074] Further, when the data leakage risk coefficient is greater than a preset risk coefficient threshold, the date is determined to be a data leakage risk date in the time period.

[0075] Optionally, the method for determining the data leakage risk date in the period is:

[0076] Based on the recognition result of the target feature in the historical monitoring data in the time period, determine the time when the time period in the date includes the target feature, and use it as the feature matching time;

[0077] Determine the total number of target features for the time period on the date based on the number of target features at the feature matching moment;

[0078] Determine whether the date is a data leakage risk date in the time period according to the total number.

[0079] It should be noted that when the total number of the target features is greater than a preset feature number threshold, the date is determined to be a data leakage risk date in the time period.

[0080] Optionally, the method for determining the data leakage risk date in the period is:

[0081] Based on the recognition result of the target feature in the historical monitoring data in the time period, determine the time in the time period of different dates that includes the target feature, and use it as the feature matching time, obtain the number ratio of the feature matching time in the time period in the date, and when the number ratio of the feature matching time in the time period in the date is greater than the number ratio of the preset time, determine that the date is a data leakage risk date in the time period;

[0082] When the proportion of the feature matching moments in the period on the date is not greater than the proportion of the preset moments:

[0083] Determine the number of target features at different feature matching moments based on the recognition results of the target features at different feature matching moments, and when the total number of target features in the time period is less than a preset target feature number threshold, determine that the date does not belong to a data leakage risk date in the time period;

[0084] When the total number of target features in the time period is not less than the preset target feature number threshold:

[0085] When the total number of target features in the time period is greater than a preset feature number threshold, determining that the date is a data leakage risk date in the time period;

[0086] When the total number of target features in the time period is not greater than the preset feature number threshold:

[0087] When the number of target features at different feature matching moments is less than the preset number of target features: it is determined that the date does not belong to the data leakage risk date in the period;

[0088] When there is a feature matching moment where the number of target features is not less than the preset number of target features:

[0089] Acquire the number of feature matching moments when the number of target features is not less than the preset number of target features, and when the number of feature matching moments when the number of target features is not less than the preset number of target features does not meet the requirement, determine that the date is a data leakage risk date in the period;

[0090] When the number of target features is not less than the preset number of target features and the number of feature matching moments meets the requirement:

[0091] According to the proportion of the number of feature matching moments in the time period on the date, and combined with the number of target features in different feature matching moments, the data leakage risk coefficient of the date in the time period is determined, and the data leakage risk coefficient is used to determine whether the date in the time period is a data leakage risk date.

[0092] S3 determines the matching status of target monitoring devices belonging to data leakage risk dates in different time periods among different data leakage risk dates. When it is determined based on the matching status that the data leakage risk of the video monitoring system meets the requirements, the data security protection strategy of the video monitoring system in different time periods is determined based on the distribution data of the data leakage risk dates of different target monitoring devices in different time periods.

[0093] Further, the matching status of the target monitoring devices belonging to the data leakage risk date in the time period is determined according to the number of the target monitoring devices belonging to the data leakage risk date in the time period on the current date.

[0094] Specifically, determining whether the data leakage risk of the video surveillance system meets the requirements includes:

[0095] Determine the number of target monitoring devices belonging to data leakage risk dates in different time periods on different data leakage risk dates based on the matching conditions of target monitoring devices belonging to data leakage risk dates in different time periods on different data leakage risk dates;

[0096] Determining a risk leakage period in the period based on the number of target monitoring devices belonging to data leakage risk dates in different periods;

[0097] Obtain the percentage of the number of data leakage risk dates, and determine the system data leakage risk coefficient of the video surveillance system based on the average value of the percentage of the number of risk leakage time periods in different data leakage risk dates, and use the system data leakage risk coefficient to determine whether the data leakage risk of the video surveillance system meets the requirements.

[0098] Furthermore, the system data leakage risk coefficient is determined according to the product of the number ratio of the data leakage risk dates and the average value of the number ratio of risk leakage time periods in different data leakage risk dates.

[0099] Specifically, when the system data leakage risk coefficient of the video surveillance system is greater than a preset leakage risk coefficient, it is determined that the data leakage risk of the video surveillance system does not meet the requirement.

[0100] It is understandable that when the data leakage risk of the video surveillance system does not meet the requirements, the preset encryption measures are used to perform data security protection processing of the video surveillance system.

[0101] In another possible embodiment, determining that the data leakage risk of the video surveillance system meets the requirement specifically includes:

[0102] Determine the number of target monitoring devices belonging to data leakage risk dates in different time periods on different data leakage risk dates based on the matching conditions of target monitoring devices belonging to data leakage risk dates in different time periods on different data leakage risk dates;

[0103] Determining a risk leakage period in the period based on the number of target monitoring devices belonging to data leakage risk dates in different periods;

[0104] The data leakage risk date whose number of risk leakage time periods accounts for a greater proportion than the preset number of time periods is used as the screening risk date, and whether the data leakage risk of the video surveillance system meets the requirements is determined based on the number proportion of the screening risk date.

[0105] Further, when the proportion of the number of the screened risk dates is greater than the proportion of the number of preset screened dates, it is determined that the data leakage risk date of the video surveillance system does not meet the requirements.

[0106] Optionally, determining whether the data leakage risk of the video surveillance system meets the requirement specifically includes:

[0107] S31 determines the number of target monitoring devices belonging to data leakage risk dates in different time periods on different data leakage risk dates based on the matching conditions of target monitoring devices belonging to data leakage risk dates in different time periods on different data leakage risk dates;

[0108] S32 determines the risk leakage period in the period based on the number of target monitoring devices belonging to the data leakage risk date in different periods, and determines the date risk coefficients of different data leakage risk dates based on the number of risk leakage periods in different data leakage risk dates and the number of target monitoring devices belonging to the data leakage risk date in different risk leakage periods;

[0109] S33 determines the system data leakage risk coefficient of the video surveillance system by multiplying the number of the data leakage risk dates by the average value of the date risk coefficients of different data leakage risk dates, and uses the system data leakage risk coefficient to determine whether the data leakage risk of the video surveillance system meets the requirements.

[0110] Specifically, Figure 4 As shown, the method for determining the data security protection strategy of the video surveillance system in different time periods is:

[0111] Determine the quantity proportion of the data leakage risk dates of different target monitoring devices in the period based on the distribution data of the data leakage risk dates of different target monitoring devices in the period;

[0112] Determining matching risk coefficients of different target monitoring devices in the time period based on the proportion of the number of data leakage risk dates of different target monitoring devices in the time period;

[0113] Matching risk monitoring devices in the time period are performed by matching risk coefficients of different target monitoring devices in the time period, and the data security protection strategy in the time period is determined by using the number of matching risk monitoring devices.

[0114] Further, the data security protection strategy in the time period is determined by using the number of matching risk monitoring devices, specifically including:

[0115] When the number of the matching risk monitoring devices is greater than a preset risk device number threshold, a preset encryption measure is used to perform data security protection processing on the video monitoring system.

[0116] When the number of the matching risk monitoring devices is not greater than a preset risk device number threshold, a second preset encryption measure is used to perform data security protection processing on the video monitoring system.

[0117] It can be understood that the preset encryption measure is to use the CryptoJS library to perform data encryption processing, and the second preset encryption measure uses Base64 encoding to perform data encryption processing.

[0118] Example 2

[0119] Second, as Figure 5 As shown, the present invention provides a computer system, comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned network data security protection method when running the computer program.

[0120] Optionally, the above step S31 includes the following contents:

[0121] S311 obtains the number ratio of the data leakage risk dates. When the number ratio of the data leakage risk dates is less than the number ratio threshold, it is determined that the data leakage risk of the video surveillance system meets the requirement. When the number ratio of the data leakage risk dates is not less than the preset number ratio threshold, the process proceeds to step S312.

[0122] S312: When the number ratio of the data leakage risk date is within the preset number ratio interval, the process proceeds to step S313; when the number ratio of the data leakage risk date is not within the preset number ratio interval, the process proceeds to step S32;

[0123] S313 determines the number of target monitoring devices belonging to the data leakage risk dates in different time periods on different data leakage risk dates based on the matching conditions of the target monitoring devices belonging to the data leakage risk dates in different time periods on different data leakage risk dates. When the time period quantity ratio of the target monitoring devices belonging to the data leakage risk dates on different data leakage risk dates meets the requirements, the process proceeds to step S314. When there is a data leakage risk date for which the time period quantity ratio of the target monitoring devices belonging to the data leakage risk dates does not meet the requirements, the process proceeds to step S32.

[0124] S314 When the number of target monitoring devices belonging to the data leakage risk date in different time periods is within the preset device quantity range, it is determined that the data leakage risk of the video monitoring system meets the requirements. When there is a time period when the number of target monitoring devices belonging to the data leakage risk date is not within the preset device quantity range, proceed to step S32.

[0125] Optionally, the above step S32 includes the following contents:

[0126] S321 determines the risk leakage period in the period based on the number of target monitoring devices belonging to the data leakage risk date in different periods. When the number of the risk leakage period is greater than the preset leakage period number threshold, it is determined that the data leakage risk of the video monitoring system does not meet the requirements. When the number of the risk leakage period is not greater than the preset leakage period number threshold, the process proceeds to step S322.

[0127] S322 determines the date whose number ratio is greater than the preset leakage period ratio based on the number ratio of the risk leakage time periods in different data leakage risk dates. When the number of dates whose number ratio is greater than the preset leakage period ratio does not meet the requirement, it is determined that the data leakage risk of the video surveillance system does not meet the requirement. When the number of dates whose number ratio is greater than the preset leakage period ratio meets the requirement, the process proceeds to step S323.

[0128] S323 determines the date risk coefficients of different data leakage risk dates based on the number of risk leakage periods in different data leakage risk dates and the number of target monitoring devices belonging to the data leakage risk dates in different risk leakage periods. When the date risk coefficients of different data leakage risk dates all meet the requirements, the process proceeds to step S33. When there is a data leakage risk date whose date risk coefficient does not meet the requirements, the process proceeds to step S324.

[0129] S324 When the number of data leakage risk dates whose date risk coefficients do not meet the requirements is greater than the preset number of risk dates, it is determined that the data leakage risk of the video surveillance system does not meet the requirements; when the number of data leakage risk dates whose date risk coefficients do not meet the requirements is not greater than the preset number of risk dates, proceed to step S33.

[0130] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0131] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0132] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A network data security protection method, characterized in that: Specifically include: Obtaining a target monitoring device of the video monitoring system, and when it is determined that the video monitoring system needs to generate a differentiated data security protection strategy based on the distribution data of the target monitoring device and the data volume of different target monitoring devices, proceeding to the next step; Obtaining historical monitoring data of different target monitoring devices in different time periods, and determining data leakage risk dates of different target monitoring devices in different time periods based on the recognition results of target features in the historical monitoring data in different time periods; Determine the matching status of target monitoring devices belonging to data leakage risk dates in different time periods among different data leakage risk dates. When it is determined based on the matching status that the data leakage risk of the video monitoring system meets the requirements, determine the data security protection strategy of the video monitoring system in different time periods based on the distribution data of data leakage risk dates of different target monitoring devices in different time periods.

2. The network data security protection method according to claim 1, characterized in that: The target monitoring device is a monitoring device in the video monitoring system.

3. The network data security protection method according to claim 1, characterized in that: The data volume of the target monitoring device is determined according to the average data volume of the historical monitoring data of the target monitoring device on different dates.

4. The network data security protection method according to claim 1, characterized in that: Determine that the video surveillance system needs to generate differentiated data security protection strategies, including: Determining the number of the target monitoring devices based on the distribution data of the target monitoring devices; Determining the total amount of data of the target monitoring devices based on the number of the target monitoring devices and the amount of data of different target monitoring devices; Determine whether the video surveillance system needs to generate differentiated data security protection strategies based on the total amount of data.

5. The network data security protection method according to claim 4, characterized in that: When the total amount of data is less than a preset data amount threshold, it is determined that the video surveillance system does not need to generate a differentiated data security protection strategy.

6. The network data security protection method according to claim 1, characterized in that: When the video surveillance system does not need to generate differentiated data security protection strategies, preset encryption measures are used to perform data security protection processing for the video surveillance system.

7. The network data security protection method according to claim 1, characterized in that: The method for determining the data security protection strategy of the video surveillance system in different time periods is: Determine the quantity proportion of the data leakage risk dates of different target monitoring devices in the period based on the distribution data of the data leakage risk dates of different target monitoring devices in the period; Determining matching risk coefficients of different target monitoring devices in the time period based on the proportion of the number of data leakage risk dates of different target monitoring devices in the time period; Matching risk monitoring devices in the time period are performed by matching risk coefficients of different target monitoring devices in the time period, and the data security protection strategy in the time period is determined by using the number of matching risk monitoring devices.

8. The network data security protection method according to claim 7, characterized in that: Determining the data security protection strategy in the time period by using the number of matching risk monitoring devices specifically includes: When the number of the matching risk monitoring devices is greater than a preset risk device number threshold, a preset encryption measure is used to perform data security protection processing on the video monitoring system. When the number of the matching risk monitoring devices is not greater than a preset risk device number threshold, a second preset encryption measure is used to perform data security protection processing on the video monitoring system.

9. The network data security protection method according to claim 8, characterized in that: The preset encryption measure is to use the CryptoJS library to perform data encryption processing, and the second preset encryption measure uses Base64 encoding to perform data encryption processing.

10. A computer system comprising: A memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes a network data security protection method as described in any one of claims 1-9 when running the computer program.

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