Carbon Asset Information Security Synchronization Method Dependent on Internet Cloud Platform

Abstract

This application relates to the field of data processing technology, specifically to a carbon asset information security synchronization method relying on an Internet cloud platform. The method includes: constructing various carbon asset change sequences of each user based on the similarity of carbon asset information when each user updates carbon asset information twice adjacent to each other, and combining the data update frequencies of various carbon asset information to analyze the influence degree of the corresponding type information of each user; constructing the trend matching confidence of each type of carbon asset information of each user based on the similarity degree between the carbon asset change sequences of each user and those of other users; determining the synchronization priority of the carbon asset information of each user based on the influence degree of the type information and the trend matching confidence to ensure the security and efficiency of the transmission process. For the carbon asset information security synchronization method relying on an Internet cloud platform, it can achieve real-time and efficient information transmission, and solve the problems of data delay and inconsistency in the distributed management of carbon assets.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and specifically to a carbon asset information security synchronization method relying on an Internet cloud platform. Background Art

[0002] Carbon assets usually include information such as carbon emission permits and carbon offset projects. The accuracy and security of this data directly affect the fairness and transparency of the carbon market. In the carbon trading market, the price of carbon emission quotas is affected by various factors, including historical carbon trading prices, macroeconomic indicators, energy prices, and environmental conditions. Information synchronization based on the cloud platform not only improves the timeliness and accessibility of data but also brings security risks such as data leakage and tampering. Therefore, an effective information security synchronization method needs to be established to achieve the security protection of carbon asset information.

[0003] In the information security synchronization of the cloud platform for carbon asset management, it is necessary to comprehensively consider the confidentiality, integrity, and availability of data, and adopt multi-level security strategies and technical means. By reasonably designing the synchronization architecture, implementing strong encryption and authentication mechanisms, utilizing advanced blockchain technology, and following best practices, the secure synchronization of carbon asset information can be effectively guaranteed.

[0004] However, in the synchronization process of carbon asset data including various information types, the security requirements for data synchronization are different. For different enterprise users, the refined control requirements for multiple projects within some categories of information are different, and the visualization display requirements for the prediction results of carbon asset information are also different. Due to data latency and inconsistency problems in distributed carbon asset management, there is a situation where the Internet cloud platform cannot perform real-time and efficient carbon asset information security synchronization. Summary of the Invention

[0005] To solve the above technical problems, this application provides a carbon asset information security synchronization method relying on an Internet cloud platform to solve the existing problems.

[0006] The carbon asset information security synchronization method relying on an Internet cloud platform of this application adopts the following technical solutions:

[0007] An embodiment of this application provides a carbon asset information security synchronization method relying on an Internet cloud platform. The method includes the following steps:

[0008] Collect various carbon asset information synchronized by each user through the Internet cloud platform each time, and construct the carbon asset information sequence of each user;

[0009] Calculate the data update frequency of various carbon asset information for each user based on the synchronization time corresponding to each element in each carbon asset information sequence; construct the change sequences of each carbon asset for each user based on the similarity between adjacent elements in each carbon asset information sequence; construct the type vectors of each user based on all the carbon asset change sequences of each user; construct the influence degree of the type information of the type vectors of each user based on the similarity between the type vectors of different users, in combination with the data update frequency;

[0010] Based on the data point matching characteristics between the same carbon asset change sequences of each user and other users, obtain the number of matching data points of each element in each carbon asset change sequence of each user in the corresponding carbon asset change sequences of each other user; construct the trend matching confidence of each type of carbon asset information of each user based on the differences between the numbers of all the matching data points in the carbon asset change sequences;

[0011] Construct the hierarchical parameters of the adjustment synchronization level of the carbon asset information of each user based on the influence degree of the type information and the trend matching confidence; determine the synchronization priority of the carbon asset information of each user based on the hierarchical parameters.

[0012] In one embodiment, the process of obtaining the data update frequency is as follows:

[0013] For the various carbon asset information sequences of a single user, obtain the synchronization time corresponding to the carbon asset information data at each synchronization in the carbon asset information sequence, calculate the extreme values of all the synchronization times in each carbon asset information sequence, and calculate the reciprocal of the extreme values as the data update frequency of the corresponding carbon asset information.

[0014] In one embodiment, the process of obtaining the carbon asset change sequence is as follows:

[0015] In the various carbon asset information sequences of a single user, analyze the text similarity between the carbon asset information data at each synchronization and the carbon asset information data at the previous synchronization as the change degree value of the carbon asset information data at each synchronization, and record the sequence composed of all the change degree values in the carbon asset information sequence as the carbon asset change sequence.

[0016] In one embodiment, the process of obtaining the text similarity is as follows:

[0017] Perform word segmentation on the carbon asset information data at each synchronization, and record the vector composed of all the obtained word groups as the carbon asset information word segmentation vector at each synchronization; calculate the cosine similarity between the carbon asset information word segmentation vectors at each synchronization and the carbon asset information word segmentation vector at the previous synchronization as the text similarity.

[0018] In one embodiment, the type vector is: a vector composed of the last elements in all carbon asset change sequences of each user.

[0019] In one embodiment, the expression of the influence degree of the type information is:

[0020] , where represents the influence degree of the type information of the type vector of user a; represents the type vector of user a; represents the mean vector of the type vectors of all users; represents the cosine similarity function; represents the mean of the data update frequencies of all types of carbon asset information of user a; is a normalization function.

[0021] In one embodiment, the process of obtaining the number of matching data points is as follows:

[0022] For any user, the carbon asset change sequences of the same type of carbon asset information of the any user and each other user are used as the input of the matching algorithm, and the output is the pairs of mutually matching data points between the carbon asset change sequences of the same type of carbon asset information of the any user and each other user;

[0023] For any element in the carbon asset change sequences of the any user, the number of data points matched by the any element in the corresponding carbon asset change sequences of each other user is counted to obtain the number of matching data points.

[0024] In one embodiment, the process of obtaining the trend matching confidence is as follows:

[0025] Calculate the mean of the number of the matching data points of the any element in the corresponding carbon asset change sequences of all other users, denoted as the first mean; Denote the trend matching confidence of the j-th type of carbon asset information of user a as , The expression of is:

[0026] , where K is the number of elements in the j-th carbon asset change sequence of user a, represents the first mean of the k-th element in the j-th carbon asset change sequence of user a, represents the variance of the first means of all elements in the j-th carbon asset change sequence of user a, is a normalization function.

[0027] In one embodiment, the expression of the hierarchical parameter is:

[0028] , where is a hierarchical parameter representing the adjustment synchronization level of user a's carbon asset information, represents the influence degree of the type information of the type vector of user a, represents the trend matching confidence of the j-th type of carbon asset information of user a, represents the number of types of carbon asset information, is a normalization function.

[0029] In one embodiment, the process of determining the priority of carbon asset information synchronization for each user is as follows:

[0030] Preset each synchronization level, which respectively corresponds to the priority levels of each level; use a linear function to perform a synchronization level numerical mapping on the hierarchical parameters of all users to obtain the synchronization level numerical values corresponding to each user, and determine the priority of carbon asset information synchronization for each user.

[0031] This application has at least the following beneficial effects:

[0032] This application collects various carbon asset information synchronized by each user through the Internet cloud platform each time, and constructs the carbon asset information sequences of each user; constructs the carbon asset change sequences of each user based on the similarity of carbon asset information when the carbon asset information is updated twice in succession, combines the data update frequencies of various carbon asset information, and analyzes the influence degree of the corresponding type information of each user; constructs the trend matching confidence of each type of carbon asset information of each user based on the similarity degree between the carbon asset change sequences of each user and those of other users, taking into account the dynamic changes of carbon asset information, which is beneficial to the matching accuracy of synchronization priorities; constructs the hierarchical parameters of the adjustment synchronization level of the carbon asset information of each user based on the influence degree of the type information and the trend matching confidence; determines the priority of carbon asset information synchronization for each user based on the hierarchical parameters, and adopts data encryption methods and transmission channels with different security levels for different priorities to ensure the security and efficiency of the transmission process. For the carbon asset information security synchronization method relying on the Internet cloud platform, it can achieve real-time and efficient information transmission, and solve the problems of data delay and inconsistency in distributed carbon asset management. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0034] Figure 1Flowchart of the carbon asset information security synchronization method provided for this application and relying on the Internet cloud platform;

[0035] Figure 2 Schematic diagram of the acquisition process of text similarity. Detailed implementation manners

[0036] In order to further elaborate on the technical means and effects adopted by this application to achieve the intended invention purpose, the following combines the accompanying drawings and preferred embodiments to detail the specific implementation manners, structures, features and effects of the carbon asset information security synchronization method provided according to this application and relying on the Internet cloud platform. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0038] The following specifically describes the specific solution of the carbon asset information security synchronization method provided by this application and relying on the Internet cloud platform with reference to the accompanying drawings.

[0039] The carbon asset information security synchronization method provided by an embodiment of this application and relying on the Internet cloud platform.

[0040] Specifically, the following carbon asset information security synchronization method relying on the Internet cloud platform is provided. Please refer to Figure 1 , and this method includes the following steps:

[0041] Step S1, collect various carbon asset information synchronized by each user through the Internet cloud platform each time, and construct the carbon asset information sequence of each user.

[0042] Each time a user uploads carbon asset information and trades carbon assets through the Internet cloud platform, the carbon asset information involved includes actual emissions, emission sources, emission factors, quota allocation amounts, transaction records, surplus / shortage, sources of carbon credits, project verification information, market transaction prices, trading volumes, relevant policy and regulation information, emission reduction amounts, climate impact assessments, real-time monitoring and compliance reports, carbon asset value assessments, and cost-benefit analyses. Among them, the relevant policy and regulation information covers compliance requirements and policy changes and other information.

[0043] Collect various carbon asset information synchronized by each user through the Internet cloud platform each time. Among them, for each type of carbon asset information of a single user, collect the data at the N times closest to the current moment when this type of carbon asset information is synchronized as the synchronization data of each time for this type of carbon asset information; record the sequence composed of all synchronization data of various carbon asset information of a single user in ascending order of time as the data sequence of various carbon asset information of a single user, denoted as the sequence of each carbon asset information.

[0044] Preferably, in the embodiment of the present application, the value of N is set to 20. As other embodiments of the present application, the implementer can set the value of N according to the actual situation.

[0045] Step S2, calculate the data update frequency of various carbon asset information of each user based on the synchronization time corresponding to each element in the sequence of each carbon asset information; construct the change sequence of each carbon asset of each user based on the similarity between adjacent elements in the sequence of each carbon asset information; construct the type vector of each user based on all the carbon asset change sequences of each user; based on the similarity between the type vectors of different users, combine the data update frequency to construct the influence degree of the type information of the type vector of each user.

[0046] Since the Internet cloud platform of the carbon trading market involves multiple types of users, such as enterprises, investors, and environmental protection organizations, etc., the generation and circulation of data involve complex interaction and trading mechanisms. Since the Internet cloud platform stores data in the form of data types, but for the carbon resource information uploaded by different users, it often contains privacy information with different levels of information richness, resulting in a large deviation in analyzing user trading behaviors. Therefore, it is necessary to define the information synchronization range of carbon asset data, analyze user trading behaviors, and extract the refined trend change status of carbon asset data under the different user type differences. The specific steps are as follows:

[0047] 1) For the sequence of various carbon asset information of a single user, obtain the synchronization time corresponding to the carbon asset information data at each synchronization in this carbon asset information sequence, calculate the extreme values of all the synchronization times in this carbon asset information sequence, and calculate the reciprocal of the extreme values as the data update frequency of this type of carbon asset information.

[0048] 2) In the sequence of various carbon asset information of a single user, calculate the text similarity between the carbon asset information data at each synchronization and the carbon asset information data at the previous synchronization as the change degree value of the carbon asset information data at each synchronization. The specific text similarity is as follows:

[0049] In the various carbon asset information sequences of a single user, the carbon asset information data at each synchronization is segmented by the Jieba tokenizer, and the vector composed of all the obtained phrases is recorded as the carbon asset information segmentation vector at each synchronization; calculate the cosine similarity between the carbon asset information segmentation vectors at each synchronization and the carbon asset information segmentation vector at the previous synchronization as the text similarity. Among them, the cosine similarity is a well-known technology, and the specific process will not be elaborated here.

[0050] 3) For the various carbon asset information sequences of a single user, the sequence composed of all the change degree values in the carbon asset information sequence is recorded as the carbon asset change sequence, so as to obtain the respective carbon asset change sequences of a single user.

[0051] 4) For a single user, the vector composed of the last elements in all its carbon asset change sequences is recorded as the type vector of the user. Among them, the i-th element in the type vector of the user is the last change degree value in the i-th carbon asset change sequence of the user.

[0052] 5) The greater the difference between the type vectors of each user and those of other users indicates that the change of the carbon asset information of each user is more affected by the carbon resource information uploaded by itself, and it often contains privacy information with different information richness levels. The security level should be improved in the subsequent information synchronization level division. Therefore, the expression for the influence degree of the type information of the type vector of each user is:

[0053] , where represents the influence degree of the type information of the type vector of user a; represents the type vector of user a; represents the mean vector of the type vectors of all users. Since the type vectors of all users are of the same length, the mean can be directly calculated using vector operation rules; is the cosine similarity function; represents the mean of the data update frequencies of all types of carbon asset information of user a; is the normalization function.

[0054] The larger the value of

[0055] Step S3: Based on the data point matching features between the same type of carbon asset change sequences of each user and those of other users, obtain the number of matching data points of each element in each carbon asset change sequence of each user in the corresponding carbon asset change sequences of each of the other users; construct the trend matching confidence of each type of carbon asset information of each user based on the differences between the numbers of the matching data points of all elements in the carbon asset change sequences.

[0056] The degree of influence of the type information of the type vector of a user measures the differences between user data types. In the actual carbon asset market trading process, its asset data is dynamically changing. The carbon asset data changes over time and fluctuates under the influence of various factors such as market supply and demand and enterprise emission reduction measures. It is more manifested as the change in the synchronization update frequency of each type of user, specifically as the change in the arrangement structure in the carbon asset change sequences of a single user.

[0057] Since the influence of the carbon asset trading market is more of an overall trend change, the analysis of two time series implemented using the DTW (Dynamic Time Warping) algorithm can well remove the trend differences between time series caused by the trend fluctuations in the carbon asset trading market. However, its trend differences are usually limited to the similar conditions in local areas. When the changes in the time series are too drastic, its removal effect is poor.

[0058] 1) For any user, use the carbon asset change sequences of the same type of carbon asset information of the any user and those of each of the other users as the input of the DTW algorithm, and the output is the pairs of mutually matching data points between the carbon asset change sequences of the same type of carbon asset information of the any user and those of each of the other users; among them, the DTW algorithm is a well-known technology, and the specific process will not be elaborated.

[0059] For any element in each carbon asset change sequence of the any user, obtain the number of data points matched by the any element in the corresponding carbon asset change sequences of each of the other users when matched by the DTW algorithm, as the first matching number of the any element, that is, the number of matching data points.

[0060] Calculate the mean value of the first matching numbers of the any element in the corresponding carbon asset change sequences of all the other users, denoted as the first mean value of the any element.

[0061] 2) The more transactions occur and the closer the situation is, the more common the corresponding protection level is. Then, obtain the trend matching confidence of each type of carbon asset information of each user, and the expression is:

[0062] , where in the formula, represents the trend matching confidence of the j-th type of carbon asset information of user a, K is the number of elements in the j-th carbon asset change sequence of user a, The first mean value of the k-th element in the j-th carbon asset change sequence of user a The variance of the first mean values of all elements in the j-th carbon asset change sequence of user a is a normalization function.

[0063] The ratio represents the degree of change in the sensitivity of user type differences within the local interval range. The smaller its value, the higher the impact on the size of the local area in the trend matching process.

[0064] Step S4: Construct the hierarchical parameters of the adjustment and synchronization level of the carbon asset information of each user based on the influence degree of the type information and the trend matching confidence; determine the priority of the carbon asset information synchronization of each user based on the hierarchical parameters.

[0065] In order to make the extraction of user type differences by the size of the local area in the trend matching process more universal, here, using the influence degree of the type information and the trend matching confidence, obtain the priority weight, and obtain the hierarchical parameters of the adjustment and synchronization level of different types of data by weighted average. The expression is:

[0066] , where in the formula, represents the hierarchical parameter of the adjustment and synchronization level of the carbon asset information of user a represents the influence degree of the type information of the type vector of user a represents the trend matching confidence of the j-th type of carbon asset information of user a represents the number of types of carbon asset information is a normalization function.

[0067] represents the degree of significance of the type difference of the type data of this user under the overall data trend. The larger its value, the closer the trading correlation status of the type data of this user is with other users when more transactions occur, and the more common, that is, the lower, the corresponding protection level of this type of data.

[0068] Preset synchronization levels. Preferably, in the embodiments of the present application, the synchronization levels are set to four levels: 1, 2, 3, and 4. As other embodiments of the present application, the implementer can set the number of synchronization levels according to the actual situation. Among them, the synchronization level values 1, 2, 3, and 4 correspond to high priority, medium-high priority, medium priority, and low priority respectively. The smaller the synchronization level, the higher the priority. Use a linear function to map the level parameters of all users to synchronization level values, so as to obtain the synchronization level values corresponding to each user, and then obtain the priority of carbon asset information synchronization for each user. Among them, the linear function mapping method is a well-known technology, and the specific process will not be elaborated. Different security level data encryption methods and transmission channels are used for different priorities to ensure the security and efficiency of the transmission process. By reasonably classifying and synchronizing this information, enterprises can view the display information of emission reduction status in a timely manner, formulate emission reduction strategies more effectively, and optimize carbon asset management.

[0069] The schematic diagram of the acquisition process of text similarity is as Figure 2 shown.

[0070] To sum up, in the embodiments of the present application, by collecting various carbon asset information synchronized by each user through the Internet cloud platform each time, a carbon asset information sequence of each user is constructed; based on the similarity of carbon asset information when the carbon asset information is updated twice adjacent to each other, each carbon asset change sequence of each user is constructed, and combined with the data update frequency of various carbon asset information, the influence degree of the corresponding type information of each user is analyzed; based on the similarity degree between the carbon asset change sequences of each user and those of other users, the trend matching confidence of each carbon asset information of each user is constructed, taking into account the dynamic changes of carbon asset information, which is beneficial to the matching accuracy of synchronization priorities; based on the influence degree of the type information and the trend matching confidence, the level parameters for adjusting the synchronization levels of the carbon asset information of each user are constructed; based on the level parameters, the priorities of carbon asset information synchronization for each user are determined, and different security level data encryption methods and transmission channels are used for different priorities to ensure the security and efficiency of the transmission process. For the carbon asset information security synchronization method relying on the Internet cloud platform, it can achieve real-time and efficient information transmission, and solve the problems of data delay and inconsistency in distributed carbon asset management.

[0071] It should be noted that: the above sequence of the embodiments of the present application is only for description and does not represent the advantages or disadvantages of the embodiments. And the above specific embodiments of the present application have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] Each embodiment in this application is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

[0073] The above-described embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; modifying the technical solutions recorded in the foregoing embodiments, or equivalently replacing some of the technical features, does not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of each embodiment of this application, and should all be included within the protection scope of this application.

Claims

1. A carbon asset information security synchronization method relying on an Internet cloud platform, characterized in that The method includes the following steps: Collect various carbon asset information synchronized by each user through the Internet cloud platform each time, and construct the carbon asset information sequences of each user; Calculate the data update frequency of various carbon asset information of each user based on the synchronization time corresponding to each element in each carbon asset information sequence; construct the carbon asset change sequences of each user based on the similarity between adjacent elements in each carbon asset information sequence; construct the type vectors of each user based on all the carbon asset change sequences of each user; based on the similarity between the type vectors of different users, combine the data update frequency to construct the influence degree of type information of the type vectors of each user; Based on the data point matching characteristics between the same-kind carbon asset change sequences of each user and other users, obtain the number of matching data points of each element in each carbon asset change sequence of each user in the corresponding carbon asset change sequences of each other user; construct the trend matching confidence of each type of carbon asset information of each user based on the difference between the number of all the matching data points in the carbon asset change sequences; Construct the hierarchical parameters of the adjustment synchronization level of the carbon asset information of each user based on the influence degree of type information and the trend matching confidence; determine the synchronization priority of the carbon asset information of each user based on the hierarchical parameters, and use data encryption methods and transmission channels with different security levels to transmit carbon asset information with different priorities.

2. The carbon asset information security synchronization method dependent on an Internet cloud platform according to claim 1, wherein The process of obtaining the data update frequency is as follows: For the carbon asset information sequences of a single user, obtain the synchronization time corresponding to the carbon asset information data at each synchronization in the carbon asset information sequence, calculate the extreme values of all the synchronization times in each carbon asset information sequence, and calculate the reciprocal of the extreme values as the data update frequency of the corresponding carbon asset information.

3. The carbon asset information security synchronization method relying on the Internet cloud platform according to claim 1, characterized in that The process of obtaining the carbon asset change sequence is as follows: In the carbon asset information sequences of a single user, analyze the text similarity between the carbon asset information data at each synchronization and the carbon asset information data at the previous synchronization as the change degree value of the carbon asset information data at each synchronization, and record the sequence composed of all the change degree values in the carbon asset information sequence as the carbon asset change sequence.

4. The carbon asset information security synchronization method relying on the Internet cloud platform according to claim 3, wherein The process of obtaining the text similarity is as follows: Perform word segmentation on the carbon asset information data at each synchronization, and record the vector composed of all the obtained word groups as the carbon asset information word segmentation vector at each synchronization; calculate the cosine similarity between the carbon asset information word segmentation vectors at each synchronization and the carbon asset information word segmentation vector at the previous synchronization as the text similarity.

5. The carbon asset information security synchronization method relying on an Internet cloud platform according to claim 1, characterized in that The type vector is: the vector composed of the last element in all the carbon asset change sequences of each user.

6. The carbon asset information security synchronization method relying on the Internet cloud platform according to claim 1, characterized in that, The expression of the influence degree of type information is: In the formula, LY a represents the influence degree of the type information of the type vector of user a; N a represents the type vector of user a; represents the mean vector of the type vectors of all users; cos( ) represents the cosine similarity function; represents the mean of the data update frequencies of all types of carbon asset information of user a; norm( ) is the normalization function.

7. The carbon asset information security synchronization method relying on the Internet cloud platform according to claim 1, characterized in that The process of obtaining the number of matching data points is as follows: For any user, use the carbon asset change sequences of the same-kind carbon asset information of the any user and each other user as the input of the matching algorithm, and the output is each pair of mutually matching data points between the carbon asset change sequences of the same-kind carbon asset information of the any user and each other user; For any element in the carbon asset change sequences of any one of the users, count the number of data points matched by the any element in the corresponding carbon asset change sequences of each of the other users to obtain the number of matched data points.

8. The carbon asset information security synchronization method dependent on the Internet cloud platform according to claim 7, characterized in that, The process of obtaining the trend matching confidence level is as follows: Calculate the mean value of the number of the matching data points of any of the elements in the carbon asset change sequences corresponding to all other users, and denote it as the first mean value; denote the trend matching confidence of the j-th type of carbon asset information of user a as PZ a,j , PZ a,j The expression of is: Where K is the number of elements in the j-th carbon asset change sequence of user a, and l a,j,k represents the first mean of the k-th element in the j-th carbon asset change sequence of user a, and σ(l a,j ) represents the variance of the first means of all elements in the j-th carbon asset change sequence of user a, and norm( ) is a normalization function.

9. The carbon asset information security synchronization method relying on an Internet cloud platform according to claim 1, characterized in that The expression of the hierarchical parameter is: where ρ a represents the hierarchical parameter of the adjustment synchronization level of the carbon asset information of user a, LY a represents the influence degree of the type information of the type vector of user a, PZ a,j represents the trend matching confidence of the j-th type of carbon asset information of user a, J represents the number of types of carbon asset information, and norm( ) is the normalization function.

10. The carbon asset information security synchronization method relying on an Internet cloud platform according to claim 1, characterized in that The process of determining the priority of carbon asset information synchronization for each user is as follows: Preset each synchronization level, which respectively corresponds to priorities at each level; use a linear function to perform a synchronization level numerical mapping on the hierarchical parameters of all users to obtain the synchronization level numerical values corresponding to each user, and determine the priority of carbon asset information synchronization for each user.

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