Power distribution internet-of-things terminal management method and system based on quantum cloud code, and electronic equipment

Abstract

The invention relates to the technical field of power data transmission, and discloses a power distribution Internet of Things terminal management method and system based on quantum cloud codes, and electronic equipment. The method comprises the steps of mixing original data through a random number generator to obtain a quantum cloud code seed, obtaining a quantum cloud code sequence through fragmentation encryption, forming a terminal equipment grouping key according to a preset rule, generating an equipment identity feature code in combination with operation state information, and establishing a data transmission channel according to the feature code. A secure communication link is formed through encryption and verification of a session key, operation data in the communication link is collected, a standardized data set is obtained through cleaning and normalization, output equipment behavior characteristics are mapped, operation authority is dynamically adjusted to construct a management system, regular snapshot and distributed backup are performed, and disaster recovery backup data are formed to establish a recovery strategy. According to the invention, security authentication, dynamic permission allocation and intelligent management of the terminal equipment are realized, and the security and management efficiency of the system are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of power data transmission, and particularly to a management method, system, and electronic device for distribution Internet of Things terminals based on quantum cloud codes. Background Art

[0002] With the rapid development of smart grid technology, the number of Internet of Things terminal devices in the distribution automation system has shown an explosive growth. These terminal devices undertake key tasks such as data collection, device monitoring, and fault diagnosis, and play an important role in the safe and stable operation of the power system. The existing management of distribution Internet of Things terminals mainly adopts traditional key management and access control methods, authenticates identities through fixed keys, uses a static permission allocation mechanism to manage the access permissions of terminal devices, and uses regular backup methods to ensure the security of system data.

[0003] However, the existing technologies have many deficiencies. First, the traditional key management method has low security and is vulnerable to various network attacks. Second, the static permission allocation mechanism cannot be dynamically adjusted according to the operating status of terminal devices, easily causing problems such as over-allocation or under-allocation of permissions. Third, the traditional backup method often uses centralized storage, with a risk of single-point failure and low recovery efficiency. In addition, the existing terminal management methods lack in-depth analysis and evaluation of device behaviors, making it difficult to detect and handle abnormal behaviors in a timely manner, posing a potential threat to system security. Summary of the Invention

[0004] This application provides a management method, system, and electronic device for distribution Internet of Things terminals based on quantum cloud codes, which are used to solve the technical problems in the existing management of distribution Internet of Things terminals, such as poor system security and low management efficiency due to the lack of a dynamic security authentication mechanism and an intelligent permission management system. By introducing quantum cloud code technology and combining quantum encryption and dynamic permission management, secure authentication, dynamic permission allocation, and intelligent management of terminal devices are realized, significantly improving the security and management efficiency of the system.

[0005] In a first aspect, the present application provides a management method for a power distribution IoT terminal based on quantum cloud codes. The management method for the power distribution IoT terminal based on quantum cloud codes includes: performing confusion processing on the original data through a random number generator to obtain a quantum cloud code seed, performing shard encryption on the quantum cloud code seed to obtain a quantum cloud code sequence, and performing grouping and matching on the quantum cloud code sequence according to a preset rule to form a terminal device grouping key; extracting the hardware identification data of the terminal device based on the terminal device grouping key, and performing feature synthesis on the hardware identification data in combination with the terminal operation status information to generate a device identity feature code; establishing a data transmission channel according to the device identity feature code, encrypting the data transmission channel through a session key to establish an encrypted data channel, and performing integrity verification on the encrypted data channel to form a secure communication link; collecting the terminal operation data in the secure communication link, performing data cleaning and normalization processing on the terminal operation data to obtain a standardized data set, and performing feature mapping according to the standardized data set to output device behavior features; performing hierarchical evaluation on the terminal access permissions based on the device behavior features, dynamically adjusting the terminal operation permissions through the hierarchical evaluation results, and constructing a permission management system; taking a periodic snapshot of the system operation status according to the permission management system, performing distributed backup on the system snapshot data to form disaster recovery backup data, and establishing a system recovery strategy according to the disaster recovery backup data.

[0006] In a second aspect, the present application provides a management system for a power distribution IoT terminal based on quantum cloud codes. The management system for the power distribution IoT terminal based on quantum cloud codes includes: An encryption module, configured to perform confusion processing on the original data through a random number generator to obtain a quantum cloud code seed, perform shard encryption on the quantum cloud code seed to obtain a quantum cloud code sequence, and perform grouping and matching on the quantum cloud code sequence according to a preset rule to form a terminal device grouping key; An extraction module, configured to extract the hardware identification data of the terminal device based on the terminal device grouping key, and perform feature synthesis on the hardware identification data in combination with the terminal operation status information to generate a device identity feature code; A establishment module, configured to establish a data transmission channel according to the device identity feature code, encrypt the data transmission channel through a session key to establish an encrypted data channel, and perform integrity verification on the encrypted data channel to form a secure communication link; A cleaning module, configured to collect the terminal operation data in the secure communication link, perform data cleaning and normalization processing on the terminal operation data to obtain a standardized data set, and perform feature mapping according to the standardized data set to output device behavior features; A grading module, which is used to conduct a grading evaluation on the terminal access rights according to the device behavior characteristics, dynamically adjust the terminal operation rights through the grading evaluation results, and construct a permission management system; A snapshot module, which is used to take regular snapshots of the system running status according to the permission management system, perform distributed backup on the system snapshot data to form disaster recovery backup data, and establish a system recovery strategy based on the disaster recovery backup data.

[0007] The third aspect of this application provides an electronic device. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through a bus. When the machine-readable instructions are executed by the processor, the steps of the above-mentioned power distribution IoT terminal management method based on quantum cloud codes are executed.

[0008] In the technical solution provided by this application, the original data is obfuscated by a random number generator, realizing the high randomness and unpredictability of the data, effectively preventing the data from being stolen and tampered with. The quantum cloud code seeds are processed by using the sharding encryption technology, improving the security and reliability of the data. Through the generation and distribution of the terminal device group keys, the accurate identification and classification management of the terminal devices are realized, enhancing the security control ability of the system. The hardware identification data is extracted based on the terminal device group keys, and the device identity feature code is generated in combination with the terminal running status information, ensuring the uniqueness and verifiability of the device identity. The established data transmission channel is encrypted by the session key and integrity verification is carried out simultaneously to form a secure communication link, ensuring the security and integrity of the data transmission. The terminal running data in the secure communication link is collected and processed, and a standardized data set is obtained through data cleaning and normalization processing, improving the quality and usability of the data. Feature mapping is performed according to the standardized data set to accurately output the device behavior characteristics, providing a reliable basis for subsequent permission management. The terminal access rights are graded and evaluated according to the device behavior characteristics, realizing the dynamic adjustment of the permissions and constructing a flexible and effective permission management system. Through the regular snapshot and distributed backup mechanisms, perfect disaster recovery backup data is formed, ensuring the recoverability of the system data. A system recovery strategy is established based on the disaster recovery backup data, improving the reliability and continuous operation ability of the system. The overall solution realizes the secure access, reliable communication, dynamic management and effective recovery of the power distribution IoT terminals, significantly improving the security, reliability and management efficiency of the power distribution IoT network. Brief Description of the Drawings

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings; Figure 1 FIG. is a schematic diagram of an embodiment of a power distribution IoT terminal management method based on quantum cloud codes in an embodiment of the present application; Figure 2 FIG. is a schematic diagram of an embodiment of a power distribution IoT terminal management system based on quantum cloud codes in an embodiment of the present application; Figure 3 FIG. is a schematic diagram of the structure of an electronic device in an embodiment of the present application. Detailed Embodiments

[0010] The embodiments of the present application provide a power distribution IoT terminal management method, system and electronic device based on quantum cloud codes. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and accompanying drawings of the present application are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0011] For ease of understanding, the following describes the specific process of the embodiments of the present application. Please refer to Figure 1 , an embodiment of the power distribution IoT terminal management method based on quantum cloud codes in the embodiments of the present application includes: Step S101: Confuse the original data through a random number generator to obtain a quantum cloud code seed, perform sharding encryption on the quantum cloud code seed to obtain a quantum cloud code sequence, and group and match the quantum cloud code sequence according to a preset rule to form a terminal device group key; Step S102: Extract the hardware identification data of the terminal device based on the terminal device group key, and synthesize the characteristics of the hardware identification data in combination with the terminal operation status information to generate a device identity characteristic code; Step S103: Establish a data transmission channel according to the device identity characteristic code, encrypt the data transmission channel through a session key to establish an encrypted data channel, and perform integrity verification on the encrypted data channel to form a secure communication link; Step S104: Collect the operation data of the terminals in the secure communication link, perform data cleaning and normalization processing on the terminal operation data to obtain a standardized data set, and perform feature mapping based on the standardized data set to output device behavior features; Step S105: Perform a hierarchical evaluation of the terminal access permissions based on the device behavior features, dynamically adjust the terminal operation permissions through the hierarchical evaluation results, and construct a permission management system; Step S106: Take a regular snapshot of the system operation status according to the permission management system, perform distributed backup on the system snapshot data to form disaster recovery backup data, and establish a system recovery policy based on the disaster recovery backup data.

[0012] It can be understood that the execution subject of this application can be a power distribution Internet of Things terminal management system based on quantum cloud codes, or it can also be a terminal or a server, and specific limitations are not made here. In this embodiment of the application, the server is used as the execution subject for illustration.

[0013] Specifically, the original data is obfuscated by a random number generator. The obfuscation process uses a non-linear transformation algorithm to convert the input original data into a random sequence. In the distribution Internet of Things network, the original data includes information such as the operating parameters, communication status, and resource occupancy of terminal devices. During the data obfuscation process, each value of the original data is randomly permuted and non-linearly transformed to generate a quantum cloud code seed. The quantum cloud code seed is a key sequence with high randomness and unpredictability, which is used for subsequent security authentication and encrypted communication. The generated quantum cloud code seed is encrypted in slices. The slice encryption adopts a dynamic slicing strategy, and the quantum cloud code seed is divided into multiple sub-fragments according to the data structure characteristics. Each sub-fragment contains different weights and security levels, and each sub-fragment is independently encrypted by a symmetric encryption algorithm to ensure the confidentiality of the data. The encrypted sub-fragments are combined to form a quantum cloud code sequence, which contains the complete authentication information and security policies of the terminal device. When grouping and matching the quantum cloud code sequence, it is classified according to the functional attributes, security levels, access permissions, etc. of the terminal device, and the corresponding key group is assigned to different types of terminal devices. The grouping and matching adopt a multi-dimensional evaluation mechanism, comprehensively considering factors such as the computing power, communication requirements, and security requirements of the device, and finally form the terminal device group key. The terminal device group key is used for subsequent identity authentication and data encryption. Based on the obtained terminal device group key, the hardware identification data of the terminal device is extracted. The hardware identification data includes the unique identification code of the device, hardware configuration information, operating environment parameters, etc. The extraction of the hardware identification data adopts a hierarchical scanning strategy, and the device characteristics are collected step by step from the hardware bottom layer to the application layer. At the same time, combined with the terminal operating status information, including real-time monitoring data such as CPU occupancy rate, memory usage, and network traffic, the hardware identification data is synthesized with features to generate a feature code that can uniquely identify the device identity. The generated device identity feature code is used as the basis for establishing a secure communication. A data transmission channel is established through feature code verification and key negotiation. The data transmission channel adopts a multi-layer encryption mechanism, and the data transmitted is encrypted in real time using a session key. The session key is dynamically generated through a key exchange protocol to ensure the security of the communication process. After establishing the encrypted data channel, a stable and reliable secure communication link is formed through packet checksum and integrity verification. The terminal operating data transmitted in the secure communication link is collected. The collected data includes information such as device operating status, performance indicators, and abnormal events. The collected original data may have problems such as noise, redundancy, and outliers, and needs to be cleaned. The data cleaning process includes steps such as outlier detection, data completion, and redundancy removal. The cleaned data is then normalized to unify data with different dimensions into the same scale range to form a standardized data set.

[0014] The terminal access permissions are hierarchically evaluated based on the device behavior characteristics. The evaluation process considers multiple dimensions such as the device's access history, resource occupancy, and abnormal behaviors. By establishing an evaluation index system, the access behaviors of the device are quantitatively analyzed to generate a hierarchical evaluation result. According to the evaluation result, the terminal operation permissions are dynamically adjusted to construct a permission management system with multiple security levels. According to the established permission management system, the system running status is snapshotted regularly, and key data such as the system configuration information, running parameters, and permission allocation are recorded. The system snapshot data adopts a distributed storage strategy, and the data is dispersed and stored on multiple backup nodes to improve the reliability and availability of the data. The formed disaster recovery backup data is used for system fault recovery and state backtracking, and a system recovery strategy including recovery time sequence and priority strategy is established accordingly.

[0015] For example, when a distribution terminal device accesses the system, it first obtains a set of original data, including information such as device model XM-2024, MAC address, and CPU serial number CPU-8A76. Through random number obfuscation processing, these data are converted into a 128-bit quantum cloud code seed. The seed is encrypted by being divided into 8 slices, each slice being 16 bits, and after being encrypted separately, they form a quantum cloud code sequence. According to the device's security level (Level-3) and function type (monitoring type), the terminal device group key KEY-M789 is generated. Based on this key, the hardware identification data is extracted, and combined with the current running status information such as CPU usage rate of 75%, memory occupancy rate of 60%, and network bandwidth utilization rate of 45%, the device identity characteristic code is generated. The system then establishes an encrypted communication link. The collected terminal data is cleaned and normalized, and it is found that the device has made 3 unauthorized access attempts in the past 24 hours. The system automatically downgrades its permission level by one level and takes a status snapshot every hour, which is saved to 3 distributed storage nodes as disaster recovery backup.

[0016] In the embodiments of the present application, the original data is obfuscated by a random number generator, achieving a high degree of randomness and unpredictability of the data, effectively preventing the data from being stolen and tampered with. The sharding encryption technology is used to process the quantum cloud code seeds, improving the security and reliability of the data. Through the generation and distribution of the group keys of the terminal devices, the accurate identification and classification management of the terminal devices are realized, enhancing the security control ability of the system. The hardware identification data is extracted based on the group keys of the terminal devices, and the device identity feature code is generated in combination with the terminal operation status information, ensuring the uniqueness and verifiability of the device identity. The established data transmission channel is encrypted by the session key and integrity verification is performed simultaneously to form a secure communication link, ensuring the security and integrity of the data transmission. The terminal operation data in the secure communication link is collected and processed, and a standardized data set is obtained through data cleaning and normalization processing, improving the quality and usability of the data. Feature mapping is performed according to the standardized data set, and the device behavior features are accurately output, providing a reliable basis for subsequent permission management. The terminal access permissions are hierarchically evaluated based on the device behavior features, realizing the dynamic adjustment of the permissions, and constructing a flexible and effective permission management system. Through the regular snapshot and distributed backup mechanisms, a perfect disaster recovery backup data is formed, ensuring the recoverability of the system data. The system recovery strategy is established according to the disaster recovery backup data, improving the reliability and continuous operation ability of the system. The overall solution realizes the secure access, reliable communication, dynamic management and effective recovery of the distribution IoT terminals, significantly improving the security, reliability and management efficiency of the distribution IoT network.

[0017] In a specific embodiment, the process of executing step S101 may specifically include the following steps: (1) Perform random number mapping on the operation parameters of the distribution terminal through a random number generator to generate an original confusion matrix, and construct a random perturbation vector based on the original confusion matrix; (2) Perform a non-linear transformation on the original data according to the random perturbation vector to obtain an initial obfuscated data stream, and perform data recombination on the initial obfuscated data stream through piecewise linear transformation to form quantum cloud code seeds; (3) Establish a data sharding index table based on the quantum cloud code seeds, and slice the quantum cloud code seeds through a dynamic sharding algorithm to obtain a set of quantum cloud code shards; (4) Perform encryption conversion on the set of quantum cloud code shards according to the symmetric encryption algorithm, output an encrypted shard sequence, and sort and combine the encrypted shard sequence through a data reconstruction algorithm to generate a quantum cloud code sequence; (5) Perform grouping calculation on the quantum cloud code sequence through hierarchical clustering to obtain a grouping feature vector, and construct a terminal grouping mapping table based on the grouping feature vector; (6) Perform key distribution for the terminal devices according to the terminal grouping mapping table, calculate the key parameters for each group through the key derivation function, and form the group keys for the terminal devices.

[0018] Specifically, perform random number mapping processing on the operating parameters of the distribution terminal. The operating parameters include core operating indicators such as the voltage value, current value, power factor, and harmonic content of the device. Through the random number generator, these deterministic parameter values are mapped into a random space to generate the original confusion matrix. The original confusion matrix is a multi-dimensional data structure, with each dimension corresponding to a type of operating parameter, and the element values in the matrix are obtained through random mapping of the original parameter values. Based on this original confusion matrix, construct a random perturbation vector, and the dimension of the perturbation vector matches the dimension of the original confusion matrix, which is used for further randomization processing of the data.

[0019] For the hierarchical clustering processing process, adopt the following mathematical model: Where: represents the weighted distance between the i-th and j-th samples in the quantum cloud code sequence, represents the weight coefficient of the k-th feature, represents the k-th feature value of the i-th sample, represents the k-th feature value of the j-th sample, and n represents the total number of feature dimensions.

[0020] Apply the random perturbation vector to the original data for non-linear transformation processing. The non-linear transformation adopts a multi-level data conversion mechanism, and each level perturbs the data to different degrees, and finally obtains the initial confused data stream. This data stream needs to undergo piecewise linear transformation for data reorganization, rearrange and combine the confused data to form a quantum cloud code seed with a specific structure. The quantum cloud code seed is the basis for subsequent security mechanisms, and its structure needs to meet certain requirements of randomness and unpredictability. Based on the generated quantum cloud code seed, establish a data sharding index table, and the index table records the location information and association relationships of the data shards. Through the dynamic sharding algorithm, the quantum cloud code seed is sliced, and the dynamic sharding algorithm will dynamically adjust the shard size and the number of shards according to the importance and security level of the data, and finally obtain a set of quantum cloud code shards. Each shard contains some key information, and a single shard cannot restore the complete data content.

[0021] For the quantum cloud code shard set, a symmetric encryption algorithm is used for encryption conversion. In the encryption process, a high-strength encryption key is used to independently encrypt each shard, and an encrypted shard sequence is output. The encrypted shards need to be sorted and combined through a data reconstruction algorithm. The data reconstruction algorithm will recombine the scattered encrypted shards into a complete quantum cloud code sequence according to the association relationship and version information between the shards. The quantum cloud code sequence undergoes hierarchical clustering processing for grouping calculation. By calculating the similarity and correlation degree between the shards, the shards with similar characteristics are grouped into one group, and finally a grouped feature vector is obtained. The grouped feature vector reflects the differences between different shard groups and the internal consistency. Based on these feature vectors, a terminal grouping mapping table is constructed, and the mapping table defines the corresponding relationship between different types of terminal devices and shard groups.

[0022] According to the terminal grouping mapping table, key distribution is performed for each terminal device, and the dedicated key parameters for each group of devices are calculated through a key derivation function. The key derivation process takes into account the security level, functional requirements, and resource constraints of the devices, and finally forms a complete set of terminal device grouping key systems.

[0023] Taking a certain intelligent power distribution terminal as an example, the operating parameters monitored in real time by this terminal include: voltage 220V, current 5A, power factor 0.95, and harmonic content 2.5%. These parameters are mapped and converted into a 48-bit original confusion matrix through random numbers, with each 12 bits corresponding to a parameter value. The generated random perturbation vector modulates these values, and through three-layer non-linear transformation, a 192-bit initial confusion data stream is obtained. After 8-segment linear transformation and recombination, a 256-bit quantum cloud code seed is formed. This seed is divided into 16 shards according to the dynamic sharding algorithm, with each shard being 16 bits, generating a quantum cloud code shard set. These 16 pieces of data are encrypted using the AES-256 algorithm, and after encryption, a 512-bit quantum cloud code sequence is formed through data reconstruction. This sequence undergoes hierarchical clustering calculation and is classified into terminal group B according to the security level and functional attributes, obtaining the corresponding grouped key parameter QKEY-B396. The entire process strictly follows the data security requirements, ensuring the secure access and reliable operation of the power distribution terminal.

[0024] In a specific embodiment, the process of executing step S102 may specifically include the following steps: (1) Perform identity resolution on the terminal device through the terminal device grouping key to obtain the hardware data stream, and classify the data according to the hardware data stream to form hardware identification data; (2) Collect and statistically analyze the resource occupancy indicators, communication load parameters, and power consumption values of the terminal device to obtain an operating parameter set, and perform time series integration on the operating parameter set through time synchronization to generate terminal operating status information; Extract the features of the hardware identification data according to data dimensionality reduction to obtain a hardware feature set, and remove redundant data in the hardware feature set according to data filtering to form a hardware feature vector; (4)Combine the data according to the terminal operation status information and the hardware feature vector to obtain a multi-dimensional feature table, and extract the key values from the multi-dimensional feature table through feature screening to generate a core feature matrix; (5)Perform a non-linear mapping on the core feature matrix according to feature transformation to obtain a feature space sequence, and sort the importance of the feature space sequence according to the variable correlation degree to form a feature identification set; (6)Perform an encryption transformation on the feature identification set through digital signature to obtain an identity identification sequence, and encrypt the identity identification sequence according to the encryption key to form a device identity feature code.

[0025] Specifically, parse the identification information of the terminal device through the terminal device group key. The group key is used as the decryption key to decrypt the hardware identification information stored in the device. The hardware data stream obtained after decryption contains raw data such as the processor information, memory information, and communication interface information of the device. Classify and organize these data, and form structured hardware identification data according to different hardware component types. During the operation of the terminal device, real-time collect the resource occupancy indicators of the device, including CPU usage rate, memory occupancy rate, storage space usage, etc.; at the same time, monitor the communication load parameters, including network traffic, communication delay, packet loss rate, etc.; in addition, collect the power consumption values of the device, including the overall power consumption and the power consumption distribution of each module. These data are statistically analyzed to obtain an operation parameter set, and the data collected at different time points are integrated into time-series terminal operation status information through timestamp alignment and sequence synchronization.

[0026] Perform dimensionality reduction processing on the hardware identification data, extract the main features using the principal component analysis method to obtain a hardware feature set. There are duplicate and redundant information in the hardware feature set. Remove these redundant data through data filtering technology, retain the key feature information, and finally form a concise hardware feature vector.

[0027] For the non-linear mapping process of feature transformation, use the following mathematical model: Where: Represents the i-th eigenvalue after mapping, Represents the j-th eigenvalue in the input feature matrix, Represents the mapping scale factor, Represents the non-linearity degree adjustment parameter, Represents the weight coefficient matrix between features, Represents the bias parameter, Represents the dimension of the input feature.

[0028] Fuse the terminal operation status information with the hardware feature vector, store the combined data using a multi-dimensional table structure to form a multi-dimensional feature table. Through feature importance evaluation, extract the most representative values for the device identity features from the multi-dimensional feature table to construct a core feature matrix. Perform a non-linear mapping transformation on the core feature matrix to project the feature data into a high-dimensional feature space, obtaining a feature space sequence. According to the correlation coefficient between features, evaluate and sort the variables in the feature space sequence, and finally form a feature identification set.

[0029] Perform an encryption transformation on the feature identification set through a digital signature algorithm to ensure the immutability of the feature data, generating an identity identification sequence. Use the device-specific encryption key to perform secondary encryption on the identity identification sequence, and finally form a unique device identity feature code.

[0030] For example, for a power distribution terminal device with a model number QD-2024, use the terminal device group key KEY-G789 to parse its hardware information to obtain a hardware data stream containing the CPU model ARM-M4 (main frequency 180MHz), memory capacity 256MB, and communication interface 4G-LTE. After data classification, form hardware identification data containing 15 fields. The real-time collected CPU usage rate of this device is 65%, memory occupancy rate is 48%, communication bandwidth occupancy rate is 35%, and the overall power consumption is 15W. Synchronize these data in time, sample once every 10 seconds, and accumulate 1 minute of data to form the terminal operation status information. Perform dimensionality reduction processing on the hardware identification data, reduce 15 features to 8 key features, and form a 6-dimensional hardware feature vector after removing duplicate information. Combine the operation status information with the feature vector to generate an 8×12 multi-dimensional feature table, and extract the most representative 6×8 core feature matrix. Convert this matrix into a 24-dimensional feature space sequence through non-linear mapping, and select features with a correlation degree greater than 0.8 in it according to correlation analysis to form a feature identification set. Finally, use the RSA-2048 algorithm for digital signature to generate a 512-bit identity identification sequence, and then use the AES-256 algorithm for encryption to form the final device identity feature code.

[0031] In a specific embodiment, the process of executing step S103 may specifically include the following steps: (1) Authenticate and verify the device identity feature code through data parsing to obtain channel authentication information, and perform connection configuration according to the channel authentication information to establish a data transmission channel; (2) Periodically count the data traffic characteristics of the data transmission channel to obtain a traffic characteristic table, and perform conversion calculations on the traffic characteristic table through key generation to form a session key; (3) Encrypt the data packets of the data transmission channel according to the session key to obtain an encrypted data stream, and construct a channel for the encrypted data stream according to data recombination to generate an encrypted data channel; (4) Calculate the checksum of the data packet header of the encrypted data channel to obtain a check sequence, and perform a verification operation on the check sequence through data comparison to output an integrity identifier; (5) Calculate the reliability of the encrypted data channel according to the integrity identifier to obtain a channel evaluation value, and perform optimization and adjustment based on the channel evaluation value to form an optimization parameter group; (6) Update the parameters of the optimization parameter group through channel configuration to obtain a secure channel configuration, and reconstruct the encrypted data channel according to the secure channel configuration to form a secure communication link.

[0032] Specifically, the device identity feature code is authenticated and verified through a data parsing module. The verification process includes format check of the feature code, digital signature verification, and decryption of encrypted information. After successful verification, channel authentication information is obtained. The authentication information includes key parameters such as the device's identity identifier, security level, and communication permissions. Based on this authentication information, the communication connection is configured, and parameters such as the transmission protocol type, data packet format, and communication bandwidth are set, thus establishing an initial data transmission channel. The established data transmission channel is monitored in real time, and the data traffic characteristics in the channel are collected, including indicators such as data packet size, transmission rate, delay jitter, and packet loss rate. A periodic statistical method is used to statistically analyze the traffic data once every minute, and the statistical results are recorded in the traffic feature table. The traffic feature table contains traffic data of multiple time windows. These data are processed through a key generation algorithm to extract random feature values, and finally a session key for encrypted communication is generated.

[0033] The session key is used to encrypt and protect the data packets transmitted in the data transmission channel. The encryption process uses block encryption, where the data packets are divided into blocks of a fixed size for encryption operations to generate a ciphertext data stream. The encrypted data stream is reorganized, and the encrypted data packets are reorganized according to a predetermined channel structure to construct an encrypted data channel. The encrypted data channel adds a data encryption layer on the basis of the original data transmission channel to ensure the security of data transmission. To ensure the integrity of data transmission, each data packet transmitted in the encrypted data channel needs to be checked. The check process first calculates the checksum of the data packet header and generates a check sequence using the cyclic redundancy check algorithm. The calculated check sequence is compared and verified with the original check value carried in the data packet, and an integrity identifier is output through the comparison result. The identifier includes information such as the check status and error type.

[0034] Quantitatively evaluate the reliability of the encrypted data channel based on the integrity identifier, calculate performance indicators such as the bit error rate, retransmission rate, and latency of the channel, and obtain the channel evaluation value. The evaluation value reflects the current transmission quality of the channel. Optimize and adjust the channel parameters according to the evaluation results, including adjusting the encryption strength, updating the transmission protocol, optimizing the bandwidth allocation, etc., and finally form a set of optimized parameters.

[0035] Apply the optimized parameters to the channel configuration, update configuration items such as the communication protocol, encryption algorithm, and transmission strategy, and generate a new secure channel configuration scheme. Reconstruct the original encrypted data channel according to this configuration scheme, optimize the channel structure, and adjust the transmission strategy to finally establish a secure and reliable communication link.

[0036] For example, the identity characteristic code of a certain distribution terminal device is parsed and verified to confirm that it is a legal device with a security level of 3. Obtain the authentication information including the device ID (DID-8A92) and the communication permission code (AUTH-567). Configure the communication parameters based on the authentication information, set the transmission rate to 10 Mbps, the maximum packet length to 1500 bytes, and establish a data transmission channel. Statistically analyze the channel traffic for 5 minutes and record it in the traffic characteristic table. The average transmission rate is 8.5 Mbps, the peak rate is 9.8 Mbps, and the latency fluctuation range is 5 - 15 ms. Generate a 256-bit session key (SK-789F) based on these traffic characteristics. Encrypt the transmitted data using the session key, and group-encrypt the data packets in units of 64 bytes to generate an encrypted data stream. Calculate the 32-bit CRC check value for each encrypted data packet, continuously monitor 100 data packets, and find 2 check errors. Output the integrity identifier to show a 98% correct rate. Calculate the channel evaluation value based on this integrity index to be 0.95, trigger parameter optimization, adjust the encryption packet size to 128 bytes, and reduce the transmission rate to 8 Mbps to form a new set of optimized parameters. After updating the channel configuration, the reconstructed secure communication link maintains a 100% data correct rate in the subsequent 30-minute communication.

[0037] In a specific embodiment, the process of executing step S104 may specifically include the following steps: (1) Collect data on the quantum state information transmitted in the secure communication link to obtain a quantum state data stream, and perform time segmentation on the quantum state data stream through the quantum entanglement characteristic to form terminal operation data; (2) Identify noise on the terminal operation data according to the quantum state threshold to obtain a quantum noise set, and filter the quantum noise set according to the quantum state purity to generate a cleaned quantum state sequence; (3) Perform quantum state normalization calculation on the cleaned quantum state sequence to obtain normalized quantum data, and perform mapping transformation on the normalized quantum data through quantum state projection to output a normalized data set; (4) Construct quantum features based on the standardized data set to obtain a quantum feature combination, and perform mapping analysis on the quantum feature combination according to the quantum dimension to form a quantum state feature table; (5) Extract parameters from the quantum state feature table through the quantum correlation degree to obtain quantum key features, and sort the quantum key features according to the quantum state weight to generate a quantum feature matrix; (6) Perform multi-dimensional state superposition on the quantum feature matrix to obtain a device quantum state sequence, and integrate the device quantum state sequence through quantum state fusion to form a device behavior feature.

[0038] Specifically, the quantum state information transmitted in the secure communication link is collected in real time. The quantum state information is a quantization representation of the operating state of the terminal device, including the quantum encoding of the device's operating parameters, communication status, resource occupancy, and other information. These information are obtained through a quantum state collector and converted into a quantum state data stream. The quantum state data stream is a continuous sequence of quantum bits, and each quantum bit carries part of the device state information. Using the quantum entanglement property, the quantum state data stream is segmented according to time windows, and the data in each time window constitutes an independent quantum state sample, finally forming a data set describing the terminal operating state. Noise identification and filtering are performed on the obtained terminal operating data. The quantum state threshold is a preset quantum state purity standard for judging the noise components in the data. By comparing with the quantum state threshold, the quantum noise in the terminal operating data is identified, and these noises include data distortion caused by factors such as quantum decoherence effects and quantum measurement errors. The identified noise data are grouped into a quantum noise set, and then the noise data are filtered according to the quantum state purity index. The quantum state purity reflects the quality of the quantum state, and the higher the purity, the more stable the quantum state. After purity filtering, high-quality quantum state data are retained to form a cleaned quantum state sequence.

[0039] Normalize the cleaned quantum state sequence to map quantum state data of different scales to a unified value range. The quantum state normalization calculation takes into account the amplitude and phase information of the quantum state to ensure that the normalized data retains quantum characteristics. The standardized quantum data is projected onto a specific quantum state space through a quantum state projection operator to achieve data dimensionality reduction and feature extraction, and finally output a standardized data set. Quantum features are constructed based on the standardized data set. By the principle of quantum state superposition, multiple ground states are combined into a composite quantum state to form a quantum feature combination. Analyze the feature combination according to the quantum dimension. The quantum dimension describes the complexity and information capacity of the quantum state. The feature data is organized into a quantum state feature table through dimension mapping. Each row in the table corresponds to a quantum feature, and each column represents different quantum state parameters.

[0040] Analyze and extract the parameters in the quantum state feature table using the quantum correlation degree measurement method. The quantum correlation degree reflects the interaction strength between different quantum states. Select the most representative quantum features according to the magnitude of the correlation degree as the quantum key features. Sort the importance of these key features according to the quantum state weight. The weight value reflects the influence degree of each quantum feature on the device behavior, and finally generate a sorted quantum feature matrix. Perform multi-dimensional state superposition on each quantum state in the quantum feature matrix, and form a more complex quantum state structure through the coherent superposition of quantum states to obtain the device quantum state sequence. Finally, through the quantum state fusion algorithm, integrate the information in the quantum state sequence, extract the features that can best characterize the device behavior, and form the complete device behavior features.

[0041] For example, during the operation of a certain intelligent power distribution terminal, the state information of 100 qubits is collected per second by a quantum state collector, including the quantum state representations of parameters such as voltage, current, and power. Divide these quantum state information according to a 10ms time window to form quantum state samples containing 10 qubits. According to the preset quantum state threshold of 0.85, identify the noise data with a quantum state purity lower than the threshold. A total of 12 quantum state samples are found to be contaminated by quantum noise. Through quantum purity filtering, retain the samples with a purity greater than 0.9 to obtain 88 high-quality quantum state sequences. Normalize these sequences for the quantum state, and unify the value range of the quantum state into the interval [0,1]. Reduce the 10-dimensional quantum state data to a 6-dimensional feature vector through dimension mapping to construct a 6×88 quantum feature table. Calculate the quantum correlation degree and find that the correlation degrees of 4 quantum features exceed 0.8. Extract these features and sort them according to the weight to form a 4×88 quantum feature matrix. Finally, through quantum state superposition and fusion, integrate these features into a 256-bit device behavior feature code for subsequent device management and control.

[0042] In a specific embodiment, the process of executing step S105 may specifically include the following steps: (1) Perform quantum state statistics on the quantum access frequency, quantum access duration, and quantum access resources according to the device behavior features to obtain quantum state access data, and classify the quantum state access data according to the quantum access mode to form a quantum access sequence; (2) Through the quantum state comparison of the quantum access sequence, distinguish quantum out-of-limit access, quantum frequent access, and quantum abnormal time access to obtain a quantum abnormal set, and perform a hierarchical evaluation on the quantum abnormal set according to the quantum risk degree to generate a quantum risk sequence; (3) Quantize the terminal access permission according to the quantum state degree in the quantum risk sequence to obtain a quantum permission index, and segment the quantum permission index according to the quantum state threshold to form a hierarchical evaluation result; (4) Conduct quantum state statistics on the hierarchical evaluation results to obtain the quantum permission distribution. Calculate the quantum weights for the quantum permission distribution based on the proportion of quantum states, and generate a quantum evaluation matrix. (5) Dynamically adjust the terminal operation permissions through the quantum evaluation matrix to obtain quantum adjustment parameters. Update the quantum adjustment parameters according to the quantum refresh period, and output a quantum dynamic sequence. (6) Construct a quantum multi-level structure based on the quantum dynamic sequence to obtain a quantum classification table. Organize the quantum classification table according to the quantum inheritance relationship to form a permission management system.

[0043] Specifically, conduct quantum analysis on the terminal access behavior according to the device behavior characteristics. The quantum access frequency represents the quantum state representation of the number of accesses per unit time. The quantum access duration describes the quantum encoding of the duration of each access. The quantum access resource reflects the quantum state characteristics of the type and usage amount of the system resources accessed. Conduct quantum state statistics on these three dimensions, and convert the statistical results into quantum state access data. Classify and organize the quantum state access data according to different quantum access modes, such as regular access, emergency access, batch access, etc., and finally generate a quantum access sequence containing access characteristics. Conduct quantum state comparison and analysis on the generated quantum access sequence, and focus on identifying three types of abnormal access behaviors: Quantum over-limit access refers to an access attempt that exceeds the permission range. Quantum frequent access represents a high-frequency access behavior within a short period of time. Quantum abnormal time segment access refers to an access request during an abnormal time period. Classify the identified abnormal access behaviors into the quantum anomaly set and evaluate them according to the quantum risk degree index. The quantum risk degree is a comprehensive index that includes multiple quantum state parameters such as the degree of abnormality, the scope of influence, and the hazard level. Generate a quantum risk sequence through evaluation, and the sequence contains the risk rating information of various abnormal accesses.

[0044] Based on the risk levels recorded in the quantum risk sequence, conduct quantum processing on the access permissions of the terminal. The quantum processing converts the traditional discrete permission levels into continuous quantum state representations, and generates quantum permission indicators. Set the quantum state threshold as the boundary condition for permission classification, segment the quantum permission indicators, divide the permissions into multiple levels, and form a hierarchical evaluation result. Conduct quantum state statistical analysis on the hierarchical evaluation result, count the distribution of different permission levels, and form a quantum permission distribution. Calculate the corresponding quantum state weights according to the proportion of each permission level in the whole. The quantum state weight reflects the importance and influence of each permission level. Generate a quantum evaluation matrix through weight calculation, and the matrix contains the complete quantum state representation of the permission distribution.

[0045] The operating permissions of the terminal are adjusted in real time using a quantum evaluation matrix, and quantum adjustment parameters are generated based on the evaluation results in the matrix. The quantum adjustment parameters include the change amount and adjustment direction of the permission level. These adjustment parameters are updated regularly according to a preset quantum refresh period to ensure the timeliness of permission adjustment, and finally a quantum dynamic sequence reflecting the permission changes is output. A hierarchical permission structure is constructed based on the quantum dynamic sequence, different levels of permissions are organized into a quantum multi-level structure, and a quantum grading table is generated. The grading table is organized and optimized according to the quantum inheritance relationship, which defines the inclusion and derivation relationships between different permission levels, and finally a complete permission management system is formed.

[0046] For example, the device behavior characteristics of a certain distribution terminal device show that in the past 24 hours, the quantum access frequency was recorded as 30 times per hour, the average quantum access duration was 2 minutes, and the main resources accessed were distribution control and data acquisition. After quantum state statistics on these data, a quantum access sequence is classified as 80% regular access, 15% emergency access, and 5% bulk data access. Through quantum state comparison, it is found that there are 3 quantum over-limit accesses (attempting to access high-voltage switch control permissions), 5 quantum frequent accesses (more than 10 requests within 1 minute), and 2 quantum abnormal time period accesses (operation requests at 3 am). The evaluation results of the quantum risk degrees of these abnormal accesses are quantified as values between 0 and 1, where the over-limit access risk degree is 0.8, the frequent access risk degree is 0.6, and the abnormal time period access risk degree is 0.7. According to the risk assessment results, the terminal permissions are quantized, the original 5-level permissions are converted into quantum state representations, and a quantum state threshold of 0.7 is set as the downgrading condition. After hierarchical evaluation, the terminal permissions are downgraded from level 4 to level 3, and the updated quantum permission distribution shows that the proportion of level 3 permissions is 65%, the proportion of level 2 permissions is 25%, and the proportion of level 1 permissions is 10%. The permission configuration is updated according to a quantum refresh period of once every 4 hours, and finally the terminal is classified into the restricted operation category in the permission management system.

[0047] In a specific embodiment, the process of executing step S106 may specifically include the following steps: (1) Periodically perform quantum sampling on the quantum state operating status according to the permission management system to obtain quantum state samples, and check the quantum state samples according to the quantum state integrity to form system state snapshot data; (2) Quantum classify the system state snapshot data through quantum state parameters to obtain a quantum state classification set, and construct a quantum index for the quantum state classification set according to the quantum data structure to generate a quantum snapshot index table; (3) Perform quantum sharding processing on the quantum snapshot index table to obtain a quantum sharding set, and map the quantum sharding set to the quantum state according to the quantum storage node to form a distributed storage sequence; (4) Distribute the system snapshot data to quantum nodes according to the distributed storage sequence to obtain a quantum backup set, and verify the consistency of the quantum backup set through quantum state synchronization to form disaster recovery backup data; (5) Perform quantum backtracking analysis on the quantum historical state based on the disaster recovery backup data to obtain the quantum state change sequence, construct quantum relations for the quantum state change sequence based on the quantum correlation, and generate a quantum transfer table; (6) The quantum state of the system recovery point is located through the quantum transfer table to obtain the quantum recovery sequence, which is then sorted according to the quantum priority to form a system recovery strategy.

[0048] Specifically, according to the quantum state operation parameter requirements defined in the authority management system, the terminal equipment is periodically sampled for quantum states. Quantum state sampling collects the operating status information of the terminal equipment, including quantized power parameters, voltage parameters, communication status and other key indicators, with a cycle of every 10 seconds to form the original quantum state sample. The collected quantum state samples are integrity checked to verify the validity and integrity of each quantum state, and incomplete or damaged quantum state data are eliminated to finally form the system state snapshot data. The system state snapshot data is subjected to quantum state parameter analysis, and the data is divided into different quantum state categories according to the parameter characteristics, such as operating state, alarm state, fault state, etc., to obtain a quantum state classification set. An index relationship is established for the classified data based on the quantum data structure. The quantum data structure uses the superposition characteristics of the quantum state to encode the multi-dimensional state information into the quantum bit, and a quantum snapshot index table is generated by constructing a quantum index.

[0049] The quantum snapshot index table is split according to the quantum sharding strategy. Each shard contains a set of related quantum state information to form a quantum shard set. According to the pre-configured quantum storage node distribution, the quantum shard set is mapped to different storage nodes, and a mapping relationship from quantum state to physical storage location is established to generate a distributed storage sequence. The system snapshot data is distributed to each quantum node according to the distributed storage sequence. Each node stores part of the quantum state information to form a quantum backup set. The data consistency between each node is ensured through the quantum state synchronization mechanism. The quantum backup set is checked and compared to verify the integrity and consistency of the data, and finally reliable disaster recovery backup data is formed.

[0050] Perform quantum retrospective analysis on the historical operating status of the system based on disaster recovery backup data, focusing on analyzing the evolution process of quantum states, recording the rules and characteristics of state transitions, and generating a quantum state change sequence. Calculate the correlation relationship between different states through quantum correlation degree, construct a quantum state transfer network, and form a quantum transfer table. Use the quantum transfer table to locate the key recovery points of the system. These recovery points are the time nodes when the system state is stable and the data is complete. Organize these recovery points into a quantum recovery sequence. Sort the quantum recovery sequence according to business importance and recovery priority, and finally form the recovery strategy of the system.

[0051] For example, during the operation of an intelligent power distribution terminal, quantum state sampling is performed every 10 seconds, and quantum state information including parameters such as voltage (220V±5%), current (50A±2A), and power factor (0.95±0.02) is collected. A total of 8640 quantum state samples are collected within 24 hours, and 8500 valid samples are retained after integrity inspection. Classify these samples according to operating characteristics, among which the normal operating state accounts for 85%, the minor alarm state accounts for 12%, and the severe fault state accounts for 3%. Establish a quantum index for the classified data, use 4-bit encoding to represent the state type, and 8-bit encoding to represent the timestamp, forming a quantum snapshot index table. Divide the index table into 32 quantum shards, each shard contains approximately 266 quantum state records, and distribute them to 8 quantum storage nodes. Through the quantum state synchronization mechanism, ensure the consistency of data on each node, and the verification result shows that the data synchronization rate reaches 99.9%. Perform quantum retrospective analysis on 30 days of historical data, find that the device has experienced 5 state transitions, and establish a quantum transfer table containing 15 key recovery points. According to the degree of business impact, divide these recovery points into 3 priorities, and construct a multi-level recovery strategy covering 1 hour, 6 hours, and 24 hours.

[0052] The above describes the management method of the power distribution IoT terminal based on quantum cloud code in the embodiments of the present application. Next, the management system of the power distribution IoT terminal based on quantum cloud code in the embodiments of the present application will be described. Please refer to Figure 2 , an embodiment of the management system of the power distribution IoT terminal based on quantum cloud code in the embodiments of the present application includes: An encryption module for performing confusion processing on the original data through a random number generator to obtain a quantum cloud code seed, performing shard encryption on the quantum cloud code seed to obtain a quantum cloud code sequence, and performing group matching on the quantum cloud code sequence according to a preset rule to form a terminal device group key; An extraction module for extracting the hardware identification data of the terminal device based on the terminal device group key, and performing feature synthesis on the hardware identification data in combination with the terminal operating state information to generate a device identity feature code; A building module, configured to establish a data transmission channel according to the device identity feature code, encrypt the data transmission channel through a session key to establish an encrypted data channel, perform integrity verification on the encrypted data channel, and form a secure communication link; A cleaning module, configured to collect the terminal operation data in the secure communication link, perform data cleaning and normalization processing on the terminal operation data to obtain a standardized data set, and perform feature mapping according to the standardized data set to output device behavior features; A grading module, configured to perform a grading evaluation on the terminal access permissions according to the device behavior features, dynamically adjust the terminal operation permissions through the grading evaluation results, and construct a permission management system; A snapshot module, configured to perform a regular snapshot on the system operation state according to the permission management system, perform distributed backup on the system snapshot data to form disaster recovery backup data, and establish a system recovery policy according to the disaster recovery backup data.

[0053] Through the collaborative cooperation of the above-mentioned various components, the original data is obfuscated by a random number generator, realizing the high randomness and unpredictability of the data, effectively preventing the data from being stolen and tampered with. The quantum cloud code seeds are processed by using the sharding encryption technology, improving the security and reliability of the data. Through the generation and distribution of the terminal device group keys, the accurate identification and classification management of the terminal devices are realized, enhancing the security control ability of the system. The hardware identification data is extracted based on the terminal device group keys, and the device identity feature code is generated in combination with the terminal operation status information, ensuring the uniqueness and verifiability of the device identity. The established data transmission channel is encrypted through the session key, and integrity verification is performed at the same time to form a secure communication link, ensuring the security and integrity of the data transmission. The terminal operation data in the secure communication link is collected and processed, and a standardized data set is obtained through data cleaning and normalization processing, improving the quality and usability of the data. Feature mapping is performed according to the standardized data set, accurately outputting the device behavior features, providing a reliable basis for subsequent permission management. The terminal access permissions are graded and evaluated according to the device behavior features, realizing the dynamic adjustment of the permissions, and constructing a flexible and effective permission management system. Through the regular snapshot and distributed backup mechanisms, perfect disaster recovery backup data is formed, ensuring the recoverability of the system data. A system recovery policy is established according to the disaster recovery backup data, improving the reliability and continuous operation ability of the system. The overall solution realizes the secure access, reliable communication, dynamic management and effective recovery of the power distribution IoT terminals, significantly improving the security, reliability and management efficiency of the power distribution IoT network.

[0054] Based on the same inventive concept, an embodiment of the present application further provides an electronic device. Refer to Figure 3As shown in the figure, it is a schematic structural diagram of an electronic device 300 provided by an embodiment of the present application, including a processor 301, a memory 302, and a bus 303. Among them, the memory 302 is used to store execution instructions, including an internal memory 3021 and an external memory 3022; the internal memory 3021 here is also called the main memory, which is used to temporarily store the operation data in the processor 301 and the data exchanged with the external memory 3022 such as a hard disk. The processor 301 exchanges data with the external memory 3022 through the internal memory 3021. When the electronic device 300 runs, the processor 301 communicates with the memory 302 through the bus 303.

[0055] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A management method for a power distribution IoT terminal based on quantum cloud codes, characterized in that, The distribution IoT terminal management method based on quantum cloud code includes: The original data is obfuscated by a random number generator to obtain a quantum cloud code seed. The quantum cloud code seed is encrypted by sharding to obtain a quantum cloud code sequence. The quantum cloud code sequence is grouped and matched according to a preset rule to form a terminal device group key. Based on the terminal device group key, the hardware identification data of the terminal device is extracted, and the hardware identification data is feature synthesized in combination with the terminal operation status information to generate a device identity feature code. According to the device identity feature code, a data transmission channel is established, and the data transmission channel is encrypted by a session key to establish an encrypted data channel. The integrity of the encrypted data channel is verified to form a secure communication link. The terminal operation data in the secure communication link is collected, and the terminal operation data is subjected to data cleaning and normalization processing to obtain a standardized data set. Feature mapping is performed according to the standardized data set to output device behavior features. Based on the device behavior features, the terminal access permissions are hierarchically evaluated, and the terminal operation permissions are dynamically adjusted according to the hierarchical evaluation results to construct a permission management system. According to the permission management system, a periodic snapshot of the system operation state is taken, and the system snapshot data is distributed and backed up to form disaster recovery backup data. A system recovery strategy is established according to the disaster recovery backup data.

2. The distribution IoT terminal management method based on quantum cloud code according to claim 1, characterized in that, The step of obfuscating the original data by a random number generator to obtain a quantum cloud code seed, encrypting the quantum cloud code seed by sharding to obtain a quantum cloud code sequence, and grouping and matching the quantum cloud code sequence according to a preset rule to form a terminal device group key includes: The operation parameters of the distribution terminal are randomly mapped by a random number generator to generate an original obfuscation matrix, and a random perturbation vector is constructed based on the original obfuscation matrix. The original data is non-linearly transformed according to the random perturbation vector to obtain an initial obfuscated data stream, and the initial obfuscated data stream is data recombined by piecewise linear transformation to form a quantum cloud code seed. Based on the quantum cloud code seed, a data sharding index table is established, and the quantum cloud code seed is sliced by a dynamic sharding algorithm to obtain a set of quantum cloud code slices. The set of quantum cloud code slices is encrypted and transformed according to a symmetric encryption algorithm to output an encrypted slice sequence, and the encrypted slice sequence is sorted and combined by a data reconstruction algorithm to generate a quantum cloud code sequence. Grouping calculation is performed on the quantum cloud code sequence by hierarchical clustering to obtain a grouping feature vector, and a terminal grouping mapping table is constructed based on the grouping feature vector. According to the terminal grouping mapping table, key distribution is performed on the terminal device, and the key parameters of each group are calculated by a key derivation function to form a terminal device group key.

3. The management method of the power distribution IoT terminal based on the quantum cloud code according to claim 1, wherein The step of extracting the hardware identification data of the terminal device based on the terminal device group key, and feature synthesizing the hardware identification data in combination with the terminal operation status information to generate a device identity feature code includes: Identify and resolve the terminal device through the group key of the terminal device to obtain the hardware data stream, classify the data according to the hardware data stream, and form the hardware identification data; Collect and count the resource occupancy index, communication load parameter, and power consumption value of the terminal device to obtain the operation parameter set, and perform timing integration on the operation parameter set through time synchronization to generate the terminal operation status information; Extract features from the hardware identification data according to data dimensionality reduction to obtain the hardware feature set, and remove redundant data in the hardware feature set according to data filtering to form the hardware feature vector; Combine data according to the terminal operation status information and the hardware feature vector to obtain the multi-dimensional feature table, and extract key values from the multi-dimensional feature table through feature screening to generate the core feature matrix; Perform non-linear mapping on the core feature matrix according to feature transformation to obtain the feature space sequence, and sort the importance of the feature space sequence according to the variable correlation degree to form the feature identification set; Perform encryption transformation on the feature identification set through digital signature to obtain the identity identification sequence, and encrypt the identity identification sequence according to the encryption key to form the device identity feature code.

4. The management method of the power distribution IoT terminal based on quantum cloud code according to claim 1, characterized in that Establish a data transmission channel according to the device identity feature code, encrypt the data transmission channel through the session key, establish an encrypted data channel, and perform integrity verification on the encrypted data channel to form a secure communication link, including: Authenticate and verify the device identity feature code through data parsing to obtain the channel authentication information, and perform connection configuration according to the channel authentication information to establish a data transmission channel; Perform periodic statistics on the data traffic characteristics of the data transmission channel to obtain the traffic feature table, and perform conversion calculation on the traffic feature table through key generation to form the session key; Perform encryption operation on the data packets of the data transmission channel according to the session key to obtain the encrypted data stream, and construct the channel for the encrypted data stream according to data recombination to generate the encrypted data channel; Calculate the checksum of the data packet header of the encrypted data channel to obtain the check sequence, and perform verification operation on the check sequence through data comparison to output the integrity identification; Perform reliability calculation on the encrypted data channel according to the integrity identification to obtain the channel evaluation value, and perform optimization adjustment according to the channel evaluation value to form the optimization parameter group; Perform parameter update on the optimization parameter group through channel configuration to obtain the secure channel configuration, and reconstruct the encrypted data channel according to the secure channel configuration to form a secure communication link.

5. The management method of the power distribution IoT terminal based on quantum cloud code according to claim 1, wherein, Collect the terminal operation data in the secure communication link, perform data cleaning and normalization processing on the terminal operation data to obtain the standardized data set, and perform feature mapping according to the standardized data set to output the device behavior feature, including: Collect the quantum state information transmitted in the secure communication link to obtain the quantum state data stream, and perform time division on the quantum state data stream through the quantum entanglement characteristic to form the terminal operation data; Perform noise identification on the terminal operation data according to the quantum state threshold to obtain a quantum noise set, and filter the data of the quantum noise set according to the quantum state purity to generate a cleaned quantum state sequence; Perform quantum state normalization calculation on the cleaned quantum state sequence to obtain standardized quantum data, and perform mapping transformation on the standardized quantum data through quantum state projection to output a standardized data set; Construct quantum features based on the standardized data set to obtain a quantum feature combination, and perform mapping analysis on the quantum feature combination according to the quantum dimension to form a quantum state feature table; Extract parameters from the quantum state feature table through the quantum correlation degree to obtain quantum key features, and sort the quantum key features according to the quantum state weight to generate a quantum feature matrix; Perform multi-dimensional state superposition on the quantum feature matrix to obtain a device quantum state sequence, and integrate the device quantum state sequence through quantum state fusion to form a device behavior feature.

6. The distribution IoT terminal management method based on quantum cloud code according to claim 1, characterized in that, Perform hierarchical evaluation on the terminal access permission according to the device behavior feature, and dynamically adjust the terminal operation permission through the hierarchical evaluation result to construct a permission management system, including: Perform quantum state statistics on the quantum access frequency, quantum access duration, and quantum access resources according to the device behavior feature to obtain quantum state access data, and classify the quantum state access data according to the quantum access mode to form a quantum access sequence; Identify quantum out-of-limit access, quantum frequent access, and quantum abnormal time access through the quantum state comparison of the quantum access sequence to obtain a quantum abnormal set, and perform hierarchical evaluation on the quantum abnormal set according to the quantum risk degree to generate a quantum risk sequence; Perform quantization processing on the terminal access permission according to the quantum state degree in the quantum risk sequence to obtain a quantum permission index, and segment the quantum permission index according to the quantum state threshold to form a hierarchical evaluation result; Perform quantum state statistics on the hierarchical evaluation result to obtain a quantum permission distribution, and calculate the quantum weight of the quantum permission distribution according to the quantum state occupancy ratio to generate a quantum evaluation matrix; Dynamically adjust the terminal operation permission through the quantum evaluation matrix to obtain a quantum adjustment parameter, and update the quantum adjustment parameter according to the quantum refresh period to output a quantum dynamic sequence; Construct a quantum multi-level structure according to the quantum dynamic sequence to obtain a quantum grading table, and organize the quantum grading table according to the quantum inheritance relationship to form a permission management system.

7. The method for managing a power distribution IoT terminal based on a quantum cloud code according to claim 6, wherein Take a regular snapshot of the system operation state according to the permission management system, perform distributed backup on the system snapshot data to form disaster recovery backup data, and establish a system recovery strategy according to the disaster recovery backup data, including: Perform periodic quantum sampling on the quantum state operation state according to the permission management system to obtain a quantum state sample, and inspect the quantum state sample according to the quantum state integrity to form system state snapshot data; Perform quantum classification on the system state snapshot data through quantum state parameters to obtain a quantum state classification set, and construct a quantum index for the quantum state classification set based on the quantum data structure to generate a quantum snapshot index table; Perform quantum sharding processing on the quantum snapshot index table to obtain a quantum sharding set, and perform quantum state mapping on the quantum sharding set according to quantum storage nodes to form a distributed storage sequence; Perform quantum node distribution on the system snapshot data according to the distributed storage sequence to obtain a quantum backup set, and perform consistency verification on the quantum backup set through quantum state synchronization to form disaster recovery backup data; Perform quantum backtracking analysis on the quantum historical state based on the disaster recovery backup data to obtain a quantum state change sequence, and construct a quantum relationship for the quantum state change sequence according to the quantum correlation degree to generate a quantum transfer table; Perform quantum state positioning on the system recovery point through the quantum transfer table to obtain a quantum recovery sequence, and sort the quantum recovery sequence according to the quantum priority to form a system recovery strategy.

8. A distribution Internet of Things terminal management system based on quantum cloud codes, which is used to implement the distribution Internet of Things terminal management method based on quantum cloud codes as described in any one of claims 1-7, and is characterized in that, The power distribution IoT terminal management system based on quantum cloud code includes: An encryption module for performing confusion processing on the original data through a random number generator to obtain a quantum cloud code seed, performing sharding encryption on the quantum cloud code seed to obtain a quantum cloud code sequence, and performing group matching on the quantum cloud code sequence according to a preset rule to form a terminal device group key; An extraction module for extracting the hardware identification data of the terminal device based on the terminal device group key, and performing feature synthesis on the hardware identification data in combination with the terminal operation status information to generate a device identity feature code; A establishment module for establishing a data transmission channel according to the device identity feature code, encrypting the data transmission channel through a session key to establish an encrypted data channel, and performing integrity verification on the encrypted data channel to form a secure communication link; A cleaning module for collecting the terminal operation data in the secure communication link, performing data cleaning and normalization processing on the terminal operation data to obtain a standardized data set, and performing feature mapping according to the standardized data set to output device behavior features; A grading module for performing grading evaluation on the terminal access authority according to the device behavior features, dynamically adjusting the terminal operation authority through the grading evaluation result, and constructing an authority management system; A snapshot module for performing regular snapshots on the system operation state according to the authority management system, performing distributed backup on the system snapshot data to form disaster recovery backup data, and establishing a system recovery strategy according to the disaster recovery backup data.

9. An electronic device, characterized in that, Includes: A processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of the power distribution IoT terminal management method based on quantum cloud code as described in any one of claims 1 to 7 are executed.

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