Safety protection method for intelligent video monitoring system

Abstract

The invention belongs to the technical field of video monitoring security protection, and relates to an intelligent video monitoring system security protection method, which comprises the following steps of: receiving a unified firmware updating instruction of a target video monitoring equipment cluster, verifying the authenticity and integrity of data associated with a to-be-updated firmware block chain, and if the verification is passed, updating the to-be-updated firmware block chain. Starting a firmware updating process of the target video monitoring equipment cluster, dynamically evaluating the firmware updating risk level of the target video monitoring equipment cluster at each monitoring time point in the firmware updating process so as to take corresponding management and control measures to comprehensively and deeply insight into the risk condition in the whole firmware updating process, and after the firmware updating is completed, carrying out management and control on the target video monitoring equipment cluster. According to the method, the stability test and the compatibility test are carried out on the target video monitoring equipment cluster, so that each abnormal video monitoring equipment is screened and reported, the security protection problem of the equipment firmware updating layer of the video monitoring system in the prior art is effectively solved, and the continuous and stable operation capability of the video monitoring system is enhanced.

Description

Technical Field

[0001] The invention belongs to the technical field of video surveillance security protection, and relates to a security protection method for an intelligent video surveillance system. Background Art

[0002] With the rapid development of Internet of Things and artificial intelligence technologies, intelligent video surveillance equipment has been widely used in public safety, traffic management, commercial monitoring and personal property protection. However, the high degree of networking and popularity of these devices also brings new security challenges, such as frequent cyber attacks, data leakage, unauthorized access, etc., which seriously threaten public and personal safety and arouse widespread concern about privacy protection. Therefore, researching and implementing effective security protection methods for intelligent video surveillance systems has become an urgent problem that needs to be solved.

[0003] There are also solutions related to the security protection of video surveillance systems in the prior art. For example, a video surveillance system information security protection method and system with Chinese patent publication number CN118158361A collects internal and external information of the video surveillance system through the internal and external information collection unit of the security information collection module, generates an internal security information set and an external security information set, performs related calculations, obtains a comprehensive security information coefficient Zhxs, and passes multiple external security information authentications. Therefore, when external information logs in, the security of the first line of protection is relatively improved. At the same time, through its video surveillance system, the virus monitoring software and security scanning software set inside can monitor the internal environment of the video surveillance system in real time, thereby ensuring the security of the video surveillance data storage environment and realizing an internal and external dual system protection mechanism.

[0004] Another Chinese patent publication number CN108377365A is a video surveillance system based on a video security access path, which includes several ports for information access or output, each port forms a communication path through an open / closed network, and the ports include a server port, several monitoring data input ports, and several other device ports, wherein a gateway module A is set between the server port and the open / closed network, and a gateway module B is set between the open / closed network and the monitoring data input port. Through the one-way comparison / verification / audit of information by the gateway module A to the gateway module B, an effective information transmission path between the server port and the monitoring data input port is formed, and the classification of effective and invalid paths of network information transmission and one-way transmission locking are realized, thereby realizing low-cost and high-security network protection.

[0005] However, the existing technology still has certain limitations, which are specifically manifested as follows: the existing technology focuses on the data security protection and network security protection of the video surveillance system, lacks the exploration of the equipment security protection of the video surveillance system or only stays at the shallow physical security protection level, and fails to effectively consider the security risks in the regular firmware update process of the video surveillance equipment of the video surveillance system, such as the inability to effectively identify whether the source of the firmware is legal and reliable, and it is difficult to detect whether there is an intrusion during the firmware update that causes the video work or network environment to become abnormal, and after the firmware update is completed, there is a complete lack of effective evaluation and response measures for the impact and influence on the stability and compatibility of the equipment monitoring capabilities, which undoubtedly lays a huge risk for the safe and stable operation of the video surveillance system. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a security protection method for an intelligent video surveillance system is now proposed.

[0007] The objective of the present invention can be achieved through the following technical solutions: The present invention provides a security protection method for an intelligent video surveillance system, comprising: S1. Receiving a unified firmware update instruction of a target video surveillance device cluster, verifying the authenticity and integrity of the data associated with the firmware blockchain to be updated, and if the verification passes, executing step S2; if the verification fails, rejecting the unified firmware update instruction.

[0008] S2. Start the firmware update process of the target video surveillance device cluster, monitor the firmware update network environment status and firmware update device environment status of the target video surveillance device cluster in real time during the firmware update process, and evaluate the potential risk factor of the firmware update partition of the target video surveillance device cluster at each monitoring time point.

[0009] S3. During the firmware update process, the video surveillance working status of each video surveillance device in the target video surveillance device cluster is monitored in real time, and the potential risk factor of the firmware working partition of the target video surveillance device cluster at each monitoring time point is evaluated.

[0010] S4. Comprehensively consider the potential risk factors of the firmware working partition and the firmware update partition, assess the firmware update risk level of the target video surveillance device cluster at each monitoring time point, and take corresponding control measures.

[0011] S5. After the unified firmware update of the target video surveillance device cluster is completed, stability test and compatibility test are performed on the target video surveillance device cluster, and each abnormal video surveillance device is screened, placed in a safe isolation mode and reported to the management center.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) Before the unified firmware update of the target video surveillance device cluster, the present invention verifies the authenticity and integrity of the data associated with the blockchain of the firmware to be updated, which not only effectively prevents false or tampered firmware from entering the update process, but also reduces the update failure or device abnormality caused by data errors, thereby greatly enhancing the security and stability of the firmware update of the video surveillance device cluster.

[0013] (2) The present invention unifies the firmware update process of the firmware video surveillance device cluster, comprehensively considers the potential risk factors of the firmware working partition and the firmware update partition, and dynamically assesses the firmware update risk level of the target video surveillance device cluster at each monitoring time point, so as to take corresponding management and control measures, comprehensively and deeply understand the risk status in the entire update process, and greatly improve the security and controllability of the firmware update process of the video surveillance device cluster.

[0014] (3) After the unified firmware update of the firmware video surveillance device cluster is completed, the present invention performs stability test and compatibility test on the target video surveillance device cluster to screen out abnormal video surveillance devices for reporting. This is not only conducive to improving the maintenance efficiency of the equipment and reducing the maintenance cost, but also can ensure that the video surveillance device cluster can work together after the firmware update, seamlessly connect to the existing monitoring system, and give full play to its due monitoring efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0016] Figure 1 The present invention is a flowchart of the steps for implementing the method.

[0017] Figure 2 This is a logical schematic diagram for evaluating the potential risk coefficient of the firmware update partition of the target video surveillance device cluster at each monitoring time point in step S2 of the present invention.

[0018] Figure 3 This is a logical diagram of screening various abnormal video surveillance devices in step S5 of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] See also Figure 1 As shown, the present invention provides a security protection method for an intelligent video surveillance system, including: S1. Receiving a unified firmware update instruction of a target video surveillance device cluster, verifying the authenticity and integrity of the data associated with the firmware blockchain to be updated, if the verification passes, executing step S2, if the verification fails, rejecting the unified firmware update instruction.

[0021] It should be noted that the above-mentioned target video surveillance device cluster specifically refers to an integrated group composed of various video surveillance devices within the same target video surveillance system, wherein the video surveillance devices adopt a dual-partition design so that they can continue to perform video surveillance tasks during the firmware update process.

[0022] Specifically, the verification of the authenticity and integrity of the data associated with the blockchain of the firmware to be updated includes: performing digital signature verification and hash value verification on the terminal node of the blockchain of the firmware to be updated. If the digital signature and the hash value are both verified successfully, the authenticity verification index of the data associated with the blockchain of the firmware to be updated is output as 1, otherwise the output is 0.

[0023] It should be noted that the above hash value verification process is: using existing mature hash algorithms, such as SHA-256, to calculate the content of the firmware to be updated to convert it into a hash value of fixed length, and compare it with the reference hash value carried by the blockchain of the firmware to be updated. If the two are exactly the same, it means that the hash value verification is successful. If the two are different, it means that the hash value verification has failed.

[0024] The above-mentioned digital signature verification process includes a hash value verification process, that is, the reference hash value carried by the firmware blockchain to be updated is obtained by decrypting the digital signature carried by the firmware blockchain to be updated with the publisher's public key, and the successful digital signature verification also includes the verification of the publisher's public key. It is necessary to check the validity period of the public key certificate, the integrity of the certificate chain, and whether it has been revoked. If the hash value verification is successful and the public key verification is successful, it means that the digital signature verification is successful, otherwise it means that the digital signature verification has failed.

[0025] According to the hash pointer carried by the terminal node of the blockchain of the firmware to be updated, the upward node tracing operation is performed, and the hash value of the hash pointer memory of each node is verified one by one to see if it is consistent with the calculated hash value corresponding to the data content of the previous node. If there is any inconsistency, the integrity verification index of the data associated with the blockchain of the firmware to be updated is output as 0. If there is no inconsistency, the identifiers of the traceability nodes in the blockchain of the firmware to be updated are counted and compared with the preset authorized node whitelist of the target video surveillance device cluster firmware update operation stored in the WEB cloud. If the identifiers of the traceability nodes in the blockchain of the firmware to be updated are all in the authorized node whitelist of the target video surveillance device cluster firmware update operation, the integrity verification index of the data associated with the blockchain of the firmware to be updated is output as 1.

[0026] Specifically, the authenticity and integrity verification of the data associated with the to-be-updated firmware blockchain passes the condition that the output verification indicators of the authenticity and integrity of the data associated with the to-be-updated firmware blockchain are both 1.

[0027] The embodiment of the present invention verifies the authenticity and integrity of the data associated with the blockchain of the firmware to be updated before the unified firmware update of the target video surveillance device cluster, which not only effectively prevents false or tampered firmware from entering the update process, but also reduces problems such as update failure or device abnormality caused by data errors, greatly enhancing the security and stability of the firmware update of the video surveillance device cluster.

[0028] S2. Start the firmware update process of the target video surveillance device cluster, monitor the firmware update network environment status and firmware update device environment status of the target video surveillance device cluster in real time during the firmware update process, and evaluate the potential risk factor of the firmware update partition of the target video surveillance device cluster at each monitoring time point.

[0029] See also Figure 2 As shown, specifically, the evaluation of the potential risk coefficient of the firmware update partition of the target video surveillance device cluster at each monitoring time point includes: taking the time span between adjacent monitoring time points as the inspection period corresponding to the later monitoring time point in sequence.

[0030] Collect the number of connection interruptions, network bandwidth occupancy, network delay, network jitter and network packet loss rate of the target video surveillance equipment cluster firmware update network during the inspection period at each monitoring time point during the firmware update process, and compare them with the connection interruption number allowance threshold, network bandwidth occupancy reasonable range, network delay allowance threshold, network jitter allowance threshold and network packet loss rate allowance threshold preset in the firmware update network specification standard stored in the WEB cloud, and analyze the potential risk of the target video surveillance equipment cluster firmware update network environment at each monitoring time point ,in is the number of each monitoring time point, .

[0031] Collect the update progress, update breakpoint times, location of each update breakpoint and response time of each video surveillance device in the target video surveillance device cluster during the inspection period at each monitoring time point during the firmware update process, and analyze the potential risk of the firmware update device environment of the target video surveillance device cluster at each monitoring time point .

[0032] The potential risk degrees of the target video surveillance device cluster firmware update network environment and the firmware update device environment at each monitoring time point are accumulated to obtain the potential risk coefficient of the target video surveillance device cluster firmware update partition at each monitoring time point.

[0033] Specifically, the The specific analysis process includes: obtaining the number of connection interruptions, network bandwidth occupancy, network delay, network jitter and network packet loss rate of the target video surveillance device cluster firmware update network during the inspection period at each monitoring time point during the firmware update process, and the corresponding excess standard ratios, and accumulating them to obtain the potential risk degree of the target video surveillance device cluster firmware update network environment at each monitoring time point.

[0034] It should be noted that the method for obtaining the corresponding values ​​of the excess standard ratios of the number of connection interruptions, network delay, network jitter and network packet loss rate of the target video surveillance device cluster firmware update network during the inspection period corresponding to each monitoring time point in the above-mentioned firmware update process is consistent. Taking the example of the excess standard ratio of the number of connection interruptions, it is mainly achieved by subtracting the number of connection interruptions of the target video surveillance device cluster firmware update network during the inspection period corresponding to each monitoring time point in the firmware update process from the permitted threshold of the number of connection interruptions preset in the firmware update network specification, and comparing the calculated difference with 0. If the calculated difference is greater than 0, the calculated difference is further analyzed by ratio with the permitted threshold of the number of connection interruptions preset in the firmware update network specification to obtain the excess standard ratio of the number of connection interruptions. Conversely, if the calculated difference is less than or equal to 0, the excess standard ratio of the number of connection interruptions is directly set to 0, thereby obtaining the excess standard ratio of the number of connection interruptions of the target video surveillance device cluster firmware update network during the inspection period corresponding to each monitoring time point in the firmware update process.

[0035] The specific analysis process of the ratio of the network bandwidth occupancy rate exceeding the standard for the firmware update network of the target video surveillance device cluster during the inspection period at each monitoring time point in the firmware update process is as follows: extract the upper and lower limits of the reasonable interval of network bandwidth occupancy rate preset by the firmware update network specification standard and calculate the average to obtain the reasonable reference network bandwidth occupancy rate preset by the firmware update network specification standard; subtract the reasonable reference network bandwidth occupancy rate preset by the firmware update network specification standard from the lower limit of the reasonable interval of network bandwidth occupancy rate to obtain the reasonable deviation network bandwidth occupancy rate preset by the firmware update network specification standard; calculate the network bandwidth occupancy rate of the target video surveillance device cluster during the inspection period at each monitoring time point in the firmware update process The network bandwidth occupancy rate of the group firmware update network is subtracted from the reasonable reference network bandwidth occupancy rate preset by the firmware update network specification standard, and the calculated difference result is further compared with the reasonable deviation network bandwidth occupancy rate preset by the firmware update network specification standard for ratio analysis, and the calculated difference of the ratio analysis result and 1 is further compared with 0. If the calculated difference is greater than 0, the calculated difference is used as the ratio of the network bandwidth occupancy rate exceeding the specification standard. If the calculated difference is less than or equal to 0, the ratio of the network bandwidth occupancy rate exceeding the specification standard is set to 0, thereby obtaining the ratio of the network bandwidth occupancy rate exceeding the specification standard of the target video surveillance device cluster firmware update network during the inspection period corresponding to each monitoring time point during the firmware update process.

[0036] Specifically, the The specific analysis process includes: retrieving the maximum difference update process between the video surveillance devices in the target video surveillance device cluster during the inspection period corresponding to each monitoring time point during the firmware update process, and comparing it with the preset permission difference update process between the video surveillance devices stored in the WEB cloud. If the comparison relationship is less than or equal to, then the output target video surveillance device cluster firmware update device environment impact process continuous risk is 0; if the comparison relationship is greater than, then the output target video surveillance device cluster firmware update device environment impact process continuous risk is 1, thereby outputting the target video surveillance device cluster firmware update device environment impact process continuous risk at each monitoring time point.

[0037] According to the update breakpoint times of each video surveillance device in the target video surveillance device cluster during the inspection period corresponding to each monitoring time point during the firmware update process , the location of each update breakpoint and the response time of the resume transmission ,in is the number of each video surveillance device in the target video surveillance device cluster, , The number of each update breakpoint, According to the preset influence weights of each unit position point in the firmware update process of the video surveillance equipment stored in the WEB cloud, the preset influence weights corresponding to the positions of each update breakpoint of each video surveillance device in the target video surveillance device cluster during the inspection period corresponding to each monitoring time point in the firmware update process are obtained. , according to the formula Output the impact process stability risk of the target video surveillance device cluster firmware update device environment at each monitoring time point, where To update the breakpoint count, is the number of video surveillance devices in the target video surveillance device cluster, The number of permitted update breakpoints and the reasonable resume response time threshold are preset for the firmware update process of the video surveillance device in the target video surveillance device cluster stored in the WEB cloud.

[0038] The accumulated value of the risk affecting the continuity of the process and the risk affecting the stability of the process is taken as the potential risk, thereby obtaining the potential risk of the firmware update device environment of the target video surveillance device cluster at each monitoring time point.

[0039] S3. During the firmware update process, the video surveillance working status of each video surveillance device in the target video surveillance device cluster is monitored in real time, and the potential risk factor of the firmware working partition of the target video surveillance device cluster at each monitoring time point is evaluated.

[0040] Specifically, the evaluation of the potential risk coefficient of the firmware working partition of the target video surveillance device cluster at each monitoring time point includes: retrieving the working monitoring video of each video surveillance device in the target video surveillance device cluster during the inspection period corresponding to each monitoring time point, analyzing the display parameters of the working monitoring video, including the normal display video frame rate ratio , the comparison video angle area of ​​each normal display video frame , Image resolution , Image brightness and image contrast ,in is the number of each normally displayed video frame, , analyze the working monitoring video acquisition quality coefficient of each video surveillance device in the target video surveillance device cluster during the inspection period corresponding to each monitoring time point, and compare it with the preset standard working monitoring video acquisition quality coefficient threshold of the target video surveillance device cluster stored in the WEB cloud. Count the number of video surveillance devices in the target video surveillance device cluster whose working monitoring video acquisition quality does not meet the standard during the inspection period corresponding to each monitoring time point, and perform a ratio analysis with the total number of video surveillance devices in the target video surveillance device cluster to obtain the potential risk coefficient of the firmware working partition of the target video surveillance device cluster at each monitoring time point.

[0041] It should be noted that the specific analysis formula for the working monitoring video acquisition quality coefficient of each video monitoring device in the target video monitoring device cluster during the inspection period corresponding to each monitoring time point is: ,in To display the number of video frames normally, The standard comparison video angle area, standard image resolution, standard image brightness and standard image contrast are preset for the working monitoring video display specifications of the video monitoring devices in the target video monitoring device cluster stored in the WEB cloud respectively.

[0042] S4. Comprehensively consider the potential risk factors of the firmware working partition and the firmware update partition, assess the firmware update risk level of the target video surveillance device cluster at each monitoring time point, and take corresponding control measures.

[0043] Specifically, the firmware update risk level of the target video surveillance device cluster at each monitoring time point is assessed, including: accumulating the potential risk coefficients of the firmware working partition and firmware update partition of the target video surveillance device cluster at each monitoring time point with the product of their corresponding preset weights, to obtain the comprehensive firmware update risk coefficient of the target video surveillance device cluster at each monitoring time point.

[0044] According to the preset high, medium and low risk levels of the target video surveillance device cluster firmware update stored in the WEB cloud, the firmware update comprehensive risk coefficient intervals are respectively corresponded, and the firmware update comprehensive risk coefficient of the target video surveillance device cluster at each monitoring time point is arranged in the interval to assess the firmware update risk level of the target video surveillance device cluster at each monitoring time point.

[0045] It should be noted that the specific process of taking corresponding control measures for the firmware update risk level of the target video surveillance device cluster at each monitoring time point is as follows: if the firmware update risk level of the target video surveillance device cluster at a certain monitoring time point is a low risk level, the firmware update process will continue, but the monitoring frequency will be increased; if the firmware update risk level of the target video surveillance device cluster at a certain monitoring time point is a medium risk level, the firmware update process will be suspended, and each video surveillance device in the target video surveillance device cluster will conduct a detailed self-inspection of the current status and generate a report and upload it to the management center; if the firmware update risk level of the target video surveillance device cluster at a certain monitoring time point is a high risk level, the firmware update will be terminated immediately, and the device's security rollback mechanism will be initiated to restore the device firmware to the stable version before the update.

[0046] The embodiment of the present invention unifies the firmware update process of the firmware video surveillance device cluster, comprehensively considers the potential risk factors of the firmware working partition and the firmware update partition, and dynamically assesses the firmware update risk level of the target video surveillance device cluster at each monitoring time point, so as to take corresponding management and control measures, comprehensively and deeply understand the risk status in the entire update process, and greatly improve the security and controllability of the firmware update process of the video surveillance device cluster.

[0047] See also Figure 3 As shown, S5. After the unified firmware update of the target video surveillance device cluster is completed, a stability test and a compatibility test are performed on the target video surveillance device cluster, and each abnormal video surveillance device is screened, placed in a safe isolation mode, and reported to the management center.

[0048] Specifically, the stability test and compatibility test for the target video surveillance device cluster include: sending a stability self-test data packet and a compatibility self-test data packet to each video surveillance device in the target video surveillance device cluster, wherein the stability self-test data packet contains video stream simulation data, network stress simulation data and control instruction test data, and the compatibility self-test data packet contains storage device identification instruction data and operation unit identification instruction data, parsing the stability self-test performance and compatibility self-test performance of each video surveillance device in the target video surveillance device cluster, and outputting the stable operation level index and compatible operation level index of each video surveillance device in the target video surveillance device cluster after the firmware is updated, so as to realize the stability test and compatibility test of the target video surveillance device cluster.

[0049] It should be noted that the above-mentioned video stream simulation data includes video streams under various video configuration parameter combinations, wherein each video configuration parameter combination is mainly obtained by randomly matching and combining each preset resolution, each preset frame rate and each preset encoding format. For example, each preset resolution is such as 720p, 1080p, 4K, each preset frame rate is such as 15fps, 30fps, 60fps, and each encoding format is such as H.264 and H.265. The network pressure simulation data includes network pressure scenarios under various network configuration parameter combinations, wherein each network configuration parameter combination is mainly obtained by randomly matching and combining each preset network bandwidth, each preset network delay and each preset network packet loss rate. For example, each preset network bandwidth is such as 1Mbps, 10Mbps, 100Mbps, each preset network delay is such as 100ms, 500ms, 1000ms, and each preset network packet loss rate is such as 1%, 5%, 10%. The control command test data includes various equipment control function commands, such as pan / tilt control commands, video parameter adjustment commands, video recording commands, and video playback commands.

[0050] The above-mentioned storage device identification instruction data includes various storage device simulation driver interface data, various storage devices such as SATA hard drives, NVMe solid-state drives, and network storage devices. The operation unit identification instruction data includes various operation unit simulation call data, various operation units such as Linux and Windows Embedded.

[0051] It should also be noted that the specific output process of the stable operation level index of each video surveillance device in the above-mentioned target video surveillance device cluster after the firmware is updated is as follows: after each video surveillance device in the target video surveillance device cluster receives the stability self-test data packet, the test performance content of each video surveillance device for the video stream simulation data is collected, including the smoothness index and display quality index of the video stream under each video configuration parameter combination, and the cumulative value of the smoothness index and the display quality index is used as the basic stable playback index, and the basic stable playback index of the video stream under each video configuration parameter combination is accumulated with the product of its corresponding preset weight to obtain the stable playback index of each video surveillance device for the video stream simulation data. It should be noted in particular that the above-mentioned smoothness index mainly examines the actual frame rate fluctuation degree, the actual playback jamming degree and the actual number of frame losses, and the display quality index mainly examines the number of screen distortions in the playback screen and the area proportion of each screen distortion.

[0052] The test performance of each video surveillance device for network stress simulation data is collected, including the connection stability, data transmission accuracy and data transmission integrity for network stress scenarios under each network configuration parameter combination. The cumulative value of the connection stability, data transmission accuracy and data transmission integrity is used as the basic network operation stability index. The basic network operation stability index under each network configuration parameter combination is accumulated with the product of its corresponding preset weight to obtain the stable operation index of each video surveillance device for network stress simulation data.

[0053] The test performance content of each video surveillance device for control command test data is collected, including the response timeliness and response accuracy for each type of device control function command, and the accumulated value of the response timeliness and response accuracy is used as the basic response stability index. The basic response stability index of each type of device control function command is accumulated with the product of its corresponding preset weight to obtain the stable response index of each video surveillance device for control command test data.

[0054] The stable playback indicators of each video surveillance device for video stream simulation data, the stable operation indicators for network stress simulation data, and the stable response indicators for control instruction test data are accumulated and standardized to output the stable operation level indicators of each video surveillance device in the target video surveillance device cluster after the firmware is updated.

[0055] The specific output process of the compatible operation level index of each video surveillance device in the above-mentioned target video surveillance device cluster after the firmware is updated is as follows: after each video surveillance device in the target video surveillance device cluster receives the compatibility self-test data packet, the test performance content of each video surveillance device for the storage device identification instruction data is collected, including the connection success rate, recognition success rate and data read and write operation accuracy of the simulated driver interface data for each type of storage device, and the cumulative multiplication result of the connection success rate, recognition success rate and data read and write operation accuracy is used as the basic driver compatibility index, and the basic driver compatibility index of the simulated driver interface data of each type of storage device is respectively accumulated with the product of its corresponding preset weight to obtain the test compatibility index of each video surveillance device for the storage device identification instruction data.

[0056] The test performance content of each video surveillance device for operation unit recognition instruction data is collected, including the normal response degree and normal operation degree for each type of operation unit simulation call data, and the cumulative multiplication result of the normal response degree and the normal operation degree is used as the basic operation compatibility index, and the basic operation compatibility index of each type of operation unit simulation call data is respectively accumulated with the product of its corresponding preset weight to obtain the test compatibility index of each video surveillance device for operation unit recognition instruction data.

[0057] The test compatibility index of each video surveillance device for storage device identification instruction data and operation unit identification instruction data is accumulated and standardized to output the compatible operation level index of each video surveillance device in the target video surveillance device cluster after the firmware is updated.

[0058] Specifically, the screening condition for each abnormal video surveillance device is that the stable operation level index after the firmware update is less than the preset benchmark stable operation level index reaching the standard threshold of the WEB cloud storage or the compatible operation level index is less than the preset benchmark compatible operation level index reaching the standard threshold of the WEB cloud storage.

[0059] After the unified firmware update of the firmware video surveillance device cluster is completed, the embodiment of the present invention performs stability testing and compatibility testing on the target video surveillance device cluster to screen out abnormal video surveillance devices for reporting, which is not only conducive to improving the maintenance efficiency of the equipment and reducing maintenance costs, but also can ensure that the video surveillance device cluster can work together after the firmware update, seamlessly connect to the existing monitoring system, and give full play to its due monitoring efficiency.

[0060] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A security protection method for an intelligent video surveillance system, characterized in that: include: S1. Receive the unified firmware update instruction of the target video surveillance device cluster, verify the authenticity and integrity of the data associated with the firmware blockchain to be updated, and if the verification passes, execute step S2; if the verification fails, reject the unified firmware update instruction; S2. Start the firmware update process of the target video surveillance device cluster, monitor the network environment status and the firmware update device environment status of the target video surveillance device cluster in real time during the firmware update process, and evaluate the potential risk factor of the firmware update partition of the target video surveillance device cluster at each monitoring time point; S3. Real-time monitoring of the video surveillance working status of each video surveillance device in the target video surveillance device cluster during the firmware update process, and evaluation of the potential risk factor of the target video surveillance device cluster firmware work partition at each monitoring time point; S4. Comprehensively consider the potential risk factors of the firmware working partition and the firmware update partition, assess the firmware update risk level of the target video surveillance device cluster at each monitoring time point, and take corresponding control measures; S5. After the unified firmware update of the target video surveillance device cluster is completed, stability test and compatibility test are performed on the target video surveillance device cluster, and each abnormal video surveillance device is screened, placed in a safe isolation mode and reported to the management center.

2. The intelligent video surveillance system security protection method according to claim 1, characterized in that: The verification of the authenticity and integrity of the data associated with the blockchain of the firmware to be updated includes: performing digital signature verification and hash value verification on the terminal node of the blockchain of the firmware to be updated, and if both the digital signature and the hash value are verified successfully, the authenticity verification index of the data associated with the blockchain of the firmware to be updated is output as 1, otherwise the output is 0; According to the hash pointer carried by the terminal node of the blockchain of the firmware to be updated, the upward node tracing operation is performed, and the hash value of the hash pointer memory of each node is verified one by one to see if it is consistent with the calculated hash value corresponding to the data content of the previous node. If there is any inconsistency, the integrity verification index of the data associated with the blockchain of the firmware to be updated is output as 0. If there is no inconsistency, the identifiers of the traceability nodes in the blockchain of the firmware to be updated are counted and compared with the preset authorized node whitelist of the target video surveillance device cluster firmware update operation stored in the WEB cloud. If the identifiers of the traceability nodes in the blockchain of the firmware to be updated are all in the authorized node whitelist of the target video surveillance device cluster firmware update operation, the integrity verification index of the data associated with the blockchain of the firmware to be updated is output as 1.

3. The intelligent video surveillance system security protection method according to claim 2, characterized in that: The authenticity and integrity verification of the data associated with the firmware blockchain to be updated passes the condition that the output verification indicators of the authenticity and integrity of the data associated with the firmware blockchain to be updated are both 1.

4. The intelligent video surveillance system security protection method according to claim 1, characterized in that: The step of evaluating the potential risk coefficient of the firmware update partition of the target video surveillance device cluster at each monitoring time point includes: taking the time span between adjacent monitoring time points as the inspection period corresponding to the later monitoring time point in the time sequence; Collect the number of connection interruptions, network bandwidth occupancy, network delay, network jitter and network packet loss rate of the target video surveillance equipment cluster firmware update network during the inspection period at each monitoring time point during the firmware update process, and compare them with the connection interruption number allowance threshold, network bandwidth occupancy reasonable range, network delay allowance threshold, network jitter allowance threshold and network packet loss rate allowance threshold preset in the firmware update network specification standard stored in the WEB cloud, and analyze the potential risk of the target video surveillance equipment cluster firmware update network environment at each monitoring time point ,in is the number of each monitoring time point, ; Collect the update progress, update breakpoint times, location of each update breakpoint and response time of each video surveillance device in the target video surveillance device cluster during the inspection period at each monitoring time point during the firmware update process, and analyze the potential risk of the firmware update device environment of the target video surveillance device cluster at each monitoring time point ; The potential risk degrees of the target video surveillance device cluster firmware update network environment and the firmware update device environment at each monitoring time point are accumulated to obtain the potential risk coefficient of the target video surveillance device cluster firmware update partition at each monitoring time point.

5. The intelligent video surveillance system security protection method according to claim 4, characterized in that: Said The specific analysis process includes: obtaining the number of connection interruptions, network bandwidth occupancy, network delay, network jitter and network packet loss rate of the target video surveillance device cluster firmware update network during the inspection period at each monitoring time point during the firmware update process, and the corresponding excess standard ratios, and accumulating them to obtain the potential risk degree of the target video surveillance device cluster firmware update network environment at each monitoring time point.

6. The intelligent video surveillance system security protection method according to claim 4, characterized in that: Said The specific analysis process includes: retrieving the maximum difference update process between the video surveillance devices in the target video surveillance device cluster during the inspection period at each monitoring time point during the firmware update process, comparing it with the preset permission difference update process between the video surveillance devices stored in the WEB cloud, and outputting the continuous risk degree of the impact process of the firmware update device environment of the target video surveillance device cluster at each monitoring time point; According to the update breakpoint times, positions of each update breakpoint and the response time of the retransmission of each video surveillance device in the target video surveillance device cluster during the inspection period corresponding to each monitoring time point during the firmware update process, the impact process stability risk of the firmware update device environment of the target video surveillance device cluster at each monitoring time point is output; The accumulated value of the risk affecting the continuity of the process and the risk affecting the stability of the process is taken as the potential risk, thereby obtaining the potential risk of the firmware update device environment of the target video surveillance device cluster at each monitoring time point.

7. The intelligent video surveillance system security protection method according to claim 4, characterized in that: The method for evaluating the potential risk coefficient of the firmware working partition of the target video surveillance device cluster at each monitoring time point includes: retrieving the working surveillance video of each video surveillance device in the target video surveillance device cluster within the inspection period corresponding to each monitoring time point, parsing the display parameters of the working surveillance video, including the normal display video frame rate ratio, the comparison video angle area of ​​each normal display video frame, the image resolution, the image brightness and the image contrast, analyzing the working surveillance video acquisition quality coefficient of each video surveillance device in the target video surveillance device cluster within the inspection period corresponding to each monitoring time point, comparing it with the preset standard working surveillance video acquisition quality coefficient reaching threshold of the target video surveillance device cluster stored in the WEB cloud, counting the number of video surveillance devices in the target video surveillance device cluster whose working surveillance video acquisition quality does not reach the standard within the inspection period corresponding to each monitoring time point, and performing ratio analysis with the total number of video surveillance devices in the target video surveillance device cluster to obtain the potential risk coefficient of the firmware working partition of the target video surveillance device cluster at each monitoring time point.

8. The intelligent video surveillance system security protection method according to claim 7, characterized in that: The step of assessing the firmware update risk level of the target video surveillance device cluster at each monitoring time point includes: accumulating the potential risk coefficients of the firmware working partition and the firmware update partition of the target video surveillance device cluster at each monitoring time point and multiplying them by their corresponding preset weights to obtain the comprehensive firmware update risk coefficient of the target video surveillance device cluster at each monitoring time point; According to the preset high, medium and low risk levels of the target video surveillance device cluster firmware update stored in the WEB cloud, the firmware update comprehensive risk coefficient intervals are respectively corresponded, and the firmware update comprehensive risk coefficient of the target video surveillance device cluster at each monitoring time point is arranged in the interval to assess the firmware update risk level of the target video surveillance device cluster at each monitoring time point.

9. The intelligent video surveillance system security protection method according to claim 1, characterized in that: The stability test and compatibility test for the target video surveillance device cluster include: sending a stability self-test data packet and a compatibility self-test data packet to each video surveillance device in the target video surveillance device cluster, wherein the stability self-test data packet contains video stream simulation data, network pressure simulation data and control instruction test data, and the compatibility self-test data packet contains storage device identification instruction data and operation unit identification instruction data, parsing the stability self-test performance and compatibility self-test performance of each video surveillance device in the target video surveillance device cluster, and outputting the stable operation level index and compatible operation level index of each video surveillance device in the target video surveillance device cluster after the firmware is updated, so as to realize the stability test and compatibility test of the target video surveillance device cluster.

10. The intelligent video surveillance system security protection method according to claim 9, characterized in that: The screening condition for each abnormal video surveillance device is that the stable operation level index after the firmware update is less than the preset benchmark stable operation level index reaching the standard threshold of the WEB cloud storage or the compatible operation level index is less than the preset benchmark compatible operation level index reaching the standard threshold of the WEB cloud storage.

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