Internet of Things data transmission system based on quantum secret communication

Abstract

The invention discloses an Internet of Things data transmission system based on quantum secret communication, relates to the technical field of Internet of Things security, and solves the technical problem that the existing quantum encryption technology is difficult to meet the data transmission security of Internet of Things equipment. According to the method, the performance bottleneck and the storage risk of quantum key generation are comprehensively considered, the generation and storage time of the quantum key is limited, and specifically, the data volume needing to be transmitted by the data transfer node in the set period is predicted according to the data transmission record of the Internet of Things equipment; on the basis of the data volume, a set period is divided into a plurality of time periods, the number of quantum keys required by the plurality of time periods is predicted, and then the quantum keys are stored in a safe storage medium in a pre-charging mode; the time period is reasonably determined according to the quantum key generation efficiency, the requirement of each time period for the quantum key can be ensured, and the data transmission security of the Internet of Things equipment is improved.

Description

Technical Field

[0001] The present application belongs to the field of Internet of Things security technology, and specifically is an Internet of Things data transmission system based on quantum secure communication. Background Art

[0002] The management of IoT devices is a key link in the application of IoT technology. However, with the massive increase in IoT devices, the management of IoT devices has brought a lot of problems that need to be solved, such as device compatibility, data security, energy consumption management, etc. Data security is the top priority.

[0003] IoT devices collect a large amount of basic data due to their technical characteristics, and they are used in various fields of life and production. At present, the encryption of IoT devices mainly relies on encryption algorithms, such as symmetric encryption algorithms, asymmetric encryption algorithms, hash algorithms, lightweight encryption algorithms, etc. These encryption algorithms can be cracked with sufficient computing power. Once the encryption algorithm is cracked, it is very likely to lead to the leakage of business secrets and privacy information, which will have a great adverse impact.

[0004] The present application provides an Internet of Things data transmission system based on quantum secure communication to solve the above technical problems. Summary of the invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art; to this end, the present application proposes an Internet of Things data transmission system based on quantum secure communication, which is used to solve the technical problem that existing quantum encryption technology is difficult to meet the data transmission security of Internet of Things devices.

[0006] To achieve the above-mentioned purpose, the first aspect of the present application provides an Internet of Things data transmission system based on quantum secure communication, comprising: a cloud platform, and a plurality of data transfer nodes connected thereto; each data transfer node is connected to a plurality of Internet of Things devices;

[0007] Cloud platform: used to predict the data transmission volume of the data transfer node in each time period of the set cycle, and determine the key demand in the time period according to the data transmission volume; and

[0008] Generate quantum keys through the quantum key distribution network, and pre-fill the quantum keys required for each time period into the secure storage medium of the data transfer node;

[0009] The data transfer node is used to encrypt the received data using a pre-charged quantum key and transmit the encrypted data to the cloud platform; wherein the received data is processed by an encryption algorithm.

[0010] Preferably, predicting the data transmission volume of the data transfer node in each time period of the set cycle includes:

[0011] Extract the data transmission records of IoT devices connected to the data transfer node, and predict the data generation volume of each IoT device in a set period based on the data transmission records;

[0012] The data generated by IoT devices is aggregated to obtain the predicted data volume of the data transfer node in a set period; the predicted data volume is divided according to pre-set time periods to obtain the data transmission volume of each time period; among which, the time periods are obtained according to the efficiency of quantum key generation.

[0013] Preferably, the polymerization process comprises:

[0014] According to the data aggregation record of the data transfer node, the characteristic value of each aggregation parameter is obtained; wherein the aggregation parameters include compression rate, deduplication rate, protocol overhead rate and data aggregation rate, and the characteristic value includes mean value or maximum value;

[0015] The aggregation factor is calculated based on the aggregation parameters; the aggregation factor is multiplied by the data generation amount of the IoT device to obtain the predicted data volume of the data transfer node.

[0016] Preferably, the time periods are divided and acquired according to the quantum key generation efficiency, including:

[0017] A time range is selected from the initial position of the set period, and the time range is verified by predicting the amount of data. After verification, the time range is used as time period one;

[0018] Based on the quantum key generation efficiency, the quantum key generation amount in time period one, the next time range is determined according to the quantum key generation amount as time period two; and this is carried out in sequence until the set period is divided.

[0019] Preferably, determining the next time range according to the quantum key generation amount includes:

[0020] The quantum key generation amount corresponding to time period 1 is calculated taking into account network fluctuations and marked as MSL; the upper limit of the time range corresponding to time period 1 is marked as T d ;

[0021] A data prediction function is constructed according to the predicted data volume, which is marked as F(t); wherein the data prediction function represents the functional relationship between the predicted data volume and time within a set period;

[0022] By solving the inequality Get time T u , will [T d , T u ] as the time range corresponding to time period 2.

[0023] Preferably, calculating the quantum key generation amount corresponding to time period one while taking network fluctuation into consideration includes:

[0024] Predicting the network fluctuation parameters of quantum channels According to the formula Calculate the quantum key generation rate R under the influence of network fluctuations; where R0 is the quantum key generation rate without the influence of network fluctuations;

[0025] The quantum key generation amount in time period one is calculated according to the quantum key generation rate R.

[0026] Preferably, predicting and obtaining network fluctuation parameters of the quantum channel includes:

[0027] Extracting several network fluctuation parameters of quantum channel history;

[0028] Based on several network fluctuation parameters, the network fluctuation parameters of time period one are predicted using exponential smoothing method.

[0029] Preferably, the quantum key required for each time period is pre-filled into a secure storage medium of a data transfer node, including:

[0030] A quantum key is generated through the quantum key distribution network in the current time period, and the generated quantum key is pre-filled into a secure storage medium in a timely manner for use in data encryption in the next time period.

[0031] Preferably, in the process of injecting quantum keys into a secure storage medium, when the number of pre-injected quantum keys has met the quantity requirement of the next time period; it is determined whether there is still time to generate a new quantum key in the current time period; if yes, the injected quantum key is replaced by the newly generated quantum key.

[0032] Preferably, the cloud platform is connected to a number of data transfer nodes, and each data transfer node is connected to a number of IoT devices respectively;

[0033] The cloud platform generates quantum keys for data transfer nodes through the quantum key distribution network.

[0034] Compared with the prior art, the beneficial effects of this application are:

[0035] This application predicts the amount of data that a data transfer node needs to transmit in a set period based on the data transmission records of IoT devices; based on the data volume, the set period is divided into several time periods, and the number of quantum keys required for several time periods is predicted, and then the quantum keys are stored in a secure storage medium by pre-filling; this application reasonably determines the time period based on the efficiency of quantum key generation, which can ensure the demand for quantum keys in each time period and improve the data transmission security of IoT devices.

[0036] In the process of charging quantum keys into a secure storage medium, when the number of pre-charged quantum keys has met the quantity requirement of the next time period, the charged quantum keys are replaced by newly generated quantum keys. The application shortens the storage time and reduces the risk of quantum key leakage by screening and updating the stored quantum keys, thereby further improving the data transmission security of IoT devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 This is a schematic diagram of the data encryption transmission process of the Internet of Things device in the first embodiment of the present application;

[0039] Figure 2 This is a schematic diagram of the process of dividing each time period in a setting cycle in Example 1 of the present application; DETAILED DESCRIPTION

[0040] The technical solution of the present application will be described clearly and completely in conjunction with the embodiments below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0041] IoT devices are widely used in daily life and production. For example, the power industry can monitor users' electricity consumption through smart meters, factories can collect production data through IoT devices, and residents can use IoT devices to realize smart homes. With the substantial increase in IoT devices, more and more problems have been exposed, such as compatibility issues, energy consumption management issues, data security issues, etc. Data security is of utmost importance. If IoT devices cannot guarantee data security during the process of collecting and transmitting data, data loss may lead to inability to make effective decisions, or even leakage of commercial secrets or privacy information. It can be seen that once data security cannot be guaranteed, the application scenarios of IoT technology will be greatly limited.

[0042] The present application provides an Internet of Things data transmission system based on quantum secure communication. The method mainly solves the problem of data security. A data encryption strategy is generated at the remote end, and the data transmission of each Internet of Things device is encrypted and controlled according to the encryption strategy to improve data security.

[0043] See also Figure 1 , the first embodiment of the present application provides an Internet of Things data transmission system based on quantum secure communication, including: a cloud platform, and a number of data transfer nodes connected thereto; each data transfer node is connected to a number of Internet of Things devices;

[0044] Cloud platform: used to predict the data transmission volume of the data transfer node in each time period of the set cycle, and determine the key demand in the time period according to the data transmission volume; and

[0045] Generate quantum keys through the quantum key distribution network, and pre-fill the quantum keys required for each time period into the secure storage medium of the data transfer node;

[0046] The data transfer node is used to encrypt the received data using a pre-charged quantum key and transmit the encrypted data to the cloud platform; wherein the received data is processed by an encryption algorithm.

[0047] In the field of IoT technology, data generated by IoT devices is generally encrypted using encryption algorithms, such as symmetric encryption algorithms, asymmetric encryption algorithms, etc. However, there are still many ways to crack the data encrypted by these encryption algorithms. With the development of computer technology, the above encryption algorithms can be cracked with sufficient computing power. Moreover, with the advent of quantum computers, the cracking efficiency of the above encryption algorithms will be greatly improved.

[0048] From the perspective of data security, data encryption through quantum encryption technology currently seems to be able to meet data security requirements, and quantum encryption technology provides unconditional security, which is determined by the nature of quantum encryption technology itself.

[0049] The system architecture of this embodiment includes a cloud platform, a data transfer node and an IoT device. The cloud platform and the data transfer node can refer to edge computing technology, that is, the cloud platform is used as a central processor and the data transfer node is used as an edge computing server. The cloud platform is connected to multiple data transfer nodes, and each data transfer node is connected to multiple IoT devices to build an IoT network.

[0050] The practical application of the above system architecture can be referred to as follows: for a single enterprise, the cloud platform is the enterprise's central processor, responsible for the analysis and decision-making of all data; the data transfer node can be set up in the subsidiary company of the enterprise to collect relevant data of the corresponding subsidiary company; the IoT devices in the subsidiary company are associated with the data transfer node of the subsidiary company, and the collected data is sent to the cloud platform through the data transfer node.

[0051] For residents, the cloud platform is the central processor of the smart home in their house, the data transfer node is the gateway in the smart home, and the Internet of Things devices include various smart home devices, such as sweeping robots, indoor monitoring, etc.

[0052] The quantum key of this embodiment is mainly used in data transfer nodes, that is, the data of each IoT device is encrypted by the quantum key at the data transfer node, and then the encrypted data is sent to the cloud platform. According to the principle of quantum key generation, once the data is encrypted by the generated quantum key, the security of the data is guaranteed, that is, the security of data transmission is guaranteed.

[0053] Since quantum key generation is limited by many factors, if the instantaneous data volume at the data transfer node is too large, the quantum key generated online will be difficult to meet the encryption requirements. Therefore, the quantum key is pre-filled into the data transfer node through pre-filling, and the pre-filled quantum key is used for encryption when it is used. However, the pre-filled quantum key has an obvious disadvantage, that is, the longer the quantum key is stored in the secure storage medium, the easier it is to leak, and the encryption security will decrease when the quantum key is used to encrypt data.

[0054] To solve this problem, this embodiment first predicts the data transmission volume of the data transfer node in each time period of the set cycle, and determines the key demand in the time period according to the data transmission volume. For details, refer to the following steps:

[0055] Extract the data transmission records of IoT devices connected to the data transfer node, and predict the data generation volume of each IoT device in a set period based on the data transmission records;

[0056] The data generated by IoT devices is aggregated to obtain the predicted data volume of the data transfer node in a set period; the predicted data volume is divided according to pre-set time periods to obtain the data transmission volume of each time period; among which, the time periods are obtained according to the efficiency of quantum key generation.

[0057] Taking a single data transfer node as an example, extract the data transmission records of the IoT devices connected to it. Data transmission records refer to data records generated by IoT devices and sent to data transfer nodes in the past period of time, including timestamps, number of data packets, etc. Feature extraction is performed on the data in the data transmission records to generate a data training set, which is used to train machine learning models, such as convolutional neural networks, recursive neural networks, etc. The trained machine model can predict the amount of data generated by IoT devices. The training and use methods of machine learning models can refer to the technical solutions disclosed in the prior art.

[0058] The purpose of setting a period is to introduce time characteristics to improve the accuracy of data generation prediction. The set period can be set to one day, one week, etc., which can be determined based on the data processing volume of the data transfer node or the IoT device connected to it. If the data processing volume is large, the set period can be set smaller, and if the data processing volume is small, the set period can be set larger.

[0059] After predicting the amount of data generated by each IoT device within a set period, the data transfer node needs to perform aggregation processing before sending the data to the cloud platform. The number of quantum keys required cannot be determined based on the amount of data generated, because the data will be aggregated during the data aggregation process to compress the amount of data to be sent. The specific steps of the aggregation process are as follows:

[0060] The characteristic values ​​of various aggregation parameters are obtained according to the data aggregation records of the data transfer nodes. The aggregation parameters mainly include compression rate, deduplication rate, protocol overhead rate and data aggregation rate.

[0061] The compression ratio refers to the ratio of the compressed data volume to the original data volume, the deduplication ratio refers to the ratio of the deduplication and filtering data volume to the original data volume, the protocol overhead ratio refers to the ratio of the protocol overhead data volume to the original data volume, and the data aggregation ratio refers to the ratio of the aggregated data volume to the original data volume. It should be noted that the above-mentioned original data volume is only for each step. If compression is the first step, the original data volume corresponding to the compression ratio is the data volume received by the data transfer node, and the data volume after compression is the original data volume of the next step, and so on.

[0062] The compression rate, deduplication rate, protocol overhead rate, and data aggregation rate are marked as YSL, QCL, XKL, and SJL, respectively; the aggregation factor = YSL × QCL × XKL × SJL. Multiplying the aggregation factor by the data generation amount of the IoT device can obtain the predicted data volume of the data transfer node in the set period.

[0063] Assumptions: data compression rate is 0.8 (the amount of data after compression is 80% of the original amount of data), deduplication and filtering rate is 0.9 (the amount of data after deduplication and filtering is 90% of the amount of data after compression), protocol overhead rate is 0.95 (the amount of data after protocol overhead is 95% of the amount of data after deduplication and filtering), data aggregation rate is 0.9 (the amount of data after aggregation is 90% of the amount of data after protocol overhead); aggregation factor = 0.8 × 0.9 × 0.95 × 0.9 = 0.612. This shows that the amount of data is reduced by 38.8% after aggregation processing.

[0064] Based on the above calculation process, the characteristic value of the aggregation parameter can use the mean, that is, the average value of each aggregation parameter in the data aggregation record. Of course, the maximum value can also be selected as the characteristic value of the corresponding aggregation parameter. Selecting the maximum value can increase the aggregation factor, and the amount of predicted data corresponding to the data transfer node will increase relatively, which will in turn affect the demand for quantum keys. Therefore, using the maximum value as the characteristic value can indirectly provide the redundancy of the quantum key to avoid the actual generated quantum key failing to meet the encryption requirements of the data transfer node.

[0065] Although one of the characteristics of quantum encryption technology is unconditional security, there are also situations where quantum keys are leaked and data security is affected. There are obvious differences between online and offline distribution of quantum keys. Specifically, online distribution of quantum keys is more secure than offline distribution, but online distribution has performance bottlenecks and has high environmental requirements. Although offline distribution has the problem of long quantum key generation time and easy leakage, as long as its storage time is effectively controlled and updated in time, the encryption security is not much different from online distribution. The time period in this embodiment is the basis for effective control.

[0066] See also Figure 2 The time periods of this embodiment are obtained by dividing according to the quantum key generation efficiency, including:

[0067] A time range is selected from the initial position of the set period, and the time range is verified by predicting the amount of data. After verification, the time range is used as time period one;

[0068] Based on the quantum key generation efficiency, the quantum key generation amount in time period one, the next time range is determined according to the quantum key generation amount as time period two; and this is carried out in sequence until the set period is divided.

[0069] A time range is selected from the initial position of the set period. If the set period is one day [00:00, 24:00], a time range is selected from 0:00, such as 00:00-01:00, that is, the duration of the time range is one hour. Then the amount of data corresponding to the time range is calculated based on the predicted data volume. If the number of quantum keys can meet the encryption requirements of the data volume, the corresponding time range is used as time period one. It should be noted that the quantum key for judging whether the amount of data meets the requirements can be a quantum key pre-filled in a secure storage medium. For example, in order to verify the above time range, a fixed number of quantum keys are pre-filled in the secure storage medium, which is specifically used to verify the first time range of each set period. Theoretically, the smaller the selected time range, the smaller the corresponding amount of data, and the easier it is to verify; therefore, the time range can be selected to be very small.

[0070] In some other preferred embodiments, a time range may be selected from any set period, rather than necessarily from the initial position.

[0071] The quantum key used in time period 1 is pre-filled, that is, it has been stored in the secure storage medium before time period 1. The stored quantum key can be directly retrieved when encrypting data in time period 1. Of course, time period 1 can also continue to fill quantum keys, and the quantum keys filled in this time period are used for data encryption in the next time period. The solution process for the time range corresponding to the next time period is as follows:

[0072] The quantum key generation amount corresponding to time period 1 is calculated taking into account network fluctuations and marked as MSL; the upper limit of the time range corresponding to time period 1 is marked as T d ;

[0073] A data prediction function is constructed based on the predicted data volume, which is marked as F(t); wherein the data prediction function represents the functional relationship between the predicted data volume and time within a set period;

[0074] By solving the inequality Get time T u , will [T d , T u ] as the time range corresponding to time period 2.

[0075] The solution process is described in detail:

[0076] Assuming that the number of quantum keys generated in time period 1 is MSL considering network fluctuations, it means that the amount of data in the next time period needs to be encrypted by MSL quantum keys. If the amount of data is too much, the amount of quantum key data is insufficient, and some data will certainly not be encrypted by quantum key, so the amount of data in the next time period needs to be limited.

[0077] When the predicted data volume of the data transfer node is known, a data prediction function is constructed with time as the independent variable, and the result of integrating the data prediction function is the total amount of data in the corresponding range. Based on this theory, the above inequality can be constructed. The lower limit of the integral range is the end of the previous time period, and the upper limit of the integral is the unknown quantity that needs to be solved. The specific solution process will not be repeated. It should be noted that the predicted data generation volume of the IoT device is actually how much data the IoT device will generate at each moment in the future. The function can be established with time as the independent variable. Similarly, the data prediction function of the data transfer node can also be constructed.

[0078] According to the above steps, after the time range of the previous time period is determined, the number of quantum keys that can be generated in the corresponding time period can be calculated, and then the reasonable time range of the next time period can be calculated in combination with the data prediction function to guide the division of all set periods.

[0079] Calculating the quantum key generation amount corresponding to time period one considering network fluctuations means considering the impact of network fluctuations on the quantum key generation rate. For details, please refer to the formula Calculate the quantum key generation rate R under the influence of network fluctuations; where R0 is the quantum key generation rate without the influence of network fluctuations. Multiply the quantum key generation rate by the time range of the time period to get the number of quantum keys that can be generated.

[0080] The network fluctuation parameter in the above formula is The value of is [0, 1]. A value of 0 indicates that the network has no fluctuations. When the value is close to 1, it indicates that the network fluctuations are serious. The network fluctuation parameter can be understood as the degree of influence of network fluctuations on quantum key generation, which can be predicted by exponential smoothing method. Specifically:

[0081] Several network fluctuation parameters of the quantum channel between the data transfer node and the cloud platform are extracted, and then a prediction function is established based on the exponential smoothing method to predict the network fluctuation parameters of time period one.

[0082] In some other preferred embodiments, Gaussian analysis or Chernoff-Hoffding bounds can be used to perform statistical fluctuation analysis on the QKD protocol to estimate the key generation rate under different network fluctuation conditions. Many algorithms for evaluating the impact of network fluctuations on quantum key generation rates are disclosed in existing solutions. You can choose any one and do not need to be limited to the solution provided in this embodiment.

[0083] Embodiment 2: Compared with Embodiment 1, this embodiment manages the update of the quantum key pre-charged into the secure storage medium in each time period.

[0084] The quantum keys required for each time period are pre-filled into the secure storage medium of the data transfer node, including: generating quantum keys through the quantum key distribution network in the current time period, and pre-filling the generated quantum keys into the secure storage medium in a timely manner for use in data encryption in the next time period.

[0085] In the process of injecting quantum keys into a secure storage medium, when the number of pre-injected quantum keys has met the quantity requirement of the next time period; determine whether there is still time to generate a new quantum key in the current time period; if so, replace the injected quantum key with the newly generated quantum key.

[0086] Since the influence of network fluctuations is taken into account, the efficiency of quantum key generation in each time period fluctuates. Therefore, when the network conditions are good and the pre-filled quantum keys have met the quantity requirements of the next time period, there is no need to continue to generate quantum keys. Of course, from the perspective that the longer the quantum key is stored, the less secure it is, the quantum key can be continuously generated and the newly generated quantum key can be used to update the previously pre-filled quantum key for the time period to shorten the storage time of the quantum key.

[0087] It is worth noting that since the maximum value can be selected when the aggregation parameter characteristic value is introduced in the early stage, the predicted data volume calculated on this basis should be relatively large, and the corresponding estimated quantum key demand is also relatively large. If it is found that some quantum keys are still left after all the data is encrypted in a certain time period, these quantum keys should be cleared when the data is encrypted in the next time period.

[0088] This embodiment controls the storage time from the perspective of quantum key update, which can effectively shorten the exposure time of the quantum key and provide the greatest protection for the security of encrypted data.

[0089] Embodiment 3: Compared with Embodiment 1, the data transmitted between the IoT device and the data transfer node can also be encrypted by quantum key based on Embodiment 1, and the technical solution provided in Embodiment 1 can be specifically expanded. This embodiment can further improve the data transmission security of IoT devices.

[0090] The above embodiments are only used to illustrate the technical method of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical method of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present application.

Claims

1. An Internet of Things data transmission system based on quantum secure communication, characterized in that: include: A cloud platform, and a number of data transfer nodes connected thereto; each of the data transfer nodes is connected to a number of IoT devices; Cloud platform: used to predict the data transmission volume of the data transfer node in each time period of a set period, and determine the key demand in the time period according to the data transmission volume; and Generate a quantum key through a quantum key distribution network, and pre-fill the quantum key required for each time period into the secure storage medium of the data transfer node; The data transfer node is used to encrypt the received data using a pre-charged quantum key and transmit the encrypted data to the cloud platform; wherein the received data is processed by an encryption algorithm.

2. According to claim 1, an Internet of Things data transmission system based on quantum secure communication is characterized in that: The predicted data transfer node data transmission volume in each time period of the set cycle includes: Extracting data transmission records of IoT devices connected to the data transfer node, and predicting the data generation amount of each IoT device in a set period according to the data transmission records; The data generation amount of the IoT device is aggregated to obtain the predicted data amount of the data transfer node in a set period; the predicted data amount is divided according to a pre-set time period to obtain the data transmission amount of each time period; wherein the time period is obtained according to the quantum key generation efficiency.

3. According to claim 2, an Internet of Things data transmission system based on quantum secure communication is characterized in that: The aggregation process comprises: According to the data aggregation record of the data transfer node, the characteristic value of each aggregation parameter is obtained; wherein the aggregation parameters include compression rate, deduplication rate, protocol overhead rate and data aggregation rate, and the characteristic value includes mean value or maximum value; An aggregation factor is calculated according to the aggregation parameter; and the aggregation factor is multiplied by the data generation amount of the IoT device to obtain the predicted data amount of the data transfer node.

4. According to claim 2, an Internet of Things data transmission system based on quantum secure communication is characterized in that: The time period is obtained by dividing according to the quantum key generation efficiency, including: Selecting a time range from the initial position of the set period, verifying the time range by the predicted data volume, and using the time range as time period one after verification; Based on the quantum key generation efficiency, the quantum key generation amount in time period one is determined, and the next time range is determined according to the quantum key generation amount as time period two; and this is carried out in sequence until the set period is divided.

5. According to claim 4, an Internet of Things data transmission system based on quantum secure communication is characterized in that: Determining a next time range according to the quantum key generation amount includes: The quantum key generation amount corresponding to time period 1 is calculated taking into account network fluctuations and marked as MSL; the upper limit of the time range corresponding to time period 1 is marked as T d ; Constructing a data prediction function based on the predicted data volume, marked as F(t); wherein the data prediction function represents a functional relationship between the predicted data volume and time within a set period; By solving the inequality Get time T u , will [T d , T u ] as the time range corresponding to time period 2.

6. The Internet of Things data transmission system based on quantum secure communication according to claim 5 is characterized in that: The step of calculating the quantum key generation amount corresponding to time period one while taking network fluctuation into consideration includes: Predicting the network fluctuation parameters of quantum channels According to the formula Calculate the quantum key generation rate R under the influence of network fluctuations; where R0 is the quantum key generation rate without the influence of network fluctuations; The quantum key generation amount in time period one is calculated according to the quantum key generation rate R.

7. The Internet of Things data transmission system based on quantum secure communication according to claim 6 is characterized in that: The predicting and obtaining of network fluctuation parameters of the quantum channel includes: Extracting several network fluctuation parameters of quantum channel history; Based on several network fluctuation parameters, the network fluctuation parameters of time period one are predicted using exponential smoothing method.

8. The Internet of Things data transmission system based on quantum secure communication according to claim 1 is characterized in that: Pre-filling the quantum key required for each time period into the secure storage medium of the data transfer node includes: A quantum key is generated through a quantum key distribution network in the current time period, and the generated quantum key is pre-filled into a secure storage medium in a timely manner for use in data encryption in the next time period.

9. The Internet of Things data transmission system based on quantum secure communication according to claim 8 is characterized in that: In the process of injecting quantum keys into a secure storage medium, when the number of pre-injected quantum keys has met the quantity requirement of the next time period; determine whether there is still time to generate a new quantum key in the current time period; if so, replace the injected quantum key with the newly generated quantum key.

10. The Internet of Things data transmission system based on quantum secure communication according to claim 1 is characterized in that: The cloud platform is connected to a number of data transfer nodes, and each of the data transfer nodes is connected to a number of IoT devices respectively; The cloud platform generates quantum keys for data transfer nodes through a quantum key distribution network.

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