A network data security protection method and system

Abstract

The present invention provides a network data security protection method and system, which belongs to the field of data security technology, and specifically includes: obtaining historical monitoring data of different target monitoring devices in different time periods, and determining the 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, determining the matching status of target monitoring devices belonging to data leakage risk dates in different time periods among different data leakage risk dates, and when it is determined based on the matching status that the data leakage risk of the video monitoring system meets the requirements, determining the data security protection strategy of the video monitoring system in different time periods based on the distribution data of the data leakage risk dates of different target monitoring devices in different time periods, thereby improving the security of network data.

Description

Technical Field

[0001] The present invention belongs to the field of data security technology, 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 crucial 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 recognition module recognizes and analyzes the image information obtained by the image capture module, and performs similarity recognition between the image information and the recorded image information stored in the database to determine the security of the text data, thereby ensuring the security of the video information during transmission and increasing the security of the viewer. However, the above technical solutions all have the following technical problems:

[0003] When performing security protection processing on network data, existing technical solutions ignore the determination of 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 risk of data leakage 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, this 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, specifically comprising:

[0007] S1: obtaining target monitoring devices of the video monitoring system, and when it is determined that the video monitoring system needs to generate differentiated data security protection strategies based on the distribution data of the target monitoring devices 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 the 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 on different data leakage risk dates. When it is determined based on the matching status that the data leakage risk of the video surveillance system meets the requirements, the data security protection strategy of the video surveillance 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 surveillance system needs to generate differentiated data security protection strategies, thereby realizing the evaluation of the difficulty of encryption processing based on the number and volume of data that need to be encrypted, ensuring that video surveillance 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 strategy of the video surveillance system in different time periods is determined. Taking into account the differences in the degree of matching with the data leakage risk dates of the target monitoring devices in different time periods, the data leakage risks of the video surveillance system in different time periods are differentiated. 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 a 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, a preset encryption measure is used to perform data security protection processing of 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] Determining the proportion of data leakage risk dates of different target monitoring devices in the time period based on the distribution data of data leakage risk dates of different target monitoring devices in the time period;

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

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

[0025] A further technical solution is to use the number of matching risk monitoring devices to determine the data security protection strategy in the time period, 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 adopted to perform data security protection processing of the video surveillance 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 uses 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 in communication connection, 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 objectives 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 accompanying 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 need to generate differentiated data security protection strategies for video surveillance systems;

[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] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this specification 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 based on the amount of data from different target monitoring devices. When the total amount of data is less 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 in which monitoring images with target features exist for the target monitoring device in the period 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 period.

[0043] Based on the matching of target monitoring devices belonging to data leakage risk dates in different time periods, the number of target monitoring devices belonging to data leakage risk dates in different time periods is determined, and the time period when the number of target monitoring devices belonging to data leakage risk dates is greater than the preset number of devices is regarded as a 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 said period. When the proportion of the number of risk monitoring devices is greater than 0.2, the video surveillance system adopts preset encryption measures to perform data security protection processing of the video surveillance system in the said period.

[0045] Example 1

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

[0047] S1: obtaining target monitoring devices of the video monitoring system, and when it is determined that the video monitoring system needs to generate differentiated data security protection strategies based on the distribution data of the target monitoring devices 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 a 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] Determining the number of target monitoring devices based on the distribution data of the target monitoring devices, and when the number of target monitoring devices is greater than a preset number of devices, determining 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 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 target monitoring devices is within a preset device number range:

[0062] 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, and determining that the video surveillance system needs to generate a differentiated data security protection strategy when the total amount of data of the target monitoring devices does not meet the requirements;

[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 a 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 using 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 the 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. When the monitoring target is a community, 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 debris accumulation.

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

[0071] Based on the recognition results of the target features in the historical monitoring data in the time period, determining the moments in the time period on different dates that include the target features, and using them as the feature matching moments;

[0072] Determine the data leakage risk coefficient of the period based on the proportion of the number of feature matching moments in the 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] Furthermore, 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] Determining the total number of target features for the 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 identification results of the target features in the historical monitoring data in the time period, determining the moments in the time period of different dates that include the target features, and using them as feature matching moments, obtaining the percentage of the number of feature matching moments in the time period in the date, and when the percentage of the number of feature matching moments in the time period in the date is greater than the percentage of the number of preset moments, determining that the date is a data leakage risk date in the time period;

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

[0083] Determining 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 determining that the date does not constitute a data leakage risk date during the time period when the total number of target features during the time period is less than a preset target feature number threshold;

[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: determining 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] Obtaining a number of feature matching moments in which the number of target features is not less than a preset number of target features, and when the number of feature matching moments in which the number of target features is not less than the preset number of target features does not meet the requirement, determining that the date is a data leakage risk date in the time 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] Based on 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 on different data leakage risk dates. When it is determined based on the matching status that the data leakage risk of the video surveillance system meets the requirements, the data security protection strategy of the video surveillance 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] Furthermore, 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 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 the data leakage risk dates in different time periods on different data leakage risk dates based on the matching status of the target monitoring devices belonging to the data leakage risk dates in different time periods;

[0096] Determining a risk leakage period in each period based on the number of target monitoring devices that fall within a data leakage risk period in each period;

[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 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 the data leakage risk dates in different time periods on different data leakage risk dates based on the matching status of the target monitoring devices belonging to the data leakage risk dates in different time periods;

[0103] Determining a risk leakage period in each period based on the number of target monitoring devices that fall within a data leakage risk period in each period;

[0104] The data leakage risk date whose proportion of risk leakage time periods is greater than the proportion of preset 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 proportion of the screening risk date.

[0105] Furthermore, 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 dates of the video surveillance system do not meet the requirements.

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

[0107] S31 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 status of the target monitoring devices belonging to the data leakage risk dates in different time periods;

[0108] S32: determining 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 determining 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, such as Figure 4 As shown, the method for determining the data security protection strategy of the video surveillance system in different time periods is:

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

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

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

[0114] Furthermore, 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 adopted to perform data security protection processing of the video surveillance 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] Step S311 obtains the number ratio of the data leakage risk dates. When the number ratio of the data leakage risk dates is less than a 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 a 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 range, the process proceeds to step S313; when the number ratio of the data leakage risk date is not within the preset number ratio range, 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 status of the target monitoring devices belonging to the data leakage risk dates in different time periods on different data leakage risk dates. If the time period ratio of the target monitoring devices belonging to the data leakage risk dates on different data leakage risk dates meets the requirement, the process proceeds to step S314. If the time period ratio of the target monitoring devices belonging to the data leakage risk dates does not meet the requirement, 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 number range, it is determined that the data leakage risk of the video surveillance 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 number range, go to step S32.

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

[0126] S321 determines the risk leakage period in each period based on the number of target monitoring devices that have data leakage risk dates in different periods. If the number of the risk leakage period is greater than a preset leakage period number threshold, it is determined that the data leakage risk of the video surveillance system does not meet the requirement. If 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, based on the proportion of the number of risk leakage periods in different data leakage risk dates, dates whose proportion is greater than the preset leakage period proportion. If the number of dates whose proportion is greater than the preset leakage period proportion does not meet the requirement, it is determined that the data leakage risk of the video surveillance system does not meet the requirement. If the number of dates whose proportion is greater than the preset leakage period proportion 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 coefficient does 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 coefficient does not meet the requirements is not greater than the preset number of risk dates, proceed to step S33.

[0130] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

[0131] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0132] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A network data security protection method, characterized in that: Specifically include: Obtaining target monitoring devices of the video monitoring system, and proceeding to the next step when determining that the video monitoring system needs to generate differentiated data security protection strategies based on the distribution data of the target monitoring devices and the data volume of different target monitoring devices; 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; determining matching conditions of target monitoring devices belonging to data leakage risk dates in different time periods on different data leakage risk dates; and determining, based on the matching conditions, when the data leakage risk of the video surveillance system meets the requirements, determining data security protection strategies for the video surveillance system in different time periods based on distribution data of data leakage risk dates of different target monitoring devices in different time periods; Determine that the video surveillance system needs to generate differentiated data security protection strategies, specifically including: determining the number of the target monitoring devices based on the distribution data of the target monitoring devices; determining a 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; Determining whether the video surveillance system needs to generate differentiated data security protection strategies based on the total amount of data; 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; Determine that the data leakage risk of the video surveillance system meets the requirements, including: Determine 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 status of the target monitoring devices belonging to the data leakage risk dates in different time periods; Determining a risk leakage period in each period based on the number of target monitoring devices that have data leakage risk dates in each period; Obtaining the number percentage of the data leakage risk dates, and combining the average number percentage of the risk leakage time periods in different data leakage risk dates to determine the system data leakage risk coefficient of the video surveillance system, and using the system data leakage risk coefficient to determine whether the data leakage risk of the video surveillance system meets the requirements; when the system data leakage risk coefficient of the video surveillance system is greater than a preset leakage risk coefficient, determining that the data leakage risk of the video surveillance system does not meet the requirements; The method for determining the data security protection strategy of the video surveillance system in different time periods is as follows: Determining the proportion of data leakage risk dates of different target monitoring devices in the time period based on the distribution data of data leakage risk dates of different target monitoring devices in the time period; Determining matching risk coefficients of different target monitoring devices in the time period based on the proportion of data leakage risk dates of different target monitoring devices in the time period; Matching risk monitoring devices in the time period is performed by using matching risk coefficients of different target monitoring devices in the time period, and the data security protection strategy in the time period is determined using the number of matching risk monitoring devices.

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, wherein: When the video surveillance system does not need to generate differentiated data security protection strategies, a preset encryption measure is used to perform data security protection processing for the video surveillance system.

5. The network data security protection method according to claim 1, wherein: Determining the data security protection strategy in the time period 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 of the video surveillance 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 adopted to perform data security protection processing of the video surveillance system.

6. The network data security protection method according to claim 5, characterized in 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.

7. A computer system comprising: A memory and a processor in communication connection, 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 according to any one of claims 1 to 6 when running the computer program.

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