Water conservancy video monitoring safety protection method, system and equipment

Abstract

The invention discloses a water conservancy video monitoring security protection method, system and device. The method comprises the steps of intelligent contract management device authentication of an alliance block chain architecture and decentralized distributed security access control. Selecting a self-adaptive compression algorithm according to spatial-temporal characteristics and information entropy analysis of video contents, and adjusting compression parameters in real time; constructing a double-layer encrypted video transmission mechanism based on a block chain consensus mechanism and a dynamic key derivation algorithm of a high-precision timestamp; based on a distributed hierarchical storage strategy of the block chain, executing a hybrid mechanism of local cache and block chain distributed storage; and constructing a timeliness cloud edge cooperative control mechanism. Through deep fusion of edge calculation and a block chain technology, safe access, efficient processing, encrypted transmission, anomaly detection and reliable storage of video monitoring data are realized, and the data credibility and tamper-proof capability of reservoir safety monitoring and the overall system safety are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of water conservancy safety monitoring technology, and more specifically to a water conservancy video monitoring security protection method, system and equipment. Background Technology

[0002] As crucial water conservancy infrastructure, reservoir safety monitoring is of paramount importance for flood control, disaster reduction, water resource allocation, and project safety. Reservoirs are typically located in remote areas, facing threats from various natural disasters and human-caused damage, such as torrential floods, landslides, and terrorist attacks. Therefore, an efficient and reliable video surveillance system is essential for timely detection of anomalies and activation of emergency response plans. However, existing traditional water conservancy video surveillance systems have significant shortcomings in data security and reliability, making it difficult to cope with increasingly complex cybersecurity threats and monitoring needs under extreme weather conditions. The main problems are as follows: (1) Vulnerability of centralized security architecture: Most existing reservoir monitoring systems adopt a centralized management model, which poses a risk of single point of failure. Once the central node is attacked, the security of the entire system will face a serious threat. (2) Weak security mechanism for video data transmission: Traditional systems lack effective encryption mechanisms during video data transmission, making them vulnerable to man-in-the-middle attacks, data theft and tampering, and unable to guarantee the authenticity and integrity of monitoring data; (3) Limited ability to detect abnormal behavior: The existing system mainly relies on fixed rules to detect security threats such as abnormal network traffic and unauthorized access, which is difficult to deal with complex and ever-changing attack methods. Especially when the system load increases dramatically under extreme weather conditions, the security protection capability is even more insufficient. (4) Imperfect data storage and recovery mechanism: In the event of network interruption or system failure, there is a lack of effective data consistency guarantee and recovery mechanism, which may result in the loss or tampering of monitoring data, affecting the accuracy and timeliness of emergency decision-making.

[0003] Therefore, an innovative technical architecture is urgently needed to improve the security and operational stability of water conservancy video monitoring systems. Summary of the Invention

[0004] The present invention provides a water conservancy video monitoring security protection method, system and equipment that effectively improves the data reliability, anti-tampering capability and overall system security of reservoir safety monitoring, and can solve at least one of the above-mentioned technical problems.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A method for security protection of water conservancy video surveillance includes the following steps: S1. A smart contract management device authentication mechanism based on a consortium blockchain architecture, combined with asymmetric encrypted digital certificate verification and device unique identifier verification, to achieve decentralized distributed secure access control. S2. Based on the spatiotemporal characteristics and information entropy analysis of the video content, select an adaptive compression algorithm and adjust the compression parameters in real time. Implement differentiated processing strategies based on the importance level of the monitored area, and store the processed metadata on the blockchain through a hash algorithm. S3. Based on the blockchain consensus mechanism and high-precision timestamp dynamic key derivation algorithm, the video stream is encrypted in layers and segments, and the feature values ​​are recorded in the blockchain to build a multi-layered encrypted secure transmission channel. S4. Based on blockchain, a distributed hierarchical storage strategy is implemented, which combines local high-speed caching with blockchain distributed storage, and provides automatic protection against network outages and data consistency synchronization based on smart contracts. S5. Construct a timely cloud-edge collaborative control mechanism. The cloud platform issues encrypted commands with ECDSA digital signatures and precise validity period identifiers through multiple channels. Edge devices perform multi-level cryptographic verification and execution based on command priority and timeliness, and record the execution results on the blockchain after hash processing.

[0006] Furthermore, S1 further includes: S11. Assign a globally unique identifier to each monitoring device and generate an asymmetric key pair. Submit the device information to the blockchain network. After multi-node consensus verification, write it into the distributed ledger. At the same time, the consortium blockchain certification center issues a digital certificate containing the device identity information to establish a trusted digital identity for the device on the blockchain. S12. After receiving the video stream access request from the monitoring device, the edge node extracts the device identifier, digital signature and timestamp, triggers the execution of the authentication smart contract, and the contract automatically retrieves the device registration information from the blockchain ledger and ensures that the access device is authentic and trustworthy by verifying at least the validity of the digital certificate, the authenticity of the signature and the device's operating status through multiple dimensions. S13. The smart contract automatically assigns differentiated permission levels based on the importance of the area where the monitoring equipment is located, generates an access token containing permission information and validity period, signs it with a blockchain timestamp, records the authorization event on the chain, realizes decentralized access control based on blockchain, and ensures the security of monitoring data in key areas. S14. Implement certificate lifecycle management and exception handling mechanisms, support the periodic rotation of certificates with multiple administrators and multi-signatures, and real-time synchronization of revocation lists. At the same time, record the complete authentication process on the blockchain to form an immutable audit log, establish authentication event correlation analysis capabilities, provide cross-domain authentication interoperability support, and ensure that the entire authentication process is secure, controllable, and fully traceable.

[0007] Furthermore, S2 further includes: S21. Based on the spatiotemporal characteristics and information entropy analysis results of the video stream, construct video content feature vectors, evaluate video complexity through the deep learning model of edge computing nodes, automatically select the optimal compression algorithm for different feature types, calculate the best compression parameters in real time, and dynamically adjust the encoding configuration according to network conditions and computing resources to ensure the highest compression efficiency while preserving key visual information. S22. To ensure the credibility and immutability of the video processing process, the system calculates a feature value for the processing metadata of each video stream using a hash algorithm, and submits this feature value along with a processing configuration summary to the blockchain network for notarization. After verification by a smart contract, it is written into the distributed ledger to form a credible timeline of processing history. At the same time, a video processing metadata indexing mechanism is established to support the query and verification of the processing history of videos within a specific time period through the blockchain, realizing the traceability of the entire life cycle of video data, providing technical protection for the legal validity and integrity of subsequent video content, and preventing the video processing process from being maliciously tampered with.

[0008] Furthermore, in S3, a two-layer encrypted video transmission mechanism is constructed based on the blockchain consensus mechanism and the dynamic key derivation algorithm with high-precision timestamps. The construction process is as follows: the edge device generates a random session key to encrypt the video data, then uses the cloud platform's public key to encrypt the session key, packages it and sends it to the cloud platform, the cloud platform uses its private key to decrypt and obtain the session key, and then decrypts the video data. The key feature value of the entire encryption channel is recorded in the blockchain to ensure that it cannot be tampered with.

[0009] Furthermore, S3 further includes: S31. Based on the consensus timestamp and unique device identifier of the blockchain network, a dynamic key derivation algorithm is implemented. The latest block hash value of the blockchain is cryptographically combined with the device private key and high-precision timestamp to generate a master key seed. A hierarchical key tree is derived from the master key seed through a key derivation function, including video content encryption key, metadata encryption key and authentication key. An automatic key rotation mechanism is implemented to ensure that even if a single key is leaked, it will not endanger the overall system security. At the same time, according to the sensitivity level of the video content, different strength encryption algorithms and encryption modes are adopted to build a layered encryption system that adapts to different security needs. The key usage record is stored on the chain through zero-knowledge proof to ensure that the key management process is auditable but does not disclose the actual content of the key. S32. Dynamically segment the video stream according to fixed time intervals or scene change thresholds, and encrypt each video segment independently to ensure that even if a single segment is cracked, it will not affect the security of other segments. Generate a unique identifier and integrity verification value for each encrypted video segment, construct segment metadata containing encryption parameters, timestamps, and integrity hashes, organize the feature hash values ​​of all video segments through a Merkle tree structure, and submit only the Merkle root hash and key node hashes to the blockchain storage. This reduces the storage pressure on the blockchain while ensuring data integrity and verifiability. Design a smart contract to automatically verify the Merkle proof path of newly submitted video segments, ensure that the Merkle proof path is consistent with the on-chain root hash, and record the verification results on the blockchain. S33. Integrating TLS / SSL protocols and blockchain zero-knowledge proof technology, a multi-layered secure transmission channel is constructed, with the following construction process: S331. Establish a TLS-based encrypted communication tunnel and use strong cryptographic suites to ensure transport layer security. S332. Implement a two-way authentication mechanism based on blockchain identity at the application layer, verifying that both communicating parties hold the correct blockchain identity private key through zero-knowledge proof without exposing the private key itself. S333. Design a transmission session binding mechanism to associate each transmission session with an authorization record on the blockchain, ensuring that only authorized sessions can receive specific video streams. S334. Implement end-to-end data integrity verification. The receiving end verifies the consistency between the video segment hash and the blockchain record to confirm that the data has not been tampered with.

[0010] Furthermore, S4 further includes: S41. Construct a multi-tiered hybrid storage architecture. The specific construction process is as follows: S411: Edge nodes provide local high-speed caching, regional nodes are responsible for medium-term storage backup, the cloud enables long-term archiving, and the blockchain stores key metadata and evidence hashes. S412: Data flow between different storage tiers is automatically coordinated through intelligent strategies; S413. Implement a network outage protection mechanism, switching to local emergency storage mode and increasing the sampling rate when the network is interrupted; S414. After the network is restored, key data is transmitted incrementally and its integrity is verified. S415. Deploy a distributed data recovery mechanism, using blockchain records to reconstruct data from distributed nodes in disaster scenarios, ensuring system availability under extreme conditions; S42. Based on blockchain, implement fine-grained data access control. Smart contracts define different role permissions. All data access operations are recorded on the chain to form an immutable log, realizing attribute-based encrypted access control, ensuring the security of sensitive data, providing comprehensive data usage auditing functions, supporting the tracking of the complete access history of video clips, automatically checking the compliance of data operations through smart contracts, ensuring compliance with security policies and regulatory requirements, and building a comprehensive data protection and traceability system.

[0011] Furthermore, S5 further includes: S51, the cloud platform uses a zero-trust security model to generate dynamic security control instructions, including temporary authorization credentials, encryption key rotation parameters and security policy updates. Each instruction is embedded with a high-precision timestamp and validity period limit, and is signed by an elliptic curve digital signature algorithm to ensure that the instruction itself cannot be forged or tampered with. S52. After receiving the instruction, the edge device implements a multi-level verification mechanism. First, it verifies the cryptographic correctness of the instruction's digital signature. Then, it checks whether the timestamp is within the trusted time window. Finally, it verifies whether the instruction conforms to the preset security policy. Only instructions that pass all verifications can be executed, ensuring that the edge device will not execute expired or forged security instructions, thereby preventing replay attacks and man-in-the-middle attacks. S53. After the edge device executes the security command, the execution result is recorded in a verifiable encrypted manner, including the command execution time, details of security configuration changes and system status changes. These records are written into the distributed ledger after being hashed to establish a complete security operation audit chain. At the same time, the system regularly performs security command compliance checks to ensure that the cloud-edge security configuration remains consistent and timely.

[0012] A water conservancy video surveillance security protection system, applicable to the water conservancy video surveillance security protection method, includes a three-layer structure: a top layer, a middle layer, and a bottom layer. The top layer is a video surveillance equipment layer, the middle layer is an edge computing layer, and the bottom layer is a cloud platform layer. The data collected by the video surveillance equipment layer is processed by the edge computing layer and then securely interacts with the cloud platform layer.

[0013] Furthermore, the video surveillance equipment layer includes multiple video surveillance devices, which are used to collect video data from various areas of the reservoir and transmit the video streams to edge devices for processing. The edge computing layer, as the core processing unit, includes six key functional modules: a transmission module, an interface module, a computing unit, a storage unit, a clock synchronization module, and a security encryption module. The transmission module is used to receive video stream data, the interface module is used to process device communication, the computing unit is used to perform data analysis and feature extraction, the storage unit is used to provide local data caching, the clock synchronization module is used to ensure system time consistency, and the security encryption module is used to protect data. In the cloud platform layer, a two-way communication channel is established between the cloud platform and the edge devices. Uplink, encrypted and compressed video streams and video warning information are transmitted, while downlink, dynamic instructions and time limits issued by the cloud platform are received. The cloud platform layer has three core functional components: instruction timeliness verification, private key management, and a distributed storage coordinator. The instruction timeliness verification is used to ensure the security and validity of instructions. The private key management is used to ensure the security of encrypted communication in the system. The distributed storage coordinator is used to realize efficient distributed storage and management of data.

[0014] A computer device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the above-described water conservancy video monitoring security protection method.

[0015] The beneficial effects of this invention are reflected in: 1. This invention achieves decentralized secure access control by constructing a distributed device authentication mechanism based on consortium blockchain and combining it with asymmetric encryption. Compared with traditional centralized authentication methods, it significantly improves the system's resistance to attacks and reduces the risk of single points of failure.

[0016] 2. This invention dynamically selects an adaptive compression algorithm based on the spatiotemporal characteristics and information entropy analysis of video content, and stores the processed metadata on the blockchain through a hash algorithm, thus achieving an organic combination of efficient video processing and data anti-tampering, reducing transmission bandwidth usage while ensuring video quality.

[0017] 3. This invention achieves layered and segmented encryption of video streams by adopting a dynamic key derivation algorithm based on blockchain consensus mechanism and high-precision timestamps. Compared with traditional fixed-key encryption schemes, it significantly improves encryption strength and resistance to quantum computing attacks.

[0018] 4. This invention combines advanced cryptographic technologies such as high-precision timestamps and ECDSA digital signatures with blockchain smart contracts to construct a complete spatiotemporal security proof system, effectively preventing common security threats such as replay attacks and man-in-the-middle attacks.

[0019] 5. The verification execution mechanism based on instruction priority and timeliness implemented in this invention ensures the consistent execution of security control policies across multiple levels of edge devices, avoiding common security policy conflicts and update delays in traditional systems.

[0020] 6. This invention implements a blockchain-based distributed hierarchical storage strategy, executes a hybrid mechanism of local high-speed caching and blockchain distributed storage, and provides automatic network outage protection and data consistency synchronization functions based on smart contracts, ensuring the stable operation of the monitoring system around the clock. Attached Figure Description

[0021] The accompanying drawings, which are provided to further illustrate this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application.

[0022] Figure 1 This is a schematic diagram of the overall architecture of the water conservancy video monitoring security protection system according to an embodiment of the present invention.

[0023] Figure 2 This is a schematic diagram of the overall process of the water conservancy video monitoring security protection method according to an embodiment of the present invention.

[0024] Figure 3 This is a schematic diagram illustrating the specific process of the water conservancy video monitoring security protection method according to an embodiment of the present invention.

[0025] Figure 4 This is a structural block diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] It should be noted that the meaning of "and / or" throughout the text includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or a solution that simultaneously satisfies A and B. Furthermore, "multiple" refers to two or more. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0028] See Figure 1 This invention provides a water conservancy video surveillance security protection system, which includes a three-layer structure: a top layer, a middle layer, and a bottom layer. The top layer is a video surveillance equipment layer, the middle layer is an edge computing layer, and the bottom layer is a cloud platform layer. The data collected by the video surveillance equipment layer is processed by the edge computing layer and then interacts securely with the cloud platform layer.

[0029] This system makes full use of edge computing technology to reduce network transmission pressure and improve real-time processing capabilities. At the same time, it ensures the security, reliability and efficiency of the water conservancy video monitoring system through multi-layer security mechanisms, making it particularly suitable for the security protection needs of critical infrastructure such as reservoirs.

[0030] In this embodiment, the video surveillance equipment layer includes multiple video surveillance devices (video surveillance 1 to video surveillance n), which are used to collect video data from various areas of the reservoir and transmit the video streams to edge devices for processing. The edge computing layer, as the core processing unit, includes six key functional modules: a transmission module, an interface module, a computing unit, a storage unit, a clock synchronization module, and a security encryption module. The transmission module is used to receive video stream data, the interface module is used to process device communication, the computing unit is used to perform data analysis and feature extraction, the storage unit is used to provide local data caching, the clock synchronization module is used to ensure system time consistency, and the security encryption module is used to protect data. In the cloud platform layer, a two-way communication channel is established between the cloud platform and the edge devices. Uplink, encrypted and compressed video streams and video warning information are transmitted, while downlink, dynamic instructions and time limits issued by the cloud platform are received. The cloud platform layer has three core functional components: instruction timeliness verification, private key management, and a distributed storage coordinator. The instruction timeliness verification is used to ensure the security and validity of instructions. The private key management is used to ensure the security of encrypted communication in the system. The distributed storage coordinator is used to realize efficient distributed storage and management of data.

[0031] Blockchain technology plays a crucial role in this system. The entire data processing flow begins with a consortium blockchain authentication process, ensuring that all connected devices and data sources are verified in a trusted manner. The system then prioritizes monitoring areas based on their security levels, implementing differentiated monitoring and storage strategies for areas of varying importance. The system generates unique identifiers for video data through hash calculations, guaranteeing data integrity and preventing tampering. The processed data is securely stored using a hybrid distributed storage mechanism, ensuring both high availability and improved access efficiency.

[0032] After the cloud platform issues encrypted commands, the system automatically verifies the validity of the commands from the edge device, forming a two-way verification mechanism. If the verification is successful, the cloud platform confirms receipt and records it on the blockchain, generating an immutable execution proof on the blockchain; if the verification fails, the system refuses to accept the command, reports the anomaly to the cloud platform, and actively requests new commands, forming a complete security loop.

[0033] The introduction of blockchain technology not only solves the problem of ensuring the authenticity and integrity of data in traditional video surveillance systems, but also realizes the trusted verification of the entire process of device authentication, data storage and instruction execution through distributed ledger and smart contract mechanisms, which greatly improves the security protection capabilities and reliability of video surveillance systems for critical infrastructure such as reservoirs.

[0034] See Figures 2-3 This invention also provides a water conservancy video surveillance security protection method, implemented using the aforementioned water conservancy video surveillance security protection system, comprising the following steps: S1. A smart contract management device authentication mechanism based on a consortium blockchain architecture, combined with asymmetric encrypted digital certificate verification and device unique identifier verification, to achieve decentralized distributed secure access control. S2. Based on the spatiotemporal characteristics and information entropy analysis of the video content, select an adaptive compression algorithm and adjust the compression parameters in real time. Implement differentiated processing strategies based on the importance level of the monitored area, and store the processed metadata on the blockchain through a hash algorithm. S3. Based on the blockchain consensus mechanism and high-precision timestamp dynamic key derivation algorithm, the video stream is encrypted in layers and segments, and the feature values ​​are recorded in the blockchain to build a multi-layered encrypted secure transmission channel. S4. Based on blockchain, a distributed hierarchical storage strategy is implemented, which combines local high-speed caching with blockchain distributed storage, and provides automatic protection against network outages and data consistency synchronization based on smart contracts. S5. Construct a timely cloud-edge collaborative control mechanism. The cloud platform issues encrypted commands with ECDSA digital signatures and precise expiration dates through multiple channels. Edge devices perform multi-level cryptographic verification and execution based on command priority and timeliness, and record the execution results on the blockchain after hash processing. These dynamic commands can adjust video processing parameters, update encryption strategies, manage key lifecycles, and perform remote security repairs in real time according to the security situation. This ensures that the system maintains security and controllability in a changing threat environment, and also makes all operations verifiable and traceable through distributed ledger technology, forming a complete security audit chain.

[0035] In this embodiment, S1 further includes: S11. Assign a globally unique identifier to each monitoring device and generate an asymmetric key pair. Submit the device information (such as GUID, public key, type, and location) to the blockchain network. After multi-node consensus verification, write it into the distributed ledger. At the same time, the consortium blockchain certification center issues a digital certificate containing the device identity information to establish a trusted digital identity for the device on the blockchain. S12. After receiving the video stream access request from the monitoring device, the edge node extracts the device identifier, digital signature and timestamp, triggers the execution of the authentication smart contract, and the contract automatically retrieves the device registration information from the blockchain ledger and ensures that the access device is authentic and trustworthy by verifying at least the validity of the digital certificate, the authenticity of the signature and the device's operating status through multiple dimensions. S13. The smart contract automatically assigns differentiated permission levels based on the importance of the area where the monitoring equipment is located (such as the core area of ​​the dam or a general area), generates an access token containing permission information and validity period, signs it with a blockchain timestamp, records the authorization event on the chain, realizes decentralized access control based on blockchain, and ensures the security of monitoring data in key areas. S14. Implement certificate lifecycle management and exception handling mechanisms, support the periodic rotation of certificates with multiple administrators and multi-signatures, and real-time synchronization of revocation lists. At the same time, record the complete authentication process on the blockchain to form an immutable audit log, establish authentication event correlation analysis capabilities, provide cross-domain authentication interoperability support, and ensure that the entire authentication process is secure, controllable, and fully traceable.

[0036] In this embodiment, S2 further includes: S21. Based on the spatiotemporal characteristics of the video stream (such as scene complexity, motion intensity, and lighting conditions) and information entropy analysis results, construct video content feature vectors. Evaluate video complexity through deep learning models of edge computing nodes. Automatically select the optimal compression algorithm (such as H.265 / HEVC, AV1, or dedicated water conservancy scene compression algorithm) for different feature types (such as static scenes, dynamic water surfaces, and areas of human activity). Calculate the best compression parameters (such as quantization parameters, GOP structure, and motion estimation accuracy) in real time. Dynamically adjust the encoding configuration according to network conditions and computing resources to ensure the highest compression efficiency while preserving key visual information. S22. To ensure the credibility and immutability of the video processing process, the system calculates feature values ​​for the processing metadata of each video stream (including the original video feature hash, the selected compression algorithm parameters, the processing timestamp, the processing node identifier, etc.) using hash algorithms such as SHA-256. These feature values, along with the processing configuration digest, are submitted to the blockchain network for notarization. After verification by a smart contract, they are written into the distributed ledger, forming a credible timeline of the processing history. Simultaneously, a video processing metadata indexing mechanism is established, supporting the query and verification of the processing history of videos within a specific time period via the blockchain. This achieves traceability throughout the entire lifecycle of video data, providing technical assurance for the legal validity and integrity of subsequent video content and effectively preventing malicious tampering during the video processing process.

[0037] In this embodiment, in step S3, a two-layer encrypted video transmission mechanism is constructed based on the blockchain consensus mechanism and the dynamic key derivation algorithm (DKDA) with high-precision timestamps. The construction process is as follows: the edge device generates a random session key to encrypt the video data, then uses the cloud platform's public key to encrypt the session key, packages it and sends it to the cloud platform, the cloud platform uses its private key to decrypt and obtain the session key, and then decrypts the video data. The key feature value of the entire encryption channel is recorded in the blockchain to ensure that it cannot be tampered with.

[0038] In this embodiment, S3 further includes: S31. Based on the consensus timestamp and unique device identifier of the blockchain network, a dynamic key derivation algorithm is implemented. The latest block hash value of the blockchain is cryptographically combined with the device private key and high-precision timestamp (accurate to the millisecond level) to generate a master key seed. A hierarchical key tree is derived from the master key seed through the key derivation function (KDF), including video content encryption key, metadata encryption key and authentication key. An automatic key rotation mechanism is implemented to ensure that even if a single key is leaked, it will not endanger the overall system security. At the same time, according to the sensitivity level of the video content, different strength encryption algorithms (such as AES-256, ChaCha20) and encryption modes (such as GCM, CTR) are adopted to build a layered encryption system that adapts to different security needs. The key usage record is stored on the blockchain through zero-knowledge proof to ensure that the key management process is auditable but does not disclose the actual content of the key. S32. Dynamically segment the video stream according to fixed time intervals (e.g., 5 seconds) or scene change thresholds, and encrypt each video segment independently to ensure that even if a single segment is cracked, it will not affect the security of other segments. Generate a unique identifier and integrity verification value for each encrypted video segment, construct segment metadata containing encryption parameters, timestamps, and integrity hashes, organize the feature hash values ​​of all video segments through a Merkle tree structure, and submit only the Merkle root hash and key node hashes to the blockchain storage to reduce the blockchain storage pressure while ensuring data integrity and verifiability. Design a smart contract to automatically verify the Merkle proof path of newly submitted video segments, ensure that the Merkle proof path is consistent with the on-chain root hash, and record the verification results on the blockchain. S33. Integrating TLS / SSL protocols and blockchain zero-knowledge proof technology, a multi-layered secure transmission channel is constructed, with the following construction process: S331. Establish a TLS-based encrypted communication tunnel and use strong cryptographic suites to ensure transport layer security. S332. Implement a two-way authentication mechanism based on blockchain identity at the application layer, verifying that both communicating parties hold the correct blockchain identity private key through zero-knowledge proof without exposing the private key itself. S333. Design a transmission session binding mechanism to associate each transmission session with an authorization record on the blockchain, ensuring that only authorized sessions can receive specific video streams. S333. Implement end-to-end data integrity verification. The receiving end verifies the consistency between the video segment hash and the blockchain record to confirm that the data has not been tampered with.

[0039] In this embodiment, step S4 further includes: S41. Construct a multi-tiered hybrid storage architecture. The specific construction process is as follows: S411: Edge nodes provide local high-speed caching, regional nodes are responsible for medium-term storage backup, the cloud enables long-term archiving, and the blockchain stores key metadata and evidence hashes. S412: Data flow between different storage tiers is automatically coordinated through intelligent strategies; S413. Implement a network outage protection mechanism, switching to local emergency storage mode and increasing the sampling rate when the network is interrupted; S414. After the network is restored, key data is transmitted incrementally and its integrity is verified. S415. Deploy a distributed data recovery mechanism, using blockchain records to reconstruct data from distributed nodes in disaster scenarios, ensuring system availability under extreme conditions; S42. Based on blockchain, implement fine-grained data access control. Smart contracts define different role permissions. All data access operations are recorded on the chain to form an immutable log, realizing attribute-based encrypted access control, ensuring the security of sensitive data, providing comprehensive data usage auditing functions, supporting the tracking of the complete access history of video clips, automatically checking the compliance of data operations through smart contracts, ensuring compliance with security policies and regulatory requirements, and building a comprehensive data protection and traceability system.

[0040] In this embodiment, S5 further includes: The S51 cloud platform uses a zero-trust security model to generate dynamic security control commands, including temporary authorization credentials, encryption key rotation parameters, and security policy updates. Each command is embedded with a high-precision timestamp and validity period limit, and is signed using the Elliptic Curve Digital Signature Algorithm (ECDSA) to ensure that the command itself cannot be forged or tampered with. These dynamic commands can adjust the protection strategy of edge devices based on real-time security situation analysis results, such as increasing video encryption strength or changing the key generation frequency when a potential attack is detected, enabling the system to proactively respond to the ever-changing security threat environment. S52. After receiving the instruction, the edge device implements a multi-layered verification mechanism. First, it verifies the cryptographic correctness of the instruction's digital signature. Then, it checks whether the timestamp is within the trusted time window. Finally, it verifies whether the instruction conforms to the preset security policy. Only instructions that pass all verifications can be executed, ensuring that the edge device will not execute expired or forged security instructions, thus preventing replay attacks and man-in-the-middle attacks. This verification mechanism supports the cloud platform in implementing full lifecycle management of encryption keys, including periodic key rotation and emergency key revocation, ensuring that key materials are valid within the preset security time window and automatically expire afterward, preventing the risk of key leakage. S53. After the edge device executes a security command, the execution result is recorded in a verifiable encrypted manner, including the command execution time, details of security configuration changes, and system status changes. These records are hashed and written to a distributed ledger to establish a complete security operation audit chain. At the same time, the system regularly performs security command compliance checks to ensure that the cloud-edge security configuration remains consistent and timely. This process supports the cloud platform to realize remote security response and repair functions. When vulnerabilities or abnormal behavior are found in the edge device, repair commands can be issued immediately for security updates, including software patch installation, configuration error correction, or abnormal connection blocking. This allows for rapid response to security events without interrupting core monitoring functions, ensuring the safe and stable operation of the reservoir monitoring network.

[0041] In this embodiment, the method of using the blockchain consensus mechanism and the improved blockchain fusion quantum-resistant dynamic key derivation algorithm QR-DKDA with the multidimensional secure transmission channel mathematical model in step S3 specifically includes: a. Define the quantum-resistant dynamic key derivation function:

[0042] in, Representing the Derived keys for a time window Representative equipment A unique identifier, This represents a high-precision timestamp, accurate to the microsecond level. This represents the hash value of the previous block. Represents the environmental entropy factor, which includes network state characteristics; This quantum-resistant dynamic key derivation function is implemented through multi-round hybrid hashing to ensure quantum resistance in key generation.

[0043] To address complex security threats, an adaptive multi-layered encryption strategy is adopted. This involves first optimizing encryption efficiency through a dynamic segmentation mechanism, and then employing three-layer concatenated encryption to ensure data security. The formula is as follows:

[0044] in, Representing time Security threat assessment value, These represent the threat assessment weighting coefficients, Represents a network threat assessment function. Represents the equipment anomaly assessment function. Represents a data sensitivity evaluation function; b. The adaptive segmentation mechanism based on content complexity significantly improves system efficiency. The segment size of the video stream is determined by the following model:

[0045] in, Representing the The size of each video segment and This represents the parameter for adjusting the segment size. This represents the video content complexity evaluation function. Representing the The video content of each segment and its adjacent segments; The segmented video stream is encrypted using a three-layer concatenated encryption method to ensure data security, which can be expressed as follows:

[0046] in, Represents a quantum-safe lattice cryptography algorithm. represent Public key, The Galois counter pattern, representing the Advanced Encryption Standard, This represents a high-performance stream cipher algorithm.

[0047] Building upon multi-layered encryption, this invention further incorporates blockchain technology to achieve verifiable key and data integrity. Specifically, this includes Merkle trees for vector commitments and key validity verification based on smart contracts. Innovatively, a Merkle tree structure for vector commitments is proposed:

[0048] The root calculation uses a weighted aggregation method:

[0049] Verify key validity using blockchain smart contracts:

[0050] in, Merkle tree representing vector commitment, and These represent the eigenvalue vector and the weight vector, respectively. Represents the weighting coefficient. Represents a cryptographic hash function. Represents the modulus of a prime number. Representing the The verification value of the derived key within a time window. Represents the execution function of a blockchain smart contract. Representing the The hash value of the derived key for each time window. Represents a high-precision timestamp. Representative equipment A unique identifier.

[0051] In addition to security, this invention also optimizes transmission performance and reliability. Specifically, it includes an adaptive transmission strategy and an error detection and recovery mechanism based on forward error correction. Utility function-based transfer strategy selection:

[0052] Error detection and recovery using Reed-Solomon codes:

[0053] in, Representing time The optimal transmission strategy Represents a set of optional strategies. Represents the data priority function. Represents the utility function. Represents the network state function. Represents the probability of error recovery. Represents the codeword length of the Reed-Solomon code. Represents the number of information symbols in the Reed-Solomon code. This represents the symbol error rate.

[0054] In this embodiment, the method for constructing a time-sensitive cloud-edge collaborative control mechanism in step S5 specifically includes: a. Time synchronization between edge devices and the cloud platform adopts an improved Network Time Protocol (NTP) and combines it with blockchain timestamp verification, which can be expressed as follows:

[0055] in, This represents time deviation. Represents the cloud platform timestamp. Represents the timestamp of the edge device. This indicates a delay in round-trip time; b. The cloud platform generates encrypted commands with time-sensitive verification parameters based on a time synchronization mechanism. Each command sent from the cloud platform to the edge device contains a valid time window, calculated using the following formula:

[0056] in, The timestamp represents the command issuance time, and TTL represents the command's time to live. This represents the pre-loaded fault tolerance time. This represents the post-fault tolerance time (dynamically adjusted based on network conditions). c. After receiving the instruction, the edge device first corrects the time deviation, then verifies the validity of the instruction. If the verification is successful, the cloud platform confirms receipt and prepares to record the result on the blockchain. Otherwise, if the verification fails, the edge device rejects the instruction and reports the exception, then waits for the cloud platform's response and prepares the verification environment for the new instruction.

[0057] Throughout the entire process described above, timeliness is ensured through the following key technologies: (1) Adaptive TTL calculation: Dynamically adjust the instruction validity period according to network conditions and threat level:

[0058] in, This represents the effective time of the dynamically adjusted instruction, in milliseconds (ms). This represents the effective time of the basic instruction, typically set to 5000ms as the system default. Factors representing changes in network conditions This represents a factor that indicates a change in the level of security threats.

[0059] (2) Timeliness score: Continuously monitor the difference between the instruction execution time and the expected time:

[0060] in, This represents the timeliness score of instruction execution, with a value ranging from [0, 1]. A higher value indicates better timeliness. Represents the actual timestamp of the instruction's execution. Represents the timestamp of the instruction issuance. This represents the maximum allowed latency of the system, and is typically set according to the importance level of the region.

[0061] (3) Exception handling: When a timeliness exception is detected, the system initiates an exponential backoff retry mechanism:

[0062] in, This represents the waiting time for the next retry. Represents the base delay time. This represents the current number of retries, starting from 0. It is a key factor, with a value range of [0, 1].

[0063] To verify the feasibility and effectiveness of the water conservancy video surveillance security protection method integrating edge computing and blockchain technology proposed in this invention, a simulation experimental environment was established in a reservoir in a demonstration area of ​​XX province, and a complete video surveillance security protection system integrating edge computing and blockchain technology was deployed. Specific implementation details are as follows: 1. System Hardware Architecture Edge-side device configuration: Camera equipment: Hikvision DS-2CD3T86FWDV2-I3S(B) infrared network camera, 8MP high-definition resolution, supports H.265+ encoding; Edge computing node: NVIDIA Jetson Xavier NX development kit (16GB memory, 384 CUDA cores), equipped with JetPack 4.6 software package; Edge storage: Western Digital WD Purple 4TB surveillance-grade hard drive (WD40PURZ); Network equipment: Cisco Catalyst 9300-24P switch, configured with VLAN isolation and access control lists; 2. System Software Architecture 1) Operating System and Basic Software: Edge node: Ubuntu 20.04 LTS, Docker 20.10.8, CUDA 11.4 Cloud platform: CentOS 8.4, Kubernetes 1.21 cluster management Blockchain platform: A consortium blockchain network built on Hyperledger Fabric 2.4 2) Security Components: PKI Infrastructure: A certificate management system built with OpenSSL 3.0 Encryption library: Implements high-performance encryption operations using libsodium 1.0.18. Smart Contracts: Chaincode smart contracts developed using the Go programming language Time synchronization: Employs the PTP (IEEE 1588) high-precision time protocol to ensure system time deviation <1ms. 3. Specific Implementation Process S1. Implementation of Device Security Access Authentication This embodiment constructs a blockchain-based distributed secure access mechanism. Each monitoring device is pre-installed with an X.509 digital certificate and a PUF hardware identifier. When a device comes online, it establishes a secure channel via the TLS 1.3 protocol, submits authentication information to the consortium blockchain, and undergoes multi-factor authentication via the "DeviceAuth" smart contract. After successful authentication, the system records the device status on the blockchain and issues an authorization token, which the device uses to perform subsequent operations. Test results show that all 10 legitimate devices passed authentication, and all 3 counterfeit devices were blocked, achieving a 100% accuracy rate in the verification mechanism and effectively preventing unauthorized devices from accessing the system.

[0064] S2, Adaptive Video Processing and Differentiation Strategy Implementation Based on the importance of the reservoir monitoring area, this embodiment divides the 25 monitoring points into three levels: Level 1 includes core facilities such as the main dam (5 points); Level 2 includes important facilities such as the power plant (8 points); and Level 3 includes the area surrounding the reservoir (12 points). Differentiated processing strategies are adopted for different levels: Level 1 areas maintain 4K resolution full-frame analysis and frequent on-chain evidence storage; Level 2 areas reduce resolution under normal circumstances and automatically increase it in case of anomalies; Level 3 areas use low resolution and dynamically adjust the bit rate. The system uses an information entropy analysis algorithm to evaluate scene complexity in real time and automatically adjust parameters. Tests show that this solution saves 22.3% bandwidth and 18.7% storage space compared to traditional methods, while ensuring video quality in key scenes.

[0065] S3, Implementation of dual-layer encrypted video transmission mechanism This embodiment employs a two-layer encryption system to ensure transmission security: the edge device generates a new AES-256-GCM random session key every 30 minutes, encrypting video data in segments (each segment every 10 seconds, using a different initialization vector); the session key is encrypted with the RSA-4096 cloud platform public key and then packaged and sent along with the encrypted video; simultaneously, the message hash value is recorded on a blockchain to form an immutable transmission proof chain. During a 30-day test period, the system processed 46.8TB of video data, achieving a 99.997% success rate in encrypted transmission, with no key leakage or tampering incidents, and the transmission latency increased by only 7.2ms, having virtually no impact on real-time monitoring.

[0066] S4. Implementation of Distributed Tiered Storage Strategy This embodiment constructs a three-tier storage architecture: the edge local storage layer uses WD Purple 4TB surveillance hard drives to store 1-7 days of complete video according to the importance of the monitored area; the cloud platform storage layer uses the NetApp system for redundant storage, storing 15-90 days of complete video and converting it into a long-term compressed archive; the blockchain storage layer permanently stores metadata and hash values. The system also implements an intelligent network outage protection mechanism, automatically adjusting the storage strategy through the "EmergencyBackup" smart contract, prioritizing the storage of data in critical areas, and automatically synchronizing metadata after network recovery. Tests have shown that even in the event of a network failure, the system can still save all critical monitoring data, and the data consistency verification pass rate is 100% after recovery.

[0067] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the above-described water conservancy video monitoring security protection method.

[0068] See Figure 4 The present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the above-described water conservancy video monitoring security protection method.

[0069] This invention also provides a computer program product containing instructions that, when run on a computer, causes the computer to perform the steps of the above-described water conservancy video monitoring security protection method.

[0070] It is understood that the system, device and storage medium provided in the embodiments of the present invention correspond to the method provided in the embodiments of the present invention, and the explanation, examples and beneficial effects of the relevant content can be referred to the corresponding parts of the above-mentioned water conservancy video monitoring security protection method.

[0071] It should be noted that those skilled in the art will understand that all or part of the steps implemented in the embodiments of the present invention can be implemented entirely or partially by software, hardware, firmware, or any combination thereof. When implemented in hardware, it can be implemented entirely or partially by purchasing standard parts or modifications. When implemented in software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid state disks (SSDs)).

[0072] In summary, this invention addresses the shortcomings of traditional water conservancy video monitoring systems in terms of security, reliability, and real-time performance by providing a water conservancy video monitoring security protection system and method that integrates edge computing and blockchain technologies. Specifically, this invention employs a smart contract-based device authentication mechanism based on a consortium blockchain architecture, combining asymmetric encryption digital certificate verification and device unique identifier verification to achieve decentralized distributed secure access control. By analyzing the spatiotemporal characteristics and information entropy of video content, it dynamically selects adaptive compression algorithms and implements differentiated processing strategies based on the importance of the monitored area. Simultaneously, it stores the processed metadata on the blockchain using a hash algorithm to ensure data immutability. It innovatively constructs a two-layer encrypted video transmission mechanism based on blockchain consensus and high-precision timestamps. Edge devices generate random session keys to encrypt video data, and then the cloud platform's public key is used to encrypt the session key, achieving high-strength secure transmission. By implementing a blockchain-based distributed hierarchical storage strategy and a hybrid mechanism of local high-speed caching and distributed storage, combined with the automatic network outage protection function of smart contracts, it solves the problems of data consistency and reliability. Finally, it constructs a time-sensitive cloud-edge collaborative control mechanism based on a zero-trust architecture, ensuring instruction security through ECDSA digital signatures and validity period identifiers, achieving dynamic adjustment of security policies and remote security repair, while forming a complete security audit chain through distributed ledger technology. Thus, this invention, through the deep integration of edge computing, blockchain technology and advanced cryptographic methods, comprehensively improves the security, reliability and operation and maintenance efficiency of water conservancy video monitoring systems, providing an innovative technical solution for the field of water conservancy project safety monitoring, and has good application prospects and market value.

[0073] It should be understood that the examples and embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Those skilled in the art can make various modifications or changes based on them. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A method for security protection of water conservancy video surveillance, characterized in that, Includes the following steps: S1. A smart contract management device authentication mechanism based on a consortium blockchain architecture, combined with asymmetric encrypted digital certificate verification and device unique identifier verification, to achieve decentralized distributed secure access control. S2. Based on the spatiotemporal characteristics and information entropy analysis of the video content, select an adaptive compression algorithm and adjust the compression parameters in real time. Implement differentiated processing strategies based on the importance level of the monitored area, and store the processed metadata on the blockchain through a hash algorithm. S3. Based on the blockchain consensus mechanism and high-precision timestamp dynamic key derivation algorithm, the video stream is encrypted in layers and segments, and the feature values ​​are recorded in the blockchain to build a multi-layered encrypted secure transmission channel. S4. Based on blockchain, a distributed hierarchical storage strategy is implemented, which combines local high-speed caching with blockchain distributed storage, and provides automatic protection against network outages and data consistency synchronization based on smart contracts. S5. Construct a timely cloud-edge collaborative control mechanism. The cloud platform issues encrypted commands with ECDSA digital signatures and precise validity period identifiers through multiple channels. Edge devices perform multi-level cryptographic verification and execution based on command priority and timeliness, and record the execution results on the blockchain after hash processing.

2. The water conservancy video surveillance security protection method as described in claim 1, characterized in that, S1 further includes: S11. Assign a globally unique identifier to each monitoring device and generate an asymmetric key pair. Submit the device information to the blockchain network. After multi-node consensus verification, write it into the distributed ledger. At the same time, the consortium blockchain certification center issues a digital certificate containing the device identity information to establish a trusted digital identity for the device on the blockchain. S12. After receiving the video stream access request from the monitoring device, the edge node extracts the device identifier, digital signature and timestamp, triggers the execution of the authentication smart contract, and the contract automatically retrieves the device registration information from the blockchain ledger and ensures that the access device is authentic and trustworthy by verifying at least the validity of the digital certificate, the authenticity of the signature and the device's operating status through multiple dimensions. S13. The smart contract automatically assigns differentiated permission levels based on the importance of the area where the monitoring equipment is located, generates an access token containing permission information and validity period, signs it with a blockchain timestamp, records the authorization event on the chain, realizes decentralized access control based on blockchain, and ensures the security of monitoring data in key areas. S14. Implement certificate lifecycle management and exception handling mechanisms, support the periodic rotation of certificates with multiple administrators and multi-signatures, and real-time synchronization of revocation lists. At the same time, record the complete authentication process on the blockchain to form an immutable audit log, establish authentication event correlation analysis capabilities, provide cross-domain authentication interoperability support, and ensure that the entire authentication process is secure, controllable, and fully traceable.

3. The water conservancy video surveillance security protection method as described in claim 1, characterized in that, S2 further includes: S21. Based on the spatiotemporal characteristics and information entropy analysis results of the video stream, construct video content feature vectors, evaluate video complexity through the deep learning model of edge computing nodes, automatically select the optimal compression algorithm for different feature types, calculate the best compression parameters in real time, and dynamically adjust the encoding configuration according to network conditions and computing resources to ensure the highest compression efficiency while preserving key visual information. S22. To ensure the credibility and immutability of the video processing process, the system calculates a feature value for the processing metadata of each video stream using a hash algorithm, and submits this feature value along with a processing configuration summary to the blockchain network for notarization. After verification by a smart contract, it is written into the distributed ledger to form a credible timeline of processing history. At the same time, a video processing metadata indexing mechanism is established to support the query and verification of the processing history of videos within a specific time period through the blockchain, realizing the traceability of the entire life cycle of video data, providing technical protection for the legal validity and integrity of subsequent video content, and preventing the video processing process from being maliciously tampered with.

4. The water conservancy video surveillance security protection method as described in claim 1, characterized in that, In S3, a two-layer encrypted video transmission mechanism is constructed based on the blockchain consensus mechanism and the dynamic key derivation algorithm with high-precision timestamps. The construction process is as follows: the edge device generates a random session key to encrypt the video data, then uses the cloud platform's public key to encrypt the session key, packages it and sends it to the cloud platform, the cloud platform uses the private key to decrypt and obtain the session key, and then decrypts the video data. The key feature value of the entire encryption channel is recorded in the blockchain to ensure that it cannot be tampered with.

5. The water conservancy video surveillance security protection method as described in claim 4, characterized in that, S3 further includes: S31. Based on the consensus timestamp and unique device identifier of the blockchain network, a dynamic key derivation algorithm is implemented. The latest block hash value of the blockchain is cryptographically combined with the device private key and high-precision timestamp to generate a master key seed. A hierarchical key tree is derived from the master key seed through a key derivation function, including video content encryption key, metadata encryption key and authentication key. An automatic key rotation mechanism is implemented to ensure that even if a single key is leaked, it will not endanger the overall system security. At the same time, according to the sensitivity level of the video content, different strength encryption algorithms and encryption modes are adopted to build a layered encryption system that adapts to different security needs. The key usage record is stored on the chain through zero-knowledge proof to ensure that the key management process is auditable but does not disclose the actual content of the key. S32. Dynamically segment the video stream according to fixed time intervals or scene change thresholds, and encrypt each video segment independently to ensure that even if a single segment is cracked, it will not affect the security of other segments. Generate a unique identifier and integrity verification value for each encrypted video segment, construct segment metadata containing encryption parameters, timestamps, and integrity hashes, organize the feature hash values ​​of all video segments through a Merkle tree structure, and submit only the Merkle root hash and key node hashes to the blockchain storage. This reduces the storage pressure on the blockchain while ensuring data integrity and verifiability. Design a smart contract to automatically verify the Merkle proof path of newly submitted video segments, ensure that the Merkle proof path is consistent with the on-chain root hash, and record the verification results on the blockchain. S33. Integrating TLS / SSL protocols and blockchain zero-knowledge proof technology, a multi-layered secure transmission channel is constructed, with the following construction process: S331. Establish a TLS-based encrypted communication tunnel and use strong cryptographic suites to ensure transport layer security. S332. Implement a two-way authentication mechanism based on blockchain identity at the application layer, verifying that both communicating parties hold the correct blockchain identity private key through zero-knowledge proof without exposing the private key itself. S333. Design a transmission session binding mechanism to associate each transmission session with an authorization record on the blockchain, ensuring that only authorized sessions can receive specific video streams. S334. Implement end-to-end data integrity verification. The receiving end verifies the consistency between the video segment hash and the blockchain record to confirm that the data has not been tampered with.

6. The water conservancy video surveillance security protection method as described in claim 1, characterized in that, S4 further includes: S41. Construct a multi-tiered hybrid storage architecture. The specific construction process is as follows: S411: Edge nodes provide local high-speed caching, regional nodes are responsible for medium-term storage backup, the cloud enables long-term archiving, and the blockchain stores key metadata and evidence hashes. S412: Data flow between different storage tiers is automatically coordinated through intelligent strategies; S413. Implement a network outage protection mechanism, switching to local emergency storage mode and increasing the sampling rate when the network is interrupted; S414. After the network is restored, key data is transmitted incrementally and its integrity is verified. S415. Deploy a distributed data recovery mechanism, using blockchain records to reconstruct data from distributed nodes in disaster scenarios, ensuring system availability under extreme conditions; S42. Based on blockchain, implement fine-grained data access control. Smart contracts define different role permissions. All data access operations are recorded on the chain to form an immutable log, realizing attribute-based encrypted access control, ensuring the security of sensitive data, providing comprehensive data usage auditing functions, supporting the tracking of the complete access history of video clips, automatically checking the compliance of data operations through smart contracts, ensuring compliance with security policies and regulatory requirements, and building a comprehensive data protection and traceability system.

7. The water conservancy video surveillance security protection method as described in claim 1, characterized in that, S5 further includes: S51, the cloud platform uses a zero-trust security model to generate dynamic security control instructions, including temporary authorization credentials, encryption key rotation parameters and security policy updates. Each instruction is embedded with a high-precision timestamp and validity period limit, and is signed by an elliptic curve digital signature algorithm to ensure that the instruction itself cannot be forged or tampered with. S52. After receiving the instruction, the edge device implements a multi-level verification mechanism. First, it verifies the cryptographic correctness of the instruction's digital signature. Then, it checks whether the timestamp is within the trusted time window. Finally, it verifies whether the instruction conforms to the preset security policy. Only instructions that pass all verifications can be executed, ensuring that the edge device will not execute expired or forged security instructions, thereby preventing replay attacks and man-in-the-middle attacks. S53. After the edge device executes the security command, the execution result is recorded in a verifiable encrypted manner, including the command execution time, details of security configuration changes and system status changes. These records are written into the distributed ledger after being hashed to establish a complete security operation audit chain. At the same time, the system regularly performs security command compliance checks to ensure that the cloud-edge security configuration remains consistent and timely.

8. A water conservancy video surveillance security protection system, applicable to the water conservancy video surveillance security protection method as described in any one of claims 1-7, characterized in that, It includes a three-layer structure: top layer, middle layer, and bottom layer. The top layer is the video surveillance equipment layer, the middle layer is the edge computing layer, and the bottom layer is the cloud platform layer. The data collected by the video surveillance equipment layer is processed by the edge computing layer and then interacts securely with the cloud platform layer.

9. The water conservancy video monitoring security protection system as described in claim 8, characterized in that, The video surveillance equipment layer includes multiple video surveillance devices, which are used to collect video data from various areas of the reservoir and transmit the video streams to edge devices for processing. The edge computing layer, as the core processing unit, includes six key functional modules: a transmission module, an interface module, a computing unit, a storage unit, a clock synchronization module, and a security encryption module. The transmission module is used to receive video stream data, the interface module is used to process device communication, the computing unit is used to perform data analysis and feature extraction, the storage unit is used to provide local data caching, the clock synchronization module is used to ensure system time consistency, and the security encryption module is used to protect data. In the cloud platform layer, a two-way communication channel is established between the cloud platform and the edge devices. Uplink, encrypted and compressed video streams and video warning information are transmitted, while downlink, dynamic instructions and time limits issued by the cloud platform are received. The cloud platform layer has three core functional components: instruction timeliness verification, private key management, and a distributed storage coordinator. The instruction timeliness verification is used to ensure the security and validity of instructions. The private key management is used to ensure the security of encrypted communication in the system. The distributed storage coordinator is used to realize efficient distributed storage and management of data.

10. A computer device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the water conservancy video monitoring security protection method as described in any one of claims 1-7.

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