Carbon asset information security synchronization method depending on Internet cloud platform

Abstract

The invention relates to the technical field of data processing, in particular to a carbon asset information security synchronization method depending on an internet cloud platform, and the method comprises the steps: constructing each carbon asset change sequence of each user based on the similar condition of the carbon asset information of each user during two adjacent carbon asset information updating, in combination with the data updating frequency of various kinds of carbon asset information, analyzing the type information influence degree corresponding to each user; constructing the trend matching confidence of each kind of carbon asset information of each user based on the similarity between the carbon asset change sequences of each user and other users; and determining the synchronization priority of the carbon asset information of each user based on the type information influence degree and the trend matching confidence so as to ensure the security and high efficiency of the transmission process, and realizing real-time and high-efficiency information transmission for the security synchronization method of the carbon asset information depending on the Internet cloud platform. The problems of data delay and inconsistency in carbon asset distributed management are solved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to a method for secure synchronization of carbon asset information that relies 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 these 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 many factors, including historical carbon trading prices, macroeconomic indicators, energy prices, and environmental conditions. Information synchronization based on cloud platforms not only improves the real-time and accessibility of data, but also brings security risks such as data leakage and tampering. Therefore, it is necessary to establish an effective information security synchronization method to achieve the security protection of carbon asset information.

[0003] In the cloud platform information security synchronization of 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 identity authentication mechanisms, using advanced blockchain technology and following best practices, the secure synchronization of carbon asset information can be effectively guaranteed.

[0004] However, carbon asset data includes synchronization processes for multiple information types, and the synchronization security requirements for the data are different. For different corporate users, the requirements for refined control of multiple projects within some categories of information are different, and the requirements for the visualization of carbon asset information prediction results are also different. Due to data delays and inconsistencies in the distributed management of carbon assets, the Internet cloud platform is unable to perform real-time and efficient carbon asset information security synchronization. Summary of the invention

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

[0006] The carbon asset information security synchronization method of this application that relies on the Internet cloud platform adopts the following technical solutions: An embodiment of the present application provides a carbon asset information security synchronization method relying on an Internet cloud platform, the method comprising the following steps: Collect various carbon asset information synchronized by each user through the Internet cloud platform each time, and build each user's carbon asset information sequence; 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 each carbon asset change sequence of each user based on the similarity between adjacent elements in each carbon asset information sequence; construct each user's type vector based on all carbon asset change sequences of each user; construct the type information influence degree of each user's type vector based on the similarity between type vectors of different users and the data update frequency; Based on the data point matching characteristics between each user and the same carbon asset change sequence of other users, the number of matching data points of each element in each carbon asset change sequence of each user in the corresponding carbon asset change sequence of each other user is obtained; based on the difference between the number of matching data points of all elements in the carbon asset change sequence, the trend matching confidence of each carbon asset information of each user is constructed; Based on the influence degree of the type information and the trend matching confidence, a hierarchical parameter for adjusting the synchronization level of each user's carbon asset information is constructed; and based on the hierarchical parameter, a priority for synchronization of each user's carbon asset information is determined.

[0007] In one embodiment, the process of obtaining the data update frequency is as follows: For various carbon asset information sequences of a single user, the synchronization time corresponding to the carbon asset information data at each synchronization in the carbon asset information sequence is obtained, the extreme values ​​of all the synchronization times in each carbon asset information sequence are calculated, and the reciprocal of the extreme value is calculated as the data update frequency of the corresponding carbon asset information.

[0008] In one embodiment, the process of obtaining the carbon asset change sequence is as follows: In various carbon asset information sequences of a single user, the text similarity between the carbon asset information data at each synchronization and the carbon asset information data at the previous synchronization is analyzed as the change degree value of the carbon asset information data at each synchronization, and the sequence composed of all the change degree values ​​in the carbon asset information sequence is recorded as the carbon asset change sequence.

[0009] In one embodiment, the process of obtaining the text similarity is as follows: The carbon asset information data at each synchronization is segmented, and the vector composed of all the obtained phrases is recorded as the carbon asset information segmentation vector at each synchronization; the cosine similarity between the carbon asset information segmentation vector at each synchronization and the carbon asset information segmentation vector at the previous synchronization is calculated as the text similarity.

[0010] In one embodiment, the type vector is: a vector consisting of the last element in all carbon asset change sequences of each user.

[0011] In one embodiment, the expression of the influence degree of the type information is: , where Indicates the influence degree of type information of user a’s type vector; 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 average data update frequency of all carbon asset information of user a; is the normalization function.

[0012] In one embodiment, the process of obtaining the number of matching data points is as follows: For any user, the carbon asset change sequence of the same carbon asset information of the any user and each other user is used as the input of the matching algorithm, and the output is each pair of mutually matching data points between the carbon asset change sequence of the same carbon asset information of the any user and each other user; For any element in each carbon asset change sequence of any user, the number of data points matched by the element in the corresponding carbon asset change sequence of each other user is counted to obtain the number of matched data points.

[0013] In one embodiment, the process of obtaining the trend matching confidence is as follows: Calculate the mean of the number of matching data points of any element in the carbon asset change sequence corresponding to all other users, and record it as the first mean; record the trend matching confidence of the j-th carbon asset information of user a as , The expression is: , where K is the number of elements in the j-th carbon asset change sequence of user a, represents the first mean of the kth element in the jth carbon asset change sequence of user a, represents the variance of the first mean of all elements in the j-th carbon asset change sequence of user a, is the normalization function.

[0014] In one embodiment, the expression of the level parameter is: , where The level parameter representing the adjustment synchronization level of user a’s carbon asset information, Indicates the influence degree of type information of user a’s type vector, represents the trend matching confidence of the j-th carbon asset information of user a, Indicates the number of types of carbon asset information, is the normalization function.

[0015] In one embodiment, the process of determining the priority of synchronization of carbon asset information of each user is as follows: Each synchronization level is preset to correspond to the priority of each level; the level parameters of all users are mapped to the synchronization level values ​​using a linear function to obtain the synchronization level value corresponding to each user, and determine the priority of each user's carbon asset information synchronization.

[0016] This application has at least the following beneficial effects: The present application constructs each user's carbon asset information sequence by collecting various carbon asset information synchronized by each user through the Internet cloud platform each time; constructs each user's carbon asset change sequence based on the similarity of carbon asset information when two adjacent carbon asset information are updated, and analyzes the influence of the corresponding type information of each user in combination with the data update frequency of various carbon asset information; constructs the trend matching confidence of each carbon asset information of each user based on the similarity between the carbon asset change sequence of each user and other users, taking into account the dynamic changes of carbon asset information, which is beneficial to the matching accuracy of synchronization priority; constructs the hierarchical parameters of the adjustment synchronization level of each user's carbon asset information based on the influence degree of the type information and the trend matching confidence; determines the priority of carbon asset information synchronization of 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 that relies on the Internet cloud platform, it can realize real-time and efficient information transmission, and solve the data delay and inconsistency problems in the distributed management of carbon assets. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are 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 creative work.

[0018] Figure 1 A flow chart of a carbon asset information security synchronization method relying on an Internet cloud platform provided for this application; Figure 2 Schematic diagram of the process of obtaining text similarity. DETAILED DESCRIPTION

[0019] In order to further explain the technical means and effects adopted by this application to achieve the predetermined invention purpose, the specific implementation method, structure, features and effects of the carbon asset information security synchronization method relying on the Internet cloud platform proposed by this application are described in detail below in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0020] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0021] The specific scheme of the carbon asset information security synchronization method relying on the Internet cloud platform provided by this application is described in detail below with reference to the accompanying drawings.

[0022] An embodiment of the present application provides a method for secure synchronization of carbon asset information that relies on an Internet cloud platform.

[0023] Specifically, the following carbon asset information security synchronization method relying on the Internet cloud platform is provided, please refer to Figure 1 , the method comprises the following steps: Step S1, collect various carbon asset information of each user synchronized through the Internet cloud platform each time, and construct each carbon asset information sequence of each user.

[0024] 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 allocations, transaction records, surpluses and shortages, sources of carbon credits, project verification information, market transaction prices, transaction volumes, relevant policy and regulatory information, emission reductions, climate impact assessments, real-time monitoring and compliance reports, carbon asset value assessments, and cost-benefit analysis. Among them, relevant policy and regulatory information covers compliance requirements and policy changes.

[0025] Collect various carbon asset information synchronized by each user through the Internet cloud platform each time. For each type of carbon asset information of a single user, collect the data of the N most recent synchronizations of this type of carbon asset information from the current moment as the synchronization data of 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 time order as the data sequence of various carbon asset information of a single user, and record it as each carbon asset information sequence.

[0026] 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.

[0027] Step S2, based on the synchronization time corresponding to each element in each carbon asset information sequence, calculates the data update frequency of various carbon asset information of each user; based on the similarity between adjacent elements in each carbon asset information sequence, constructs each carbon asset change sequence of each user; based on all carbon asset change sequences of each user, constructs the type vector of each user; based on the similarity between type vectors of different users, combined with the data update frequency, constructs the type information influence degree of the type vector of each user.

[0028] Since the Internet cloud platform of the carbon trading market involves multiple types of users, such as enterprises, investors and environmental protection organizations, the generation and circulation of data involve complex interaction and transaction mechanisms. Since the Internet cloud platform stores data based on data types, the carbon resource information uploaded by different users often contains privacy information with different information richness, resulting in large deviations when analyzing user trading behaviors. Therefore, it is necessary to define the scope of information synchronization for carbon asset data, analyze user trading behaviors, and extract the refined trend change status of carbon asset data under different user type differences. The specific steps are as follows: 1) For 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 value of all the synchronization times in the carbon asset information sequence, and calculate the reciprocal of the extreme value as the data update frequency of the carbon asset information.

[0029] 2) In various carbon asset information sequences of a single user, the text similarity between the carbon asset information data at each synchronization and the carbon asset information data at the previous synchronization is calculated as the change degree value of the carbon asset information data at each synchronization. The text similarity is specifically: In various carbon asset information sequences of a single user, the carbon asset information data at each synchronization is segmented through the Jieba word segmenter, and the vectors composed of all phrases obtained are recorded as the carbon asset information segmentation vectors at each synchronization; the cosine similarity between the carbon asset information segmentation vectors at each synchronization and the carbon asset information segmentation vectors at the previous synchronization is calculated as the text similarity. Among them, cosine similarity is a well-known technology, and the specific process is not repeated here.

[0030] 3) For various carbon asset information sequences of a single user, a sequence consisting of all the change degree values ​​in the carbon asset information sequence is recorded as a carbon asset change sequence, thereby obtaining various carbon asset change sequences of a single user.

[0031] 4) For a single user, the vector composed of the last element in all the carbon asset change sequences is recorded as the type vector of the user, wherein 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.

[0032] 5) The greater the difference between the type vectors of each user and other users, the greater the impact of the carbon asset information changes of each user on the carbon resource information uploaded by the user. This information often contains privacy information with different information richness. The security level should be improved in the subsequent information synchronization hierarchical division. Therefore, the expression of the type information influence degree of each user's type vector is: , where Indicates the influence degree of type information of user a’s type vector; Represents the type vector of user a; The mean vector of the type vectors of all users. Since the type vectors of all users are of equal length, the mean can be directly calculated using vector operation rules. is the cosine similarity function; Represents the average data update frequency of all carbon asset information of user a; is the normalization function.

[0033] The larger the value is, the more obvious the effect of the change in the trend of various carbon asset information data caused by the difference in user types is, and the greater the possibility that the change in carbon asset data is due to the overall difference in carbon asset information caused by the change in user types.

[0034] Step S3, based on the data point matching features between each user and the same carbon asset change sequences 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 sequence of each other user; and construct the trend matching confidence of each carbon asset information of each user based on the difference between the number of matching data points of all elements in the carbon asset change sequence.

[0035] The influence of the type information of the user's type vector measures the difference between the types of user data. In the actual market transaction process of carbon assets, the asset data is dynamically changing. The carbon asset data will change over time and fluctuate under the influence of various factors such as market supply and demand, corporate emission reduction measures, etc. It is more manifested in the change of the synchronous update frequency of various types of users, specifically in the change of the arrangement structure in the carbon asset change sequence of a single user.

[0036] Since the impact of the carbon asset trading market is more of an overall trend change, the analysis of two time series using the DTW dynamic time warping algorithm can effectively remove the trend differences between time series caused by the trend fluctuations in the carbon asset trading market. However, the trend differences are usually limited to similar conditions in local areas. When the changes in the time series are too drastic, the removal effect is poor.

[0037] 1) For any user, the carbon asset change sequence of the same carbon asset information of the any user and each other user is used as the input of the DTW algorithm, and the output is each pair of mutually matching data points between the carbon asset change sequence of the same carbon asset information of the any user and each other user; wherein the DTW algorithm is a well-known technology, and the specific process is not repeated here.

[0038] For any element in each carbon asset change sequence of any user, obtain the number of data points matched by the element in the corresponding carbon asset change sequence of each other user through the DTW algorithm, as the first matching number of the element, that is, the number of matching data points; The average of the first matching quantities of any one element in the carbon asset change sequences corresponding to all other users is calculated, and recorded as the first average of any one element.

[0039] 2) The more transactions there are and the closer the data is, the more universal the corresponding protection level is. The trend matching confidence of each carbon asset information of each user is obtained, and the expression is: , where represents the trend matching confidence of the j-th carbon asset information of user a, K is the number of elements in the j-th carbon asset change sequence of user a, represents the first mean of the kth element in the jth carbon asset change sequence of user a, represents the variance of the first mean of all elements in the j-th carbon asset change sequence of user a, is the normalization function.

[0040] The ratio indicates the degree of change in the sensitivity of user type differences within a local interval. The smaller the value, the greater its influence on the size of the local area in the trend matching process.

[0041] Step S4, constructing hierarchical parameters for adjusting the synchronization level of each user's carbon asset information based on the influence degree of the type information and the trend matching confidence; and determining the priority of synchronization of each user's carbon asset information based on the hierarchical parameters.

[0042] In order to make the extraction of user type differences based on the size of the local area in the trend matching process more universal, the influence of the type information and the trend matching confidence are used to obtain the priority weight, and the weighted average is used to obtain the level parameters of the adjustment synchronization level of different types of data. The expression is: , where The level parameter representing the adjustment synchronization level of user a’s carbon asset information, Indicates the influence degree of type information of user a’s type vector, represents the trend matching confidence of the j-th carbon asset information of user a, Indicates the number of types of carbon asset information, is the normalization function.

[0043] It indicates the significance of the type difference of the user's type data under the overall data trend. The larger the value, the closer the transaction relationship between the user's type data and other users is when more transactions occur. The corresponding protection level of this type of data is more common, that is, lower.

[0044] The synchronization level is preset. Preferably, in the embodiment of the present application, the synchronization level is set to 1, 2, 3 and 4, a total of four levels. 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. The said level parameters of all users are mapped to the synchronization level values ​​by linear functions, so as to obtain the synchronization level values ​​corresponding to each user, and then obtain the priority of carbon asset information synchronization of each user. Among them, the linear function mapping method is a well-known technology, and the specific process will not be repeated. Different security levels of 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 timely view the display information of emission reduction status, formulate emission reduction strategies more effectively, and optimize carbon asset management.

[0045] The schematic diagram of the process of obtaining text similarity is as follows: Figure 2 shown.

[0046] In summary, the embodiment of the present application constructs each user's carbon asset information sequence by collecting various carbon asset information synchronized by each user through the Internet cloud platform each time; constructs each user's carbon asset change sequence based on the similarity of carbon asset information when two adjacent carbon asset information are updated, and analyzes the corresponding type information influence of each user in combination with the data update frequency of various carbon asset information; constructs the trend matching confidence of each carbon asset information of each user based on the similarity between the carbon asset change sequence of each user and other users, taking into account the dynamic changes of carbon asset information, which is beneficial to the matching accuracy of synchronization priority; constructs the hierarchical parameters of the adjustment synchronization level of each user's carbon asset information based on the type information influence level and the trend matching confidence; determines the priority of carbon asset information synchronization of 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 that relies on the Internet cloud platform, it can realize real-time and efficient information transmission, and solve the data delay and inconsistency problems in the distributed management of carbon assets.

[0047] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. The above-mentioned specific embodiments of the present application are described. In addition, the processes depicted in the accompanying 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.

[0048] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0049] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Modifications to the technical solutions recorded in the aforementioned embodiments, or equivalent replacement of some of the technical features therein, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A carbon asset information security synchronization method based on an Internet cloud platform, characterized in that: The method comprises the following steps: Collect various carbon asset information synchronized by each user through the Internet cloud platform each time, and build each user's carbon asset information sequence; 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 each carbon asset change sequence of each user based on the similarity between adjacent elements in each carbon asset information sequence; construct each user's type vector based on all carbon asset change sequences of each user; construct the type information influence degree of each user's type vector based on the similarity between type vectors of different users and the data update frequency; Based on the data point matching characteristics between each user and the same carbon asset change sequence of other users, the number of matching data points of each element in each carbon asset change sequence of each user in the corresponding carbon asset change sequence of each other user is obtained; based on the difference between the number of matching data points of all elements in the carbon asset change sequence, the trend matching confidence of each carbon asset information of each user is constructed; Based on the influence degree of the type information and the trend matching confidence, a hierarchical parameter for adjusting the synchronization level of each user's carbon asset information is constructed; and based on the hierarchical parameter, a priority for synchronization of each user's carbon asset information is determined.

2. The carbon asset information security synchronization method relying on the Internet cloud platform as claimed in claim 1 is characterized in that: The process of obtaining the data update frequency is as follows: For various carbon asset information sequences of a single user, the synchronization time corresponding to the carbon asset information data at each synchronization in the carbon asset information sequence is obtained, the extreme values ​​of all the synchronization times in each carbon asset information sequence are calculated, and the reciprocal of the extreme value is calculated 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 as claimed in claim 1, characterized in that: The process of obtaining the carbon asset change sequence is as follows: In various carbon asset information sequences of a single user, the text similarity between the carbon asset information data at each synchronization and the carbon asset information data at the previous synchronization is analyzed as the change degree value of the carbon asset information data at each synchronization, and the sequence composed of all the change degree values ​​in the carbon asset information sequence is recorded as the carbon asset change sequence.

4. The carbon asset information security synchronization method relying on the Internet cloud platform as claimed in claim 3 is characterized in that: The process of obtaining the text similarity is as follows: The carbon asset information data at each synchronization is segmented, and the vector composed of all the obtained phrases is recorded as the carbon asset information segmentation vector at each synchronization; the cosine similarity between the carbon asset information segmentation vector at each synchronization and the carbon asset information segmentation vector at the previous synchronization is calculated as the text similarity.

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

6. The carbon asset information security synchronization method relying on the Internet cloud platform as claimed in claim 1, characterized in that: The expression of the influence degree of the type information is: , where Indicates the influence degree of type information of user a’s type vector; 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 average data update frequency of all carbon asset information of user a; is the normalization function.

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

8. The carbon asset information security synchronization method relying on the Internet cloud platform as claimed in claim 7, characterized in that: The process of obtaining the trend matching confidence is as follows: Calculate the mean of the number of matching data points of any element in the carbon asset change sequence corresponding to all other users, and record it as the first mean; record the trend matching confidence of the j-th carbon asset information of user a as , The expression is: , where K is the number of elements in the j-th carbon asset change sequence of user a, represents the first mean of the kth element in the jth carbon asset change sequence of user a, represents the variance of the first mean of all elements in the j-th carbon asset change sequence of user a, is the normalization function.

9. The carbon asset information security synchronization method relying on the Internet cloud platform as claimed in claim 1, characterized in that: The expression of the level parameter is: , where The level parameter representing the adjustment synchronization level of user a’s carbon asset information, Indicates the influence degree of type information of user a’s type vector, represents the trend matching confidence of the j-th carbon asset information of user a, Indicates the number of types of carbon asset information, is the normalization function.

10. The carbon asset information security synchronization method based on the Internet cloud platform according to claim 1, characterized in that: The process of determining the priority of each user's carbon asset information synchronization is as follows: Each synchronization level is preset to correspond to the priority of each level; the level parameters of all users are mapped to the synchronization level values ​​using a linear function to obtain the synchronization level value corresponding to each user, and determine the priority of each user's carbon asset information synchronization.

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