A method and system for secure transmission of information platform data based on the Internet

Abstract

The present invention relates to the technical field of information transmission, and provides a method for secure transmission of information platform data based on the Internet, comprising: obtaining platform data for preprocessing to obtain character data; determining a coding table based on the character data; compressing and transmitting current data according to the coding table; wherein determining the coding table based on the character data comprises: dividing each day into multiple time stages based on all historical character data based on a time series for multiple days; obtaining the actual frequency, distribution density tendency and security performance of each character data in each time stage based on analysis of all current character data; determining the coding priority of each character data in each time stage according to the actual frequency, trend performance and security performance of each character data in each time stage, and forming the coding table. The method can construct a dynamic coding table, which improves transmission while also ensuring its security. The present invention also provides a system for secure transmission of information platform data based on the Internet.

Description

Technical Field

[0001] The present invention relates to the technical field of information transmission, and in particular to a method and system for securely transmitting data on an Internet-based information platform. Background Art

[0002] In today's digital and Internet-popularized context, with the rapid growth in the number of Internet users, especially the popularity of mobile Internet, security and transmission efficiency are two core challenges and important directions for technological development. With the widespread application of the Internet and the explosive growth of data volume, how to improve transmission efficiency while ensuring data security has become an important issue in the industry.

[0003] For the secure transmission of data within the Internet information platform, the traditional method can generally use Huffman coding to compress the data before transmission, so as to improve the efficiency of its data transmission. However, in the actual operation of the Internet information platform, people's interaction with information data varies at different stages (for example, after work, there may be stronger information interaction, while during lunch break or sleep at night, people may have relatively weak information interaction). In this way, the traditional Huffman coding determines the length of the code based on the frequency of character occurrence and the coding table is fixed. In this way, there is a lack of dynamic adjustment of the coding table, and it is impossible to match the appropriate character coding length at different stages. In addition, the coding table is statically established based on the character frequency, which makes the coding lack complexity, low security, and easy to be cracked. Summary of the invention

[0004] In order to solve the technical problems of lack of coding complexity, low security and easy cracking, the purpose of the present invention is to provide a method and system for secure data transmission on an Internet-based information platform. The technical solutions adopted are as follows:

[0005] A method for secure transmission of information platform data based on the Internet, comprising:

[0006] Acquire platform data and perform preprocessing to obtain character data, wherein the platform data includes historical data and current data for multiple days, and the character data includes all historical character data based on time series for multiple days and all current character data;

[0007] Determine a coding table based on the character data;

[0008] Compressing and transmitting the current data according to the coding table;

[0009] Wherein, determining the encoding table based on the character data includes:

[0010] All the historical character data based on the time series of the plurality of days are divided into a plurality of time periods per day;

[0011] Based on the analysis of all the current character data, the actual frequency, distribution density tendency and safety performance of each character data in each time period are obtained;

[0012] The coding priority of each character data in each time stage is determined according to the actual frequency, trend performance and security performance of each character data in each time stage to form the coding table.

[0013] Preferably, all the historical character data based on the time series of the multiple days are divided into multiple time stages each day, including:

[0014] Acquire the amount of character data and the amount of character data types at each time of each day based on all the historical character data based on the time series of the plurality of days;

[0015] The complexity of character data at each time of each day is obtained based on the amount of character data and the amount of character data types at each time of each day;

[0016] Determine each minimum point according to the complexity of character data at each time of the day and calculate the time overlap of each minimum point;

[0017] The time stage dividing points are determined according to the time coincidence of each minimum point, and each day is divided into multiple time stages based on the time stage dividing points.

[0018] Preferably, the calculation formula for the character data complexity at each time of each day is:

[0019]

[0020] in, represents the character data complexity of the j-th minute of the i-th day, represents the amount of character data in the jth minute of the i-th day, Indicates the number of character data types in the jth minute of the i-th day, Represents the normalization function.

[0021] Preferably, the calculation formula for the time overlap of each minimum point is:

[0022]

[0023] in, represents the time overlap of the zth minimum point, n represents the number of days, represents the character data complexity of the zth minimum point on the i-th day, It represents the time difference between the z-th minimum point and the minimum point with the same serial number on the adjacent day.

[0024] Preferably, the distribution density tendency of each character data in each time period is obtained based on the analysis of all the current character data, including:

[0025] Numbering all character data in each time period and obtaining a number set of different character data;

[0026] The distribution density tendency of each character data is obtained according to the serial number set of the different character data.

[0027] Preferably, the calculation formula for the distribution density tendency of each character data is:

[0028]

[0029] in, Indicates the distribution density tendency of the sth character data; represents the average number difference of adjacent data in the number set corresponding to the current s-th character data; G represents the amount of data in the encoding set corresponding to the current s-th character data; Indicates the difference between the g-th data and the adjacent data in the number set corresponding to the current s-th character data; Indicates the difference between the number of the g+1th data and the adjacent data in the number set corresponding to the current sth character data; Represents the normalization function.

[0030] Preferably, the security performance of each character data in each time period is obtained based on the analysis of all the current character data, including:

[0031] Among all the current character data, for each character data, U / 2 character data are selected on the left and right of the character data according to its time sequence to obtain U character comparison data; wherein U is a preset value;

[0032] The security performance of each character data is obtained by analyzing the actual frequency of each character data and its corresponding character comparison data.

[0033] Preferably, the calculation formula for the security expression degree of each character data is:

[0034]

[0035] in, represents the security performance of the s-th character data; U represents the amount of character comparison data determined based on the s-th character data; Indicates the actual frequency of the sth character data; Indicates the actual frequency of the u-th character comparison data of the s-th character data; Represents the normalization function.

[0036] Preferably, the calculation formula for the encoding priority of each character data is:

[0037]

[0038] in, Indicates the encoding priority of the sth character data; Indicates the actual frequency of the sth character data in the current time period; Indicates the distribution density tendency of the sth character data; Indicates the security level of the s-th character data.

[0039] An Internet-based information platform data security transmission system, comprising:

[0040] A data acquisition module, used to acquire platform data and perform preprocessing to obtain character data, wherein the platform data includes historical data and current data for multiple days, and the character data includes all historical character data based on time series for multiple days and all current character data;

[0041] A coding table determination module, used for determining a coding table based on the character data;

[0042] A compression transmission module, used for compressing and transmitting the current data according to the coding table;

[0043] Wherein, the coding table determination module includes:

[0044] A time stage division unit, used for dividing each day into a plurality of time stages based on all the historical character data based on the time series of the plurality of days;

[0045] A data analysis unit, configured to obtain the actual frequency, distribution density tendency and safety performance of each character data in each time period based on the analysis of all current character data;

[0046] The coding table determination unit is used to determine the coding priority of each character data in each time stage according to the actual frequency, trend performance and security performance of each character data in each time stage to form the coding table.

[0047] The present invention has the following beneficial effects: the Internet-based information platform data security transmission method and system proposed by the present invention divides different time stages by analyzing historical data, and comprehensively adjusts the actual frequency of character data based on the consideration of data distribution performance and security in each time stage, thereby constructing a dynamic coding table to improve transmission while also ensuring its security.

[0048] This method can avoid the security problems brought by the traditional fixed coding table and the adaptation problems of the corresponding coding of the staged character data. The complexity of the coding is improved by means of a dynamic coding table to ensure security. In each dynamic coding table, the coding length of each character data is determined based on the actual data performance in the current time stage, so that the transmission efficiency of the data can be improved after compression while also ensuring its security. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 A schematic diagram of a flow chart of a method for securely transmitting data on an Internet-based information platform provided in Embodiment 1 of the present invention;

[0051] Figure 2 A schematic diagram of a sub-flow of step S2 in the Internet-based information platform data security transmission method provided in the first embodiment of the present invention;

[0052] Figure 3 A schematic diagram of a sub-flow of step S21 in the Internet-based information platform data security transmission method provided in the first embodiment of the present invention;

[0053] Figure 4 This is a module diagram of the Internet-based information platform data security transmission system provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0054] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a data security transmission method and system for an Internet-based information platform proposed by the present invention 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.

[0055] 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 invention belongs.

[0056] The specific scheme of a method and system for secure transmission of data on an Internet-based information platform provided by the present invention is described in detail below in conjunction with the accompanying drawings.

[0057] Embodiment 1

[0058] See also Figure 1 , which shows a method flow chart of a method for securely transmitting data on an Internet-based information platform provided by an embodiment of the present invention, including:

[0059] Step S1, obtaining platform data and performing preprocessing to obtain character data, wherein the platform data includes historical data and current data for multiple days, and the character data includes all historical character data based on time series for multiple days and all current character data;

[0060] Step S2, determining a coding table based on the character data;

[0061] Step S3, compressing and transmitting the current data according to the coding table.

[0062] Among them, Figure 2 As shown, step S2 includes:

[0063] Step S21, dividing each day into a plurality of time stages based on all the historical character data based on the time series of the plurality of days;

[0064] Step S22, based on the analysis of all the current character data, obtain the actual frequency, distribution density tendency and safety performance of each character data in each time period;

[0065] Step S23, determining the coding priority of each character data in each time period according to the actual frequency, trend performance and security performance of each character data in each time period, and forming the coding table.

[0066] The Internet-based information platform data security transmission method proposed in the present invention divides different time stages through historical data analysis, and comprehensively adjusts the actual frequency of character data based on considerations of data distribution performance and security in each time stage, so as to construct a dynamic coding table, thereby improving transmission while also ensuring its security.

[0067] This method can avoid the security problems brought by the traditional fixed coding table and the adaptation problems of the corresponding coding of the staged character data. The complexity of the coding is improved by means of a dynamic coding table to ensure security. In each dynamic coding table, the coding length of each character data is determined based on the actual data performance in the current time stage, so that the transmission efficiency of the data can be improved after compression while also ensuring its security.

[0068] The main purpose of the present invention is to divide the data into different time stages through the historical data of the Internet information platform, and determine the dynamic coding table based on the current time stages, compress the data to improve the transmission efficiency while ensuring its security.

[0069] The specific scenario targeted by the present invention is: in response to the multiple problems caused by static coding tables when traditional Huffman coding is used to process Internet information platform data, this method determines multiple dynamic coding tables by dividing different time stages, so that the data can be compressed while increasing the complexity of the coding, thereby improving the efficiency of data transmission while also ensuring a certain degree of security.

[0070] The following is a detailed description of each step:

[0071] In step S1, the platform data obtained is based on the Internet information platform data, the multi-day historical data can be a week (i.e., seven days) of data, and all the multi-day time-series historical character data is all the character data of each minute in time sequence. Specifically, this step is to obtain the time-series historical character data within the last week (i.e., seven days) based on the Internet information platform, and to obtain the current character data in real time, so as to facilitate subsequent processing.

[0072] In step S2, it can be understood that the current Internet information platform will present different amounts of information data in different time stages due to people's work, rest, and the emergence of hot events and topics in daily use. In this way, different time stages can be divided based on the amount of information data in historical data, so that different coding tables can be constructed for different time stages. At the same time, for the data in each time stage, we can adjust it based on the actual frequency of occurrence of its character data. For high-frequency data, its data information volume is large, and in order to ensure its data transmission performance, it should focus more on its data transmission rate; and for low-frequency data, the data transmission volume is small, so it can focus more on its data transmission security. Therefore, corrections are made based on the actual character frequency, and based on the above, we determine the corresponding coding tables for different time stages in real time.

[0073] Therefore, if Figure 2 As shown in , step S2 includes steps S21, S22 and S23.

[0074] In step S21, it can be understood that in the actual operation of the Internet information platform, different Internet information platform usage performances will be presented at different time stages according to the user's work, rest and other living habits, so the corresponding data information volume performances are different. Therefore, we divide different time stages by the performance of the data information volume presented by the recent Internet information platform, which serves as a reference for the current division of different time stages.

[0075] Preferably, if Figure 3 As shown, the step S21 includes:

[0076] Step S211, obtaining the amount of character data and the amount of character data types at each time of each day based on all the historical character data based on the time series of the plurality of days;

[0077] Step S212, obtaining the complexity of the character data at each time of each day based on the amount of character data and the amount of character data types at each time of each day;

[0078] Step S213, determining each minimum point according to the complexity of the character data at each time of each day and calculating the time coincidence of each minimum point;

[0079] Step S214, determining the time stage dividing point according to the time overlap of each minimum point, and dividing each day into multiple time stages based on the time stage dividing point.

[0080] In step S211, that is, firstly, the amount of character data contained in the information data every minute (in units of every minute) of every day in the recent week is counted, and recorded as , that is, the amount of character data in the jth minute of the i-th day in the most recent week. is the amount of character data obtained in the jth minute of the ith day in the most recent week. The data repetition is not considered. Even if the same character data appears multiple times, it is counted according to its actual number of occurrences. Therefore, here, we can analyze the number of character data types that exist every minute of every day in the most recent week, and count the number of non-repeated character data that exist every minute of every day in the most recent week, recorded as , that is, the number of character data types in the jth minute of the i-th day in the most recent week.

[0081] In step S212, through the analysis of the above two data performances, we can determine the complexity of character data per minute every day in the past week. This refers to analyzing the amount of character data per unit time from a minute-by-minute basis. This is not only related to the amount of character data but also to the number of types of character data. The larger the amount of character data per minute and the more types of character data per minute, it means that a higher amount of data information is presented on the Internet information platform based on the user's usage performance per minute.

[0082] Preferably, the calculation formula for the character data complexity at each time of each day is:

[0083]

[0084] in, represents the character data complexity of the j-th minute of the i-th day, represents the amount of character data in the jth minute of the i-th day, Indicates the number of character data types in the jth minute of the i-th day, Represents the normalization function.

[0085] In step S213, because our ultimate goal is to determine different time stages, we can first mark the minimum points of the data for the character data complexity of each minute of each day in the past week (the minimum value usually corresponds to the end of the previous stage and the beginning of the next stage), so as to analyze the time difference between each minimum point based on adjacent days. The smaller the time difference, the more likely the extreme point is to correspond to the dividing point of different time stages. Therefore, based on the character data complexity of each minute of each day in the past week, we determine each minimum point by traversing, mark it, and traverse the time corresponding to each minimum point (also in minutes).

[0086] Preferably, the calculation formula for the time overlap of each minimum point is:

[0087]

[0088] in, represents the time overlap of the zth minimum point, n represents the number of days, represents the character data complexity of the zth minimum point on the i-th day, Indicates the time difference between the zth minimum point and the minimum point of the same serial number on the adjacent day. +1 is to avoid the denominator being 0.

[0089] Overall, we determine the time overlap of each minimum point by analyzing the time difference between the minimum point with the same serial number on each day and the adjacent days. The higher the time overlap, the more likely the current minimum point is to be the dividing point of different time stages.

[0090] In step S214, M (e.g., 8) time stages may be preset, and thus M-2 minimum points of time overlap may be selected to determine the M-2 time stage dividing points. Thus, the time may be divided into M time stages, wherein each time stage maintains a relatively balanced amount of data information.

[0091] In step S22, it can be understood that in step S1, each time stage has been divided and determined based on the data information performance in the past week. Here, the above-mentioned divided time stages can be used as the stages of the current data information and analyzed accordingly. There are different data characteristics of character data in each current time stage. The traditional one is the actual frequency of character data, and for this we analyze the related characteristics, namely data trend performance and security performance. This means that for character data, according to the time series, it may show a certain regular distribution performance, such as the denser the distribution; and for security performance, for high-frequency character data (the actual frequency of character data here), the frequency of its adjacent data in the time series is closely related to its security, because compared with the situation where low-frequency data is distributed together, high-frequency data will present a security problem that is easier to crack when distributed together.

[0092] Analyze at each current time period:

[0093] (1) Count the actual frequency of each character data

[0094] Here, the number of occurrences of each character data in the current time stage is traversed and recorded as , and the total number of occurrences of all character data in the current time stage, denoted as C.

[0095] According to the above two, the actual frequency of each character data in the current time stage is determined, that is, ,in, Indicates the actual frequency of the sth character data in the current time period.

[0096] (2) Determine the distribution density tendency of each character data

[0097] Here, the distribution density tendency of each character data in each time period is obtained based on the analysis of all the current character data, preferably including: numbering all the character data in each time period and obtaining a numbering set of different character data; and obtaining the distribution density tendency of each character data according to the numbering set of different character data.

[0098] That is, we number the character data in the current time period in the form of 1, 2, 3, etc., and traverse the number set for each character data. Thus, we can get the number set for each character data in the current time period. Then, for the number set corresponding to each character data, we subtract the adjacent numbers, that is, That is, it represents the difference between the g-th data and the adjacent data in the s-th character data number set, referred to as the "g-th number difference" for short.

[0099] For example, there are 10 character data in total, numbered 1, 2, 3...10, of which 1, 3, 5, 7, 9 are character data a (the first character data), and 2, 4, 6, 8, 10 are character data b (the second character data). Then it is divided into two sets, that is, the number set corresponding to the first character data is (1, 3, 5, 7, 9), and the number set corresponding to the second character data is (2, 4, 6, 8, 10). At this time, = , = .

[0100] Preferably, the calculation formula for the distribution density tendency of each character data is:

[0101]

[0102] in, Indicates the distribution density tendency of the sth character data; represents the average number difference of adjacent data in the number set corresponding to the current s-th character data; G represents the amount of data in the encoding set corresponding to the current s-th character data; Indicates the difference between the g-th data and the adjacent data in the number set corresponding to the current s-th character data; Indicates the difference between the number of the g+1th data and the adjacent data in the number set corresponding to the current sth character data; Represents the normalization function. In this calculation formula, +1 is to change the final range from [-1,1] to [0,2], and 1 / 2 is to change the final range to [0,1].

[0103] The formula is passed To reflect the benchmark value of distribution density, the trend of adjacent number differences is analyzed from the perspective of overall step-by-step traversal (positive value means growth, negative value means decrease; the value itself indicates the degree of growth or decrease), so as to determine the distribution density tendency of character data based on the benchmark value.

[0104] (3) Determine the security performance of each character data

[0105] Here, that is, the security expression degree of each character data in each time stage is obtained based on the analysis of all the current character data, preferably including: among all the current character data, for each character data and according to its time series, U / 2 character data are selected on its left and right to obtain U character comparison data; wherein U is a preset value; and the security expression degree of each character data is obtained by analyzing the actual frequency of each character data and its corresponding character comparison data.

[0106] For each character data, we select U / 2 character data on the left and right according to the data in its time series, and record them as character comparison data for distinction, totaling U character comparison data, to analyze the security performance with the current character data. When the actual frequency of the current character data and its corresponding character comparison data is higher and the difference in actual frequency between the two is smaller, it means that the two maintain a higher actual frequency of character data based on the distribution of adjacent data. In layman's terms, the repetitiveness of such a situation is high, and there may be a greater risk of cracking. In some specific embodiments, U can be 30.

[0107] Preferably, the calculation formula for the security expression degree of each character data is:

[0108]

[0109] in, represents the security performance of the s-th character data; U represents the amount of character comparison data determined based on the s-th character data; Indicates the actual frequency of the sth character data; Indicates the actual frequency of the u-th character comparison data of the s-th character data; represents the normalization function. It can be understood that The calculation formula can be found in the previous article The +0.01 is to avoid the situation where the denominator is 0.

[0110] In step S23, for each stage, we analyze the actual frequency, distribution density tendency, and security performance of the character data. Since different data information performances correspond to different stages in the actual operation of the Internet information platform, we can adjust the encoding priority of the character data based on the actual frequency of the character data through the distribution density tendency and security performance. When the actual frequency is higher, we should consider its transmission efficiency more; and when the actual frequency is lower, we should consider its security more. In this way, the encoding priority of the character data is determined.

[0111] Preferably, the calculation formula for the encoding priority of each character data is:

[0112]

[0113] in, Indicates the encoding priority of the sth character data; Indicates the actual frequency of the sth character data in the current time period; Indicates the distribution density tendency of the sth character data; Indicates the security level of the s-th character data.

[0114] Thus, the encoding priority of each character data in each current time stage is determined. The greater the encoding priority, the shorter the corresponding encoding length, and thus the corresponding encoding table can be determined based on each time.

[0115] In step S3, the data of the Internet information platform is compressed and transmitted according to the coding table determined in step S2. It can be understood that multiple dynamic coding tables can be determined in the above manner, which improves the transmission efficiency while also ensuring the security of the data therein.

[0116] Embodiment 2

[0117] The present invention also provides an Internet-based information platform data security transmission system, such as Figure 4 As shown, the system includes:

[0118] The data acquisition module 10 is used to acquire platform data and perform preprocessing to obtain character data, wherein the platform data includes historical data and current data for multiple days, and the character data includes all historical character data based on time series for multiple days and all current character data;

[0119] A coding table determination module 20, used to determine a coding table based on the character data;

[0120] The compression transmission module 30 is used to compress and transmit the current data according to the coding table.

[0121] Wherein, the coding table determination module 20 includes:

[0122] A time stage division unit 21, used for dividing each day into a plurality of time stages based on all the historical character data based on the time series of the plurality of days;

[0123] A data analysis unit 22, configured to obtain the actual frequency, distribution density tendency and safety performance of each character data in each time period based on the analysis of all current character data;

[0124] The coding table determination unit 23 is used to determine the coding priority of each character data in each time stage according to the actual frequency, trend performance and security performance of each character data in each time stage to form the coding table.

[0125] In the embodiment of the Internet-based information platform data security transmission system of the present invention, all technical features of the above-mentioned Internet-based information platform data security transmission method embodiments are included, and the description and explanation content are basically the same as those of the above-mentioned data processing method embodiments, and will not be repeated here.

[0126] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. 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.

[0127] The various embodiments in this specification 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.

Claims

1. A data security transmission method for an information platform based on the Internet, characterized in that: include: Acquire platform data and perform preprocessing to obtain character data, wherein the platform data includes historical data and current data for multiple days, and the character data includes all historical character data based on time series for multiple days and all current character data; Determine a coding table based on the character data; Compressing and transmitting the current data according to the coding table; Wherein, determining the encoding table based on the character data includes: All the historical character data based on the time series of the plurality of days are divided into a plurality of time periods per day; Based on the analysis of all the current character data, the actual frequency, distribution density tendency and safety performance of each character data in each time period are obtained; Determine the coding priority of each character data in each time stage according to the actual frequency, distribution density tendency and security performance of each character data in each time stage to form the coding table; Based on the analysis of all the current character data, the distribution density tendency of each character data in each time period is obtained, including: Numbering all character data in each time period and obtaining a number set of different character data; Obtaining the distribution density tendency of each character data according to the number set of the different character data; The calculation formula for the distribution density tendency of each character data is: in, Indicates the distribution density tendency of the sth character data; represents the average number difference of adjacent data in the number set corresponding to the current s-th character data; G represents the amount of data in the encoding set corresponding to the current s-th character data; Indicates the difference between the g-th data and the adjacent data in the number set corresponding to the current s-th character data; Indicates the difference between the number of the g+1th data and the adjacent data in the number set corresponding to the current sth character data; represents the normalization function; The security performance of each character data in each time period is obtained based on the analysis of all the current character data, including: Among all the current character data, for each character data, U / 2 character data are selected on the left and right of the character data according to its time sequence to obtain U character comparison data; wherein U is a preset value; The security performance of each character data is obtained by analyzing the actual frequency of each character data and its corresponding character comparison data; The calculation formula of the security expression degree of each character data is: in, represents the security performance of the s-th character data; U represents the amount of character comparison data determined based on the s-th character data; Indicates the actual frequency of the sth character data; Indicates the actual frequency of the u-th character comparison data of the s-th character data; represents the normalization function; The calculation formula for the encoding priority of each character data is: in, Indicates the encoding priority of the sth character data; Indicates the actual frequency of the sth character data in the current time period; Indicates the distribution density tendency of the sth character data; Indicates the security level of the s-th character data.

2. The method for secure transmission of data on an Internet-based information platform according to claim 1, characterized in that: All historical character data based on time series for the multiple days are divided into multiple time periods per day, including: Acquire the amount of character data and the amount of character data types at each time of each day based on all the historical character data based on the time series of the plurality of days; The complexity of character data at each time of each day is obtained based on the amount of character data and the amount of character data types at each time of each day; Determine each minimum point according to the complexity of character data at each time of the day and calculate the time overlap of each minimum point; The time stage dividing points are determined according to the time coincidence of each minimum point, and each day is divided into multiple time stages based on the time stage dividing points.

3. The method for secure transmission of data on an Internet-based information platform as claimed in claim 2, characterized in that: The calculation formula of the character data complexity at each time of each day is: in, represents the character data complexity of the j-th minute of the i-th day, represents the amount of character data in the jth minute of the i-th day, Indicates the number of character data types in the jth minute of the i-th day, Represents the normalization function.

4. The method for securely transmitting data on an Internet-based information platform as claimed in claim 2, characterized in that: The calculation formula of the time overlap of each minimum point is: in, represents the time overlap of the zth minimum point, n represents the number of days, represents the character data complexity of the zth minimum point on the i-th day, It represents the time difference between the z-th minimum point and the minimum point with the same serial number on the adjacent day.

5. A data security transmission system for an information platform based on the Internet, characterized in that: include: A data acquisition module, used to acquire platform data and perform preprocessing to obtain character data, wherein the platform data includes historical data and current data for multiple days, and the character data includes all historical character data based on time series for multiple days and all current character data; A coding table determination module, used for determining a coding table based on the character data; A compression transmission module, used for compressing and transmitting the current data according to the coding table; Wherein, the coding table determination module includes: A time stage division unit, used for dividing each day into a plurality of time stages based on all the historical character data based on the time series of the plurality of days; A data analysis unit, configured to obtain the actual frequency, distribution density tendency and safety performance of each character data in each time period based on the analysis of all current character data; Based on the analysis of all the current character data, the distribution density tendency of each character data in each time period is obtained, including: Numbering all character data in each time period and obtaining a number set of different character data; Obtaining the distribution density tendency of each character data according to the number set of the different character data; The calculation formula for the distribution density tendency of each character data is: in, Indicates the distribution density tendency of the sth character data; represents the average number difference of adjacent data in the number set corresponding to the current s-th character data; G represents the amount of data in the encoding set corresponding to the current s-th character data; Indicates the difference between the g-th data and the adjacent data in the number set corresponding to the current s-th character data; Indicates the difference between the number of the g+1th data and the adjacent data in the number set corresponding to the current sth character data; represents the normalization function; The security performance of each character data in each time period is obtained based on the analysis of all the current character data, including: Among all the current character data, for each character data, U / 2 character data are selected on the left and right of the character data according to its time sequence to obtain U character comparison data; wherein U is a preset value; The security performance of each character data is obtained by analyzing the actual frequency of each character data and its corresponding character comparison data; The calculation formula of the security expression degree of each character data is: in, represents the security performance of the s-th character data; U represents the amount of character comparison data determined based on the s-th character data; Indicates the actual frequency of the sth character data; Indicates the actual frequency of the u-th character comparison data of the s-th character data; represents the normalization function; A coding table determination unit, used to determine the coding priority of each character data in each time stage according to the actual frequency, distribution density tendency and security expression of each character data in each time stage, so as to form the coding table; The calculation formula for the encoding priority of each character data is: in, Indicates the encoding priority of the sth character data; Indicates the actual frequency of the sth character data in the current time period; Indicates the distribution density tendency of the sth character data; Indicates the security level of the s-th character data.

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